Cognex Corporation

United States of America

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G06K 7/10 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation 105
G06K 7/14 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light 80
G06T 7/00 - Image analysis 65
H04N 5/225 - Television cameras 56
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09 - Scientific and electric apparatus and instruments 76
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1.

COGNEX

      
Application Number 1920732
Status Registered
Filing Date 2026-01-22
Registration Date 2026-01-22
Owner Cognex Corporation (USA)
NICE Classes  ?
  • 09 - Scientific and electric apparatus and instruments
  • 42 - Scientific, technological and industrial services, research and design

Goods & Services

Vision software and hardware; machine vision software and hardware; computer vision software and hardware; AI-powered vision software and hardware, machine vision software and hardware, and computer vision software and hardware; computer hardware and software for AI-powered vision technology, machine vision technology and computer vision technology incorporating machine learning, deep learning, edge learning or zero-shot learning; downloadable and recorded computer software for machine vision, machine learning, deep learning, artificial intelligence, and applications using deep learning, algorithm-based machine learning, imaging-based inspection and analysis technologies; computer machine vision hardware, namely barcode readers, image and data readers, scanners, and cameras; computers software and software platforms for machine vision; downloadable and recorded computer software for acquiring, processing, analysing and understanding digital images, and extracting visual data; downloadable and recorded computer software for logistics and logistics applications; optical inspection apparatus for industrial use; portable and handheld digital electronic devices for recording, organizing, transmitting, manipulating, and reviewing text, data, image, and audio files; sensor, detection, data capture and monitoring apparatus and software; image scanning apparatus; bar code decoders, terminals, scanners and readers; inspection mirrors; laser detectors and sensors; cameras containing image sensors and linear image sensors; optical character readers; downloadable software used for monitoring, measurement, gauging, defect detection, classification, verification, barcode reading, and inspecting purposes; computer software and hardware for collecting, transmitting, managing and analysing data in the nature of processing images, graphics and text for managing networked machine vision readers and scanners used to read, measure, identify, analyse, inspect, and detect defects in products; computer software and hardware for providing data forwarding services and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyse various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; computer software and hardware for providing data analytics services in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify and analyse various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; downloadable software for use with portable and handheld digital electronic devices for recording, organizing, transmitting, manipulating, and reviewing text, data, image, and audio files. Quality control and authentication services; design and development of computer hardware and software; design and development of computer hardware including artificial intelligence hardware, image scanning apparatus, bar code decoders, terminals, scanners, readers, inspection mirrors, laser detectors, optical inspection apparatus, data capture and monitoring apparatus, sensors, verifiers, and cameras for industrial use; providing technical information and consulting in the field of machine vision, machine learning, or artificial intelligence; providing technological information and consulting in the field of vision or data analytics; providing online non-downloadable web-based software for machine vision; software as a service [SaaS] and platform as a service (PaaS) featuring software for machine vision; providing AI-powered non-downloadable vision software, non-downloadable machine vision software, and non-downloadable computer vision software, AI-powered non-downloadable vision software, non-downloadable machine vision software, and non-downloadable computer vision software incorporating machine learning, deep learning, edge learning or zero-shot learning, online non-downloadable software for applications using artificial intelligence, deep learning, algorithm- based machine learning, machine vision, and imaging-based automatic inspection and analysis technologies, online non-downloadable software for acquiring, processing, analysing and understanding digital images and extracting visual data, online non-downloadable software for monitoring, measurement, gauging, defect detection, classification, verification, barcode reading, and inspecting purposes, online non-downloadable software for collecting, transmitting, managing and analysing data in the nature of processing images, graphics and text for managing networked machine vision readers and scanners used to read, measure, identify, analyse, inspect, and detect defects in products, online non-downloadable software for providing data forwarding services and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyse various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications, online non-downloadable software for providing data analytics services in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify and analyse various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications.

2.

Illumination assembly for an imaging system

      
Application Number 29986227
Grant Number D1122335
Status In Force
Filing Date 2025-01-17
First Publication Date 2026-04-14
Grant Date 2026-04-14
Owner Cognex Corporation (USA)
Inventor
  • Fernández Dorado, José
  • Garcia Campos, Pablo
  • Visser, Martijn
  • Weber, Andreas
  • Nunnink, Laurens

3.

SYSTEMS AND METHODS FOR CONFIGURING MACHINE VISION TUNNELS

      
Application Number 19114059
Status Pending
Filing Date 2023-09-22
First Publication Date 2026-04-09
Owner Cognex Corporation (USA)
Inventor
  • Sanz Rodriguez, Saul
  • Ruetten, Jens
  • Depre, Tony
  • Stroo, Bart

Abstract

Systems and methods are provided for generating machine vision tunnel configurations. The systems and methods described herein may automatically generate a configuration summary of tunnel configurations for a prospective machine vision tunnel based on received parameters. The configuration summary may be modified via operator interaction with the configuration summary. The systems and methods described herein may also automatically generate and transmit a bill of materials report, a tunnel commissioning report, or a graphical representation of an approved tunnel configuration, including generating some or all of these data sets dynamically in response to operator inputs.

IPC Classes  ?

  • G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
  • G06Q 10/0875 - Itemisation or classification of parts, supplies or services, e.g. bill of materials

4.

METHODS AND APPARATUS FOR DETERMINING VOLUMES OF 3D IMAGES

      
Application Number 19255945
Status Pending
Filing Date 2025-06-30
First Publication Date 2026-04-02
Owner Cognex Corporation (USA)
Inventor Moreno, Daniel Alejandro

Abstract

The techniques described herein relate to methods, apparatus, and computer readable media configured to determine an estimated volume of an object captured by a three-dimensional (3D) point cloud. A 3D point cloud comprising a plurality of 3D points and a reference plane in spatial relation to the 3D point cloud is received. A 2D grid of bins is configured along the reference plane, wherein each bin of the 2D grid comprises a length and width that extends along the reference plane. For each bin of the 2D grid, a number of 3D points in the bin and a height of the bin from the reference plane is determined. An estimated volume of an object captured by the 3D point cloud based on the calculated number of 3D points in each bin and the height of each bin.

IPC Classes  ?

  • G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
  • G06T 17/00 - 3D modelling for computer graphics
  • G06V 20/64 - Three-dimensional objects

5.

SLX

      
Application Number 1908030
Status Registered
Filing Date 2026-02-19
Registration Date 2026-02-19
Owner Cognex Corporation (USA)
NICE Classes  ? 09 - Scientific and electric apparatus and instruments

Goods & Services

Integrated computer systems comprised of computer hardware, software, and camera for machine vision manufacture and assembly applications, machine vision readers and scanners comprised of hardware and software used for machine vision applications and/or to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications.

6.

SYSTEM AND METHOD FOR APPLYING DEEP LEARNING TOOLS TO MACHINE VISION AND INTERFACE FOR THE SAME

      
Application Number 19219781
Status Pending
Filing Date 2025-05-27
First Publication Date 2026-03-19
Owner Cognex Corporation (USA)
Inventor
  • Wyss, Reto
  • Petry, Iii, John P.

Abstract

This invention overcomes disadvantages of the prior art by providing a vision system and method of use, and graphical user interface (GUI), which employs a camera assembly having an on-board processor of low to modest processing power. At least one vision system tool analyzes image data, and generates results therefrom, based upon a deep learning process. A training process provides training image data to a processor remote from the on-board processor to cause generation of the vision system tool therefrom, and provides a stored version of the vision system tool for runtime operation on the on-board processor. The GUI allows manipulation of thresholds applicable to the vision system tool and refinement of training of the vision system tool by the training process. A scoring process allows unlabeled images from a set of acquired and/or stored images to be selected automatically for labelling as training images using a computed confidence score.

IPC Classes  ?

  • G06V 30/19 - Recognition using electronic means
  • G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
  • G06F 3/04842 - Selection of displayed objects or displayed text elements
  • G06T 7/10 - SegmentationEdge detection
  • G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects

7.

SLX

      
Application Number 246363800
Status Pending
Filing Date 2026-02-19
Owner Cognex Corporation (USA)
NICE Classes  ? 09 - Scientific and electric apparatus and instruments

Goods & Services

(1) Integrated computer systems comprised of computer hardware, software, and camera for machine vision manufacture and assembly applications, machine vision readers and scanners comprised of hardware and software used for machine vision applications and/or to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications.

8.

WORKING-RANGE EXTENDING PHASE PLATE, ASSOCIATED IMAGING SYSTEM, AND METHOD

      
Application Number 19295243
Status Pending
Filing Date 2025-08-08
First Publication Date 2026-02-12
Owner Cognex Corporation (USA)
Inventor
  • Filhaber, John
  • Yang, Jia
  • Fernández Dorado, José

Abstract

A working-range-extending phase plate includes a central region, an inner annular region surrounding the central region, and an outer annular region surrounding the central region and the inner annular region. The central region has a central phase-transmission function. The inner annular region has an inner phase-transmission function. The outer annular region has an outer phase-transmission function. Respective magnitudes of the central, the inner, and the outer phase-transmission functions are, as a function of radial distance from an optical axis of the phase plate, one of: (i) constant, increasing, and increasing, (ii) decreasing, constant, and increasing, or (iii) decreasing, decreasing, and constant.

IPC Classes  ?

  • G02B 27/00 - Optical systems or apparatus not provided for by any of the groups ,
  • G02B 5/00 - Optical elements other than lenses
  • G02B 5/30 - Polarising elements

9.

WORKING-RANGE EXTENDING PHASE PLATE, ASSOCIATED IMAGING SYSTEM, AND METHOD

      
Application Number US2025041358
Publication Number 2026/036092
Status In Force
Filing Date 2025-08-08
Publication Date 2026-02-12
Owner COGNEX CORPORATION (USA)
Inventor
  • Filhaber, John
  • Yang, Jia
  • Fernández Dorado, José

Abstract

A working-range-extending phase plate includes a central region, an inner annular region surrounding the central region, and an outer annular region surrounding the central region and the inner annular region. The central region has a central phase-transmission function. The inner annular region has an inner phase-transmission function. The outer annular region has an outer phase-transmission function. Respective magnitudes of the central, the inner, and the outer phase-transmission functions are, as a function of radial distance from an optical axis of the phase plate, one of: (i) constant, increasing, and increasing, (ii) decreasing, constant, and increasing, or (iii) decreasing, decreasing, and constant.

IPC Classes  ?

  • G02B 27/00 - Optical systems or apparatus not provided for by any of the groups ,
  • G02B 27/58 - Optics for apodization or superresolutionOptical synthetic aperture systems
  • G06K 7/10 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation

10.

SYSTEMS AND METHODS FOR HIGH-SPEED, HIGH-ACCURACY SYMBOL PROCESSING

      
Application Number 19258296
Status Pending
Filing Date 2025-07-02
First Publication Date 2026-01-08
Owner Cognex Corporation (USA)
Inventor
  • Chen, Mo
  • Wang, Lei

Abstract

The techniques described herein relate to systems and methods for processing symbols of various types with high speed and high accuracy. The techniques can include accessing an image of a symbol comprising embedded information, inputting the image of the symbol into a deep learning module, and generating, with the deep learning module, predicted embedded information based on the image of the symbol. The predicted embedded information can include codewords, which correspond to the embedded information. The codewords can be further processed for generating the embedded information. Such techniques can enable fast and accurate processing of symbols of various types.

IPC Classes  ?

  • G06K 7/14 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light

11.

SYSTEMS AND METHODS FOR HIGH-SPEED, HIGH-ACCURACY SYMBOL PROCESSING

      
Application Number US2025036275
Publication Number 2026/011064
Status In Force
Filing Date 2025-07-02
Publication Date 2026-01-08
Owner COGNEX CORPORATION (USA)
Inventor
  • Chen, Mo
  • Wang, Lei

Abstract

The techniques described herein relate to systems and methods for processing symbols of various types with high speed and high accuracy. The techniques can include accessing an image of a symbol comprising embedded information, inputting the image of the symbol into a deep learning module, and generating, with the deep learning module, predicted embedded information based on the image of the symbol. The predicted embedded information can include codewords, which correspond to the embedded information. The codewords can be further processed for generating the embedded information. Such techniques can enable fast and accurate processing of symbols of various types.

IPC Classes  ?

  • G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
  • G06K 7/14 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
  • G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
  • G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
  • G06V 10/32 - Normalisation of the pattern dimensions
  • G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
  • G06V 30/166 - Normalisation of pattern dimensions
  • G06V 30/224 - Character recognition characterised by the type of writing of printed characters having additional code marks or containing code marks
  • G06V 30/26 - Techniques for post-processing, e.g. correcting the recognition result
  • G06V 30/413 - Classification of content, e.g. text, photographs or tables

12.

SYSTEMS AND METHODS FOR HIGH-RESOLUTION MULTILINE IMAGING

      
Application Number US2025035934
Publication Number 2026/006834
Status In Force
Filing Date 2025-06-30
Publication Date 2026-01-02
Owner COGNEX CORPORATION (USA)
Inventor
  • Wagner, Christoph T.
  • Wang, Lei
  • Jacobson, Lowell D.
  • Shivaram, Guruprasad
  • Huber, Bertram

Abstract

Systems and associated methods implement and/or perform acquiring a plurality of images with the camera, including: activating one or more illumination sources to provide different illumination conditions according to a predetermined order, and under each of the plurality of illumination conditions, capturing one of the plurality of images. Between the acquiring of successive images, a transport device is configured to cause the object to move a distance relative to the camera in a movement direction transverse to a row direction of the camera that is equal to (I).

IPC Classes  ?

13.

SYSTEM AND METHOD FOR ILLUMINATING AND IMAGING SURFACES IN MOTION

      
Application Number US2025031743
Publication Number 2025/250999
Status In Force
Filing Date 2025-05-30
Publication Date 2025-12-04
Owner COGNEX CORPORATION (USA)
Inventor
  • Jacobson, Lowell, D.
  • Wang, Lei
  • Makoto, Iwamoto
  • Kawai, Keiji

Abstract

This invention provides a system and method for imaging a surface, moving in a motion direction, with a vision system having at least a first camera, defining an optical axis, transmitting acquired images of the surface to a vision system processor. At least a first bar illuminator extends in a direction transverse to the motion direction. The bar illuminator defines opposing, interleaved arrays of localized solid state light sources (e.g. LEDs). Each of the arrays is oriented to propagate light at a respective, opposing oblique angle with respect to the optical axis, which can be independently activated as respective image(s) are acquired. The first bar illuminator is oriented with respect to the surface so as to project arrays that propagate light along a first plane defining a first non-parallel angle versus the optical axis. The two non-parallel angles can each define opposing angles with respect to the optical axis.

IPC Classes  ?

  • G02B 26/10 - Scanning systems
  • H04N 1/12 - Scanning arrangements using the sheet-feed movement as the slow scanning component

14.

Imaging device with cover plate

      
Application Number 29824856
Grant Number D1101015
Status In Force
Filing Date 2022-01-27
First Publication Date 2025-11-04
Grant Date 2025-11-04
Owner COGNEX CORPORATION (USA)
Inventor
  • Fluegge, Kai
  • Rodriguez, Saul Sanz

15.

Imaging device with housing

      
Application Number 29918278
Grant Number D1099200
Status In Force
Filing Date 2023-11-27
First Publication Date 2025-10-21
Grant Date 2025-10-21
Owner COGNEX CORPORATION (USA)
Inventor
  • Orban, Laszlo
  • Campos, Pablo Garcia
  • Könnecke, Christoph
  • Schnabler, Roman
  • Mayer, Lars

16.

SYSTEMS AND METHODS FOR COMMISSIONING A MACHINE VISION SYSTEM

      
Application Number 18864052
Status Pending
Filing Date 2023-05-09
First Publication Date 2025-10-09
Owner COGNEX CORPORATION (USA)
Inventor
  • Wurz, Caitlin
  • Atkins, Iii, Henry
  • Tanmay, Sinha
  • Surana, Deepak
  • Gauthier, Georges
  • El-Barkouky, Ahmed
  • Brodeur, Patrick
  • Lutzke, Patrick
  • Ruetten, Jens
  • Depre, Tony

Abstract

Methods and systems are provided for commissioning machine vision systems. The methods and systems described herein may automatically configure, or otherwise assist users in configuring, a machine vision system based on a specification package.

IPC Classes  ?

  • G06T 7/80 - Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration

17.

PINPOINT

      
Application Number 1880483
Status Registered
Filing Date 2025-05-20
Registration Date 2025-05-20
Owner Cognex Corporation (USA)
NICE Classes  ?
  • 09 - Scientific and electric apparatus and instruments
  • 42 - Scientific, technological and industrial services, research and design

Goods & Services

Downloadable and recorded computer software for acquiring, processing, analyzing and understanding digital images, and extracting visual data; downloadable and recorded computer software for industrial machine vision, machine learning, deep learning, artificial intelligence, and applications using deep learning, algorithm-based machine learning, machine vision, and imaging-based automatic inspection and analysis technologies; downloadable and recorded computer software for logistics applications. Providing online non-downloadable software for acquiring, processing, analyzing and understanding digital images and extracting visual data; providing online non-downloadable software for industrial machine vision, machine learning, deep learning, artificial intelligence, and applications using deep learning, algorithm- based machine learning, machine vision, and imaging-based automatic inspection and analysis technologies; providing online non-downloadable software for logistics applications; providing online non-downloadable web-based software for machine vision; providing online non-downloadable cloud-computing software for machine vision.

18.

SYSTEM AND METHOD FOR FIELD CALIBRATION OF A VISION SYSTEM

      
Application Number 18864217
Status Pending
Filing Date 2023-05-09
First Publication Date 2025-10-02
Owner COGNEX CORPORATION (USA)
Inventor
  • Wurz, Caitlin
  • Liu, Humberto Andres Leon
  • Brodeur, Patrick
  • Gauthier, Georges
  • Sposato, Kyle
  • Corbett, Michael
  • El-Barkouky, Ahmed

Abstract

A method for three-dimensional (3D) field calibration of a machine vision system includes receiving a set of calibration parameters and an identification of one or more machine vision system imaging devices, determining a camera acquisition parameter for calibration based on the set of calibration parameters, validating the set of calibration parameters and the camera acquisition parameter, and controlling the imaging device(s) to collect image data of a calibration target. The image data may be collected using the determined camera acquisition parameter. The method further includes generating a set of calibration data for the imaging device(s) using the collected image data for the imaging device(s). The set of calibration data can include a maximum error. The method further includes generating a report including the set of calibration data for the imaging device(s) and an indication of whether the maximum error for the imaging device(s) is within an acceptable tolerance and displaying the report on a display.

IPC Classes  ?

  • G06T 7/80 - Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
  • G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
  • H04N 17/00 - Diagnosis, testing or measuring for television systems or their details
  • H04N 23/90 - Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums

19.

SYSTEM AND METHOD FOR DYNAMIC TESTING OF A MACHINE VISION SYSTEM

      
Application Number 18864223
Status Pending
Filing Date 2023-05-09
First Publication Date 2025-09-25
Owner COGNEX CORPORATION (USA)
Inventor
  • Wurz, Caitlin
  • Liu, Iii, Humberto Andres Leon
  • Brodeur, Patrick
  • Gauthier, Georges
  • Sposato, Kyle
  • Corbett, Michael
  • Sanz Rodriguez, Saul
  • Ruetten, Jens

Abstract

A method for dynamic testing of a machine vision system includes receiving a set of testing parameters and a selection of a tunnel system. The machine vision system can include the tunnel system and the tunnel system can include a conveyor and at least one imaging device. The method can further include validating the testing parameters and controlling the at least one imaging device to acquire a set of image data of a testing target positioned at a predetermined justification on the conveyor. The testing target can include a plurality of target symbols. The method can further include determining a test result by analyzing the set of image data to determine if the at least one imaging device reads a target symbol associated with the at least one imaging device and generating a report including the test result.

IPC Classes  ?

  • H04N 17/00 - Diagnosis, testing or measuring for television systems or their details

20.

Machine vision system and method with hybrid zoom optical assembly

      
Application Number 18858078
Grant Number 12450455
Status In Force
Filing Date 2023-04-28
First Publication Date 2025-09-04
Grant Date 2025-10-21
Owner COGNEX CORPORATION (USA)
Inventor
  • Fernandez Dorado, Jose
  • Nunnink, Laurens

Abstract

An optical assembly for a machine vision system having an image sensor includes a lens assembly and a motor system coupled to the lens assembly. The lens assembly can include a plurality of solid lens elements and a liquid lens, where the liquid lens includes an adjustable membrane. The motor system can be configured to move the lens assembly to adjust a distance between the lens assembly and the image sensor of the vision system.

IPC Classes  ?

  • G02B 7/09 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses with mechanism for focusing or varying magnification adapted for automatic focusing or varying magnification
  • G02B 26/00 - Optical devices or arrangements for the control of light using movable or deformable optical elements
  • G06K 7/10 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation
  • G06K 7/14 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light

21.

STATISTICAL ANALYSIS-BASED TECHNIQUES FOR DETERMINING A PREFERRED TRANSFORMATION TYPE FOR 3D IMAGE PROCESSING USING MACHINE LEARNING

      
Application Number US2025017374
Publication Number 2025/184198
Status In Force
Filing Date 2025-02-26
Publication Date 2025-09-04
Owner COGNEX CORPORATION (USA)
Inventor
  • Zhu, Hongwei
  • Moreno, Daniel, Alejandro

Abstract

The techniques described herein relate to methods and systems for three-dimensional (3D) image processing using deep learning model pre-trained with two-dimensional (2D) images. The techniques include transforming a 3D representation to a 2D map, which can be input to the model. The output of the model could be a defect segmentation mask, or a probability of the input belonging to a given category. The input 2D image can result from a particular transformation configuration. The techniques described herein provide for an effective and efficient method of identifying a transformation type for applications such as 3D data-based classification, anomaly detection and segmentation. The techniques described herein perform statistical analysis over a set of training samples to identify a transformation type. The statistical analysis can include histograms of pixel values.

IPC Classes  ?

  • G06T 7/00 - Image analysis
  • G06T 7/11 - Region-based segmentation
  • G06T 7/174 - SegmentationEdge detection involving the use of two or more images

22.

STATISTICAL ANALYSIS-BASED TECHNIQUES FOR DETERMINING A PREFERRED TRANSFORMATION TYPE FOR 3D IMAGE PROCESSING USING MACHINE LEARNING

      
Application Number 19064278
Status Pending
Filing Date 2025-02-26
First Publication Date 2025-08-28
Owner Cognex Corporation (USA)
Inventor
  • Zhu, Hongwei
  • Moreno, Daniel Alejandro

Abstract

The techniques described herein relate to methods and systems for three-dimensional (3D) image processing using deep learning model pre-trained with two-dimensional (2D) images. The techniques include transforming a 3D representation to a 2D map, which can be input to the model. The output of the model could be a defect segmentation mask, or a probability of the input belonging to a given category. The input 2D image can result from a particular transformation configuration. The techniques described herein provide for an effective and efficient method of identifying a transformation type for applications such as 3D data-based classification, anomaly detection and segmentation. The techniques described herein perform statistical analysis over a set of training samples to identify a transformation type. The statistical analysis can include histograms of pixel values.

IPC Classes  ?

  • G06V 20/64 - Three-dimensional objects
  • G06T 7/00 - Image analysis
  • G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
  • G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
  • G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
  • G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
  • G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
  • G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
  • G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

23.

SLX

      
Serial Number 99350215
Status Pending
Filing Date 2025-08-21
Owner Cognex Corporation (USA)
NICE Classes  ? 09 - Scientific and electric apparatus and instruments

Goods & Services

Integrated computer systems comprised of computer hardware, software, and camera for machine vision manufacture and assembly applications, Machine vision readers and scanners comprised of hardware and software used for machine vision applications and/or to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications.

24.

RANGEMAX

      
Application Number 1865538
Status Registered
Filing Date 2025-05-20
Registration Date 2025-05-20
Owner Cognex Corporation (USA)
NICE Classes  ? 09 - Scientific and electric apparatus and instruments

Goods & Services

Image formation subsystem comprised of an optical assembly used for machine vision and automatic identification applications.

25.

ONEVISION

      
Application Number 1864941
Status Registered
Filing Date 2025-05-23
Registration Date 2025-05-23
Owner Cognex Corporation (USA)
NICE Classes  ?
  • 09 - Scientific and electric apparatus and instruments
  • 42 - Scientific, technological and industrial services, research and design

Goods & Services

Computers including integrated software used for machine vision; downloadable software platform for machine vision; downloadable software for machine vision; downloadable artificial intelligence software for machine vision; downloadable cloud computing software for machine vision. Non-downloadable web-based software for machine vision; non-downloadable web-based artificial intelligence software for machine vision; non-downloadable software platform for machine vision; non-downloadable cloud-computing software for machine vision; software as a service featuring software for machine vision.

26.

VISION SOLUTIONS

      
Serial Number 99289253
Status Pending
Filing Date 2025-07-17
Owner Cognex Corporation (USA)
NICE Classes  ? 42 - Scientific, technological and industrial services, research and design

Goods & Services

Computer services, namely, designing and implementing computer software for machine vision applications for others

27.

System and method for applying deep learning tools to machine vision and interface for the same

      
Application Number 17117105
Grant Number 12361100
Status In Force
Filing Date 2020-12-09
First Publication Date 2025-07-15
Grant Date 2025-07-15
Owner Cognex Corporation (USA)
Inventor
  • Petry, Iii, John P.
  • Wyss, Reto

Abstract

This invention overcomes disadvantages of the prior art by providing a vision system and method of use, and graphical user interface (GUI), which employs a camera assembly having an on-board processor of low to modest processing power. At least one vision system tool analyzes image data, and generates results therefrom, based upon a deep learning process. A training process provides training image data to a processor (optionally) remote from the on-board processor to cause generation of the vision system tool therefrom, and provides a stored version of the vision system tool for runtime operation on the on-board processor. The GUI allows manipulation of thresholds applicable to the vision system tool and refinement of training of the vision system tool by the training process.

IPC Classes  ?

  • G06F 18/40 - Software arrangements specially adapted for pattern recognition, e.g. user interfaces or toolboxes therefor
  • G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
  • G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
  • G06F 18/21 - Design or setup of recognition systems or techniquesExtraction of features in feature spaceBlind source separation
  • G06F 18/214 - Generating training patternsBootstrap methods, e.g. bagging or boosting
  • G06N 3/04 - Architecture, e.g. interconnection topology
  • G06N 3/08 - Learning methods
  • G06V 10/70 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning

28.

SYSTEMS AND METHODS FOR TUNING SYMBOL READERS

      
Application Number 18990344
Status Pending
Filing Date 2024-12-20
First Publication Date 2025-06-26
Owner Cognex Corporation (USA)
Inventor
  • Ye, Xiangyun
  • Pillai, Ganesa Rukmani Ramdas
  • Fan, Hongyi

Abstract

The techniques described herein relate to methods and systems for processing symbols quickly and robustly. The techniques can include using a pre-trained deep learning model to generate a region of interest (ROI) of an image captured by an imaging device according to a set of attributes associated with the imaging device. The techniques can include using a machine learning model to generate a quality metric for the image. The quality metric can indicate a measurement that the ROI of the symbol can be decoded. The set of attributes of the imaging device can be adjusted based on the quality metric before taking another image until a quality metric satisfies predetermined criteria. Such techniques enable fast and robust symbol processing with compact system configurations and easily setup components.

IPC Classes  ?

  • G06K 7/14 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
  • G06K 7/10 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation

29.

SYSTEMS AND METHODS FOR TUNING SYMBOL READERS

      
Application Number US2024061380
Publication Number 2025/137512
Status In Force
Filing Date 2024-12-20
Publication Date 2025-06-26
Owner COGNEX CORPORATION (USA)
Inventor
  • Ye, Xiangyun
  • Pillai, Ganesa, Rukmani Ramdas
  • Fan, Hongyi

Abstract

The techniques described herein relate to methods (1300) and systems (300) for processing symbols (202, 204, 208, 210, 212) quickly and robustly. The techniques can include using a pre-trained deep learning model (402) to generate (1102,1202,1304) a region of interest (612), ROI, of an image (1006a, 1006b, 1006c) captured (1302) by an imaging device (302) according to a set of attributes (1002, 1004) associated with the imaging device. The techniques can include using a machine learning model (606) to generate (1316) a quality metric for the image. The quality metric can indicate a measurement that the ROI of the symbol can be decoded (906a). The set of attributes of the imaging device can be adjusted (1320) based on the quality metric before taking another image until a quality metric satisfies predetermined criteria. Such techniques enable fast and robust symbol processing with compact system configurations and easily setup components.

IPC Classes  ?

  • G06V 10/14 - Optical characteristics of the device performing the acquisition or on the illumination arrangements
  • G06K 7/14 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
  • G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
  • G06V 10/776 - ValidationPerformance evaluation
  • G06V 10/98 - Detection or correction of errors, e.g. by rescanning the pattern or by human interventionEvaluation of the quality of the acquired patterns

30.

METHODS, SYSTEMS, AND MEDIA FOR GENERATING IMAGES OF MULTIPLE SIDES OF AN OBJECT

      
Application Number 18809524
Status Pending
Filing Date 2024-08-20
First Publication Date 2025-06-19
Owner COGNEX CORPORATION (USA)
Inventor
  • El-Barkouky, Ahmed
  • Negro, James A.
  • Ye, Xiangyun

Abstract

In accordance with some embodiments of the disclosed subject matter, methods, systems, and media for generating images of multiple sides of an object are provided. In some embodiments, a method comprises receiving information indicative of a 3D pose of a first object in a first coordinate space at a first time; receiving a group of images captured using at least one image sensor, each image associated with a field of view within the first coordinate space; mapping at least a portion of a surface of the first object to a 2D area with respect to the image based on the 3D pose of the first object; associating, for images including the surface, a portion of that image with the surface of the first object based on the 2D area; and generating a composite image of the surface using images associated with the surface.

IPC Classes  ?

  • G06T 15/10 - Geometric effects
  • G06T 3/04 - Context-preserving transformations, e.g. by using an importance map
  • G06T 7/70 - Determining position or orientation of objects or cameras
  • G06T 17/00 - 3D modelling for computer graphics

31.

ONEVISION

      
Application Number 241207400
Status Pending
Filing Date 2025-05-23
Owner Cognex Corporation (USA)
NICE Classes  ?
  • 09 - Scientific and electric apparatus and instruments
  • 42 - Scientific, technological and industrial services, research and design

Goods & Services

(1) Computers including integrated software used for machine vision; downloadable software platform for machine vision; downloadable software for machine vision; downloadable artificial intelligence software for machine vision; downloadable cloud computing software for machine vision. (1) Non-downloadable web-based software for machine vision; non-downloadable web-based artificial intelligence software for machine vision; non-downloadable software platform for machine vision; non-downloadable cloud-computing software for machine vision; software as a service featuring software for machine vision.

32.

Systems and Methods for Stitching Sequential Images of an Object

      
Application Number 19028780
Status Pending
Filing Date 2025-01-17
First Publication Date 2025-05-22
Owner COGNEX CORPORATION (USA)
Inventor
  • Negro, James A.
  • Ye, Xiangyun
  • El-Barkouky, Ahmed

Abstract

A system may comprise a transport device for moving at least one object, wherein at least one substantially planar surface of the object is moved in a known plane locally around a viewing area, wherein the substantially planar surface of the object is occluded except when the at least one substantially planar surface passes by the viewing area, at least one 2D digital optical sensor configured to capture at least two sequential 2D digital images of the at least one substantially planar surface of the at least one object that is moved in the known plane around the viewing area, and a controller operatively coupled to the 2D digital optical sensor, the controller performing the steps of: a) receiving a first digital image, b) receiving a second digital image, and c) stitching the first digital image and the second digital image using a stitching algorithm to generate a stitched image.

IPC Classes  ?

  • G06T 11/60 - Editing figures and textCombining figures or text
  • G06K 19/06 - Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
  • G06T 3/18 - Image warping, e.g. rearranging pixels individually
  • G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
  • G06V 20/40 - ScenesScene-specific elements in video content
  • H04N 23/698 - Control of cameras or camera modules for achieving an enlarged field of view, e.g. panoramic image capture
  • H04N 23/74 - Circuitry for compensating brightness variation in the scene by influencing the scene brightness using illuminating means

33.

SYSTEM AND METHOD FOR EXTRACTING AND MEASURING SHAPES OF OBJECTS HAVING CURVED SURFACES WITH A VISION SYSTEM

      
Application Number 19032355
Status Pending
Filing Date 2025-01-20
First Publication Date 2025-05-22
Owner Cognex Corporation (USA)
Inventor
  • Zhu, Hongwei
  • Moreno, Daniel

Abstract

This invention provides a system and method that efficiently detects objects imaged using a 3D camera arrangement by referencing a cylindrical or spherical surface represented by a point cloud, and measures variant features of an extracted object including volume, height, and center of mass, bounding box, and other relevant metrics. The system and method, advantageously, operates directly on unorganized and un-ordered points, requiring neither a mesh/surface reconstruction nor voxel grid representation of object surfaces in a point cloud. Based upon a cylinder/sphere reference model, an acquired 3D point cloud is flattened. Object (blob) detection is carried out in the flattened 3D space, and objects are converted back to the 3D space to compute the features, which can include regions that differ from the regular shape of the cylinder/sphere. Downstream utilization devices and/or processes, such as part reject mechanism and/or robot manipulators can act on the identified feature data.

IPC Classes  ?

  • G06T 7/00 - Image analysis
  • G06T 3/067 - Reshaping or unfolding 3D tree structures onto 2D planes
  • G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]Salient regional features

34.

RANGEMAX

      
Application Number 241346700
Status Pending
Filing Date 2025-05-20
Owner Cognex Corporation (USA)
NICE Classes  ? 09 - Scientific and electric apparatus and instruments

Goods & Services

(1) Image formation subsystem comprised of an optical assembly used for machine vision and automatic identification applications.

35.

PINPOINT

      
Application Number 242944000
Status Pending
Filing Date 2025-05-20
Owner Cognex Corporation (USA)
NICE Classes  ?
  • 09 - Scientific and electric apparatus and instruments
  • 42 - Scientific, technological and industrial services, research and design

Goods & Services

(1) Downloadable and recorded computer software for acquiring, processing, analyzing and understanding digital images, and extracting visual data; downloadable and recorded computer software for industrial machine vision, machine learning, deep learning, artificial intelligence, and applications using deep learning, algorithm-based machine learning, machine vision, and imaging-based automatic inspection and analysis technologies; downloadable and recorded computer software for logistics applications. (1) Providing online non-downloadable software for acquiring, processing, analyzing and understanding digital images and extracting visual data; providing online non-downloadable software for industrial machine vision, machine learning, deep learning, artificial intelligence, and applications using deep learning, algorithm- based machine learning, machine vision, and imaging-based automatic inspection and analysis technologies; providing online non-downloadable software for logistics applications; providing online non-downloadable web-based software for machine vision; providing online non-downloadable cloud-computing software for machine vision.

36.

EASY LINE FINDER BASED ON DYNAMIC TIME WARPING METHOD

      
Application Number 18834064
Status Pending
Filing Date 2022-01-27
First Publication Date 2025-05-01
Owner COGNEX CORPORATION (USA)
Inventor
  • Wang, Qian
  • Wei, Jia-Hui
  • Li, Yong
  • Fan, Qian-Feng

Abstract

A system and method of generating training results using a vision system is provided. At least one training image is selected, in which the image includes at least one representative feature. A line-finding tool searches the at least one training image for the at least one representative feature using at least one caliper, and a projection signal is generated from projection data associated with the at least one caliper. A filter signal is generated from the projection signal. An index value is generated by finding an edge of the at least one caliper nearest to an expected feature.

IPC Classes  ?

  • G06T 7/13 - Edge detection
  • G06T 1/00 - General purpose image data processing
  • G06T 3/18 - Image warping, e.g. rearranging pixels individually
  • G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods

37.

METHODS AND SYSTEMS FOR THREE-DIMENSIONAL (3D) INSPECTION

      
Application Number US2024047750
Publication Number 2025/064860
Status In Force
Filing Date 2024-09-20
Publication Date 2025-03-27
Owner COGNEX CORPORATION (USA)
Inventor
  • Moreno, Daniel, Alejandro
  • Zhu, Hongwei
  • Schaufuβ, Martin
  • Zadeh, Ali
  • Li, Chenye
  • Moed, Michael, C.

Abstract

The techniques described herein relate to methods and systems for three-dimensional (3D) inspection using deep learning model pre-trained with two-dimensional (2D) images. The techniques include transforming a 3D representation (e.g., captured 3D point cloud, 3D profiles, meshes, voxels) to a 2D map, which can be input to a deep learning model pre-trained with 2D images. The 2D map includes elements disposed in an array. Each element includes a vector of a number of geometric features. Such a configuration enables the 2D map to be in a structure acceptable by the 2D deep learning model. The 2D deep learning model generates an output based on the 2D map and provides the output to a subsystem for generating an inspection result. The inspection result can have a 3D result such as a surface area and/or volume.

IPC Classes  ?

38.

METHODS AND SYSTEMS FOR THREE-DIMENSIONAL (3D) INSPECTION

      
Application Number 18891849
Status Pending
Filing Date 2024-09-20
First Publication Date 2025-03-27
Owner Cognex Corporation (USA)
Inventor
  • Moreno, Daniel Alejandro
  • Zhu, Hongwei
  • Schaufuß, Martin
  • Zadeh, Ali
  • Moed, Michael C.
  • Li, Chenye

Abstract

The techniques described herein relate to methods and systems for three-dimensional (3D) inspection using deep learning model pre-trained with two-dimensional (2D) images. The techniques include transforming a 3D representation (e.g., captured 3D point cloud, 3D profiles, meshes, voxels) to a 2D map, which can be input to a deep learning model pre-trained with 2D images. The 2D map includes elements disposed in an array. Each element includes a vector of a number of geometric features. Such a configuration enables the 2D map to be in a structure acceptable by the 2D deep learning model. The 2D deep learning model generates an output based on the 2D map and provides the output to a subsystem for generating an inspection result. The inspection result can have a 3D result such as a surface area and/or volume.

IPC Classes  ?

  • G06T 17/20 - Wire-frame description, e.g. polygonalisation or tessellation
  • G06T 7/00 - Image analysis
  • G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
  • G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects

39.

TECHNIQUES FOR ROBUST MACHINE VISION SYSTEMS

      
Document Number 03304444
Status Pending
Filing Date 2024-09-10
Open to Public Date 2025-03-20
Owner COGNEX CORPORATION (USA)
Inventor
  • Ruhnau, Thomas
  • Moore, Eric

IPC Classes  ?

  • G01B 9/02004 - Interferometers characterised by controlling or generating intrinsic radiation properties using two or more frequencies using frequency scans
  • G01B 11/24 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
  • G01S 7/4915 - Time delay measurement, e.g. operational details for pixel componentsPhase measurement
  • G01S 17/34 - Systems determining position data of a target for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated using transmission of continuous, frequency-modulated waves while heterodyning the received signal, or a signal derived therefrom, with a locally-generated signal related to the contemporaneously transmitted signal
  • G01S 17/894 - 3D imaging with simultaneous measurement of time-of-flight at a 2D array of receiver pixels, e.g. time-of-flight cameras or flash lidar

40.

TECHNIQUES FOR ROBUST MACHINE VISION SYSTEMS

      
Application Number 18830442
Status Pending
Filing Date 2024-09-10
First Publication Date 2025-03-20
Owner Cognex Corporation (USA)
Inventor
  • Ruhnau, Thomas
  • Moore, Eric

Abstract

Compact and robust machine vision systems are provided herein. A machine vision system includes an optoelectronic system configured to emit measurement beams towards objects and a motion module configured to move the objects and/or components of the optoelectronic system. The machine vision system uses the relative motions to reduce degrees of freedom required to sample the objects to produce 3D images. The optoelectronic system includes a light source configured to emit a beam and sweep its frequency. The optoelectronic system includes primary interferometers configured to measure distances to points of an object and auxiliary interferometers configured with reference delays. The optoelectronic system includes electronic circuitry configured to interpret outputs of the interferometers into distance measurements by simpler computations in the time domain. The electronic circuitry is configured to measure frequency integrals of the interferometers and determine the distance measurements by comparing the measured frequency integrals.

IPC Classes  ?

  • G01S 17/894 - 3D imaging with simultaneous measurement of time-of-flight at a 2D array of receiver pixels, e.g. time-of-flight cameras or flash lidar
  • G01B 9/02 - Interferometers
  • G01B 9/02015 - Interferometers characterised by the beam path configuration
  • G01S 7/481 - Constructional features, e.g. arrangements of optical elements

41.

TECHNIQUES FOR ROBUST MACHINE VISION SYSTEMS

      
Application Number US2024046046
Publication Number 2025/059077
Status In Force
Filing Date 2024-09-10
Publication Date 2025-03-20
Owner COGNEX CORPORATION (USA)
Inventor
  • Ruhnau, Thomas
  • Moore, Eric

Abstract

Compact and robust machine vision systems are provided herein. A machine vision system includes an optoelectronic system configured to emit measurement beams towards objects and a motion module configured to move the objects and/or components of the optoelectronic system. The machine vision system uses the relative motions to reduce degrees of freedom required to sample the objects to produce 3D images. The optoelectronic system includes a light source configured to emit a beam and sweep its frequency. The optoelectronic system includes primary interferometers configured to measure distances to points of an object and auxiliary interferometers configured with reference delays. The optoelectronic system includes electronic circuitry configured to interpret outputs of the interferometers into distance measurements by simpler computations in the time domain. The electronic circuitry is configured to measure frequency integrals of the interferometers and determine the distance measurements by comparing the measured frequency integrals.

IPC Classes  ?

  • G01B 9/02004 - Interferometers characterised by controlling or generating intrinsic radiation properties using two or more frequencies using frequency scans
  • G01B 11/24 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
  • G01S 17/894 - 3D imaging with simultaneous measurement of time-of-flight at a 2D array of receiver pixels, e.g. time-of-flight cameras or flash lidar
  • G01S 7/4915 - Time delay measurement, e.g. operational details for pixel componentsPhase measurement
  • G01S 17/34 - Systems determining position data of a target for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated using transmission of continuous, frequency-modulated waves while heterodyning the received signal, or a signal derived therefrom, with a locally-generated signal related to the contemporaneously transmitted signal

42.

SYSTEM AND METHOD FOR USE OF POLARIZED LIGHT TO IMAGE TRANSPARENT MATERIALS APPLIED TO OBJECTS

      
Application Number 18843191
Status Pending
Filing Date 2023-03-02
First Publication Date 2025-02-27
Owner Cognex Corporation (USA)
Inventor
  • Carey, Ben R.
  • Norkett, Ryan D.
  • Molnar, Gergely G.

Abstract

This invention provides a system and method inspecting transparent or translucent features on a substrate of an object. A vision system camera, having an image sensor that provides image data to a vision system processor, receives light from a field of view that includes the object through a light-polarizing filter assembly. An illumination source projects polarized light onto the substrate within the field of view. A vision system process locates and registers the substrate, and locates thereon, based upon registration, the transparent or translucent features. A vision system process then performs inspection on the features using predetermined thresholds. The substrate can be a shipping box on a conveyor, having flaps sealed at a seam by transparent tape. Alternatively, a plurality of illuminators or cameras can project and receive polarized light oriented in a plurality of polarization angles, which generates a plurality of images that are combined into a result image.

IPC Classes  ?

  • G01N 21/21 - Polarisation-affecting properties
  • G01N 21/84 - Systems specially adapted for particular applications
  • G01N 21/88 - Investigating the presence of flaws, defects or contamination
  • G01N 21/958 - Inspecting transparent materials

43.

Illumination assembly for an imaging system

      
Application Number 29876724
Grant Number D1060478
Status In Force
Filing Date 2023-05-26
First Publication Date 2025-02-04
Grant Date 2025-02-04
Owner Cognex Corporation (USA)
Inventor
  • Fernández Dorado, José
  • Garcia Campos, Pablo
  • Visser, Martijn
  • Weber, Andreas
  • Nunnink, Laurens

44.

SYSTEMS AND METHODS FOR TRANSLATIONAL TRIGGERING FOR IMAGE-BASED INSPECTION OF OBJECTS

      
Application Number US2024039145
Publication Number 2025/024441
Status In Force
Filing Date 2024-07-23
Publication Date 2025-01-30
Owner COGNEX CORPORATION (USA)
Inventor
  • Moore, Eric
  • Mock, Sebastian

Abstract

Systems and associated methods and/or utilize a 3D area-scan camera having a FOV and positioned to include a portion of a transport device within the FOV, and configured to capture images in accordance with as known interval; and at least one processor in communication with the 3D area-scan camera, and configured to: receive the images, extract image data associated with the object from the images, and analyze the image data and provide an inspection result corresponding to the object.

IPC Classes  ?

  • G01B 11/04 - Measuring arrangements characterised by the use of optical techniques for measuring length, width, or thickness specially adapted for measuring length or width of objects while moving
  • G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object

45.

SYSTEMS AND METHODS FOR TRANSLATIONAL TRIGGERING FOR IMAGE-BASED INSPECTION OF OBJECTS

      
Application Number 18781336
Status Pending
Filing Date 2024-07-23
First Publication Date 2025-01-23
Owner COGNEX CORPORATION (USA)
Inventor
  • Moore, Eric
  • Mock, Sebastian

Abstract

Systems and associated methods and/or utilize a 3D area-scan camera having a FOV and positioned to include a portion of a transport device within the FOV, and configured to capture images in accordance with a known interval; and at least one processor in communication with the 3D area-scan camera, and configured to: receive the images, extract image data associated with the object from the images, and analyze the image data and provide an inspection result corresponding to the object.

IPC Classes  ?

  • G01N 21/88 - Investigating the presence of flaws, defects or contamination
  • G01N 21/84 - Systems specially adapted for particular applications

46.

System and method for auto-focusing a vision system camera on barcodes

      
Application Number 18412900
Grant Number 12367361
Status In Force
Filing Date 2024-01-15
First Publication Date 2024-12-12
Grant Date 2025-07-22
Owner Cognex Corporation (USA)
Inventor
  • Bachelder, Ivan A.
  • Gao, Chen
  • Guerrero, Francisco Azcona
  • Dorado, Jose Fernandez
  • Lozano, Esther Oteo
  • Weber, Andreas

Abstract

This invention provides a system and method for detecting and acquiring one or more in-focus images of one or more barcodes within the field of view of an imaging device. A measurement process measures depth-of-field of barcode detection. A plurality of nominal coarse focus settings of a variable lens allow sampling, in steps, of a lens adjustment range corresponding to allowable distances between the one or more barcodes and the image sensor, so that a step size of the sampling is less than a fraction of the depth-of-field of barcode detection. An acquisition process acquires a nominal coarse focus image for each nominal coarse focus setting. A barcode detection process detects one or more barcode-like regions and respective likelihoods. A fine focus process fine-adjusts, for each high-likelihood barcode, the variable lens near a location of the barcode-like regions. The process acquires an image for decoding using the fine adjusted setting.

IPC Classes  ?

  • G06K 7/14 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
  • G06K 7/10 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation
  • H04N 23/959 - Computational photography systems, e.g. light-field imaging systems for extended depth of field imaging by adjusting depth of field during image capture, e.g. maximising or setting range based on scene characteristics
  • H04N 23/67 - Focus control based on electronic image sensor signals

47.

SYSTEM AND METHOD FOR ESTIMATING BOX SHAPE REPRESENTATION OF A GENERALLY CUBOIDAL OBJECT

      
Application Number 18732059
Status Pending
Filing Date 2024-06-03
First Publication Date 2024-12-05
Owner COGNEX CORPORATION (USA)
Inventor
  • Zhu, Hongwei
  • Moreno, Daniel
  • Zadeh, Ali M.
  • Schaufuss, Martin

Abstract

A system and method for estimating a 3D box model of a generally cuboidal 3D object imaged by 3D vision system, which provides a 3D image having a set of 3D points representing surfaces of the cuboidal 3D object to a processor is provided. An input process provides an approximate box as a region of interest (ROI), to the processor, the ROI defining a search volume within the 3D image. An identification process identifies the 3D points that are within the search volume. A coarse estimation process estimates 3D box dimensions that approximate a box shape of the cuboidal object based upon the identified 3D points. A refinement process refines the coarse box shape by processing the 3D points based on the 3D box dimensions that correspond to each of a plurality of imaged faces of the cuboidal object to derive an estimated result for the cuboidal object.

IPC Classes  ?

48.

SYSTEM AND METHOD FOR ESTIMATING BOX SHAPE REPRESENTATION OF A GENERALLY CUBOIDAL OBJECT

      
Application Number US2024032264
Publication Number 2024/250007
Status In Force
Filing Date 2024-06-03
Publication Date 2024-12-05
Owner COGNEX CORPORATION (USA)
Inventor
  • Zhu, Hongwei
  • Moreno, Daniel
  • Zadeh, Ali, M.
  • Schaufuss, Martin

Abstract

A system and method for estimating a 3D box model of a generally cuboidal 3D object imaged by 3D vision system, which provides a 3D image having a set of 3D points representing surfaces of the cuboidal 3D object to a processor is provided. An input process provides an approximate box as a region of interest (ROI), to the processor, the ROI defining a search volume within the 3D image. An identification process identifies the 3D points that are within the search volume. A coarse estimation process estimates 3D box dimensions (310) that approximate a box shape of the cuboidal object based upon the identified 3D points. A refinement process refines the coarse box shape (311, 320, 330) by processing the 3D points based on the 3D box dimensions that correspond to each of a plurality of imaged faces of the cuboidal object to derive an estimated result for the cuboidal object (340).

IPC Classes  ?

  • G06T 7/11 - Region-based segmentation
  • G06T 7/12 - Edge-based segmentation
  • G06T 7/149 - SegmentationEdge detection involving deformable models, e.g. active contour models
  • G06T 15/08 - Volume rendering
  • G06T 7/64 - Analysis of geometric attributes of convexity or concavity

49.

OPTICAL SYSTEMS WITH ADAPTABLE VIEWING ANGLE CONTROL

      
Application Number 18791159
Status Pending
Filing Date 2024-07-31
First Publication Date 2024-11-28
Owner COGNEX CORPORATION (USA)
Inventor
  • Fernandez Dorado, José
  • Nunnink, Laurens

Abstract

Optical systems and methods are disclosed. The systems and methods can include two liquid lenses and an aperture positioned between the two liquid lenses along an optical axis of an imaging device, which axis passes through the two liquid lenses. The systems and methods can retrieve liquid lens settings and set desired focal distances to achieve a variety of outcomes. The systems and methods can operate based on geometric arrangements of flexible membranes associated with the liquid lenses. In some cases, a desired focal distance can be used to configure the settings for the liquid lenses. In some cases, the liquid lens settings are tailored for acquisition speeds associated with rapid scanning and decoding of code candidates.

IPC Classes  ?

  • G02B 3/14 - Fluid-filled or evacuated lenses of variable focal length
  • G02B 7/02 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses

50.

SYSTEMS AND METHODS FOR SORTING OBJECTS

      
Application Number US2024030609
Publication Number 2024/243333
Status In Force
Filing Date 2024-05-22
Publication Date 2024-11-28
Owner COGNEX CORPORATION (USA)
Inventor
  • Mullan, Nickolas, J.
  • Carey, Ben, R.
  • Lachappelle, Shane, M.

Abstract

To sort objects, runtime information can be received for one or more previous objects (224, 226, 228) processed by a system, including at least one object (224) with first symbol information that can indicate a first type of object. Symbol information of a first object (222) can be attempted to be obtained. In response to failing to obtain the symbol information, the first object (222) can be determined to be the first type of object, based on the runtime information. Routing of the first object (222) can be controlled within a transport system (202) based on determining that the first object is the first type of object.

IPC Classes  ?

  • B07C 5/342 - Sorting according to other particular properties according to optical properties, e.g. colour
  • B07C 5/36 - Sorting apparatus characterised by the means used for distribution

51.

ONEVISION

      
Serial Number 98873088
Status Pending
Filing Date 2024-11-26
Owner Cognex Corporation ()
NICE Classes  ?
  • 09 - Scientific and electric apparatus and instruments
  • 42 - Scientific, technological and industrial services, research and design

Goods & Services

Computers containing integrated recorded software used for machine vision; Downloadable computer software platform for machine vision; Downloadable software for machine vision; Downloadable artificial intelligence software for machine vision; Downloadable cloud computing software for machine vision Providing temporary use of non-downloadable web-based software for machine vision; Providing temporary use of non-downloadable web-based artificial intelligence software for machine vision; Providing on-line non-downloadable computer software platform for machine vision; Providing on-line non-downloadable cloud-computing software for machine vision; Software as a service (SAAS) services featuring software for machine vision

52.

RANGEMAX

      
Serial Number 98867871
Status Pending
Filing Date 2024-11-22
Owner Cognex Corporation (USA)
NICE Classes  ? 09 - Scientific and electric apparatus and instruments

Goods & Services

Image formation subsystem comprised primarily of an optical assembly made up of optical lenses used for machine vision and automatic identification applications

53.

PINPOINT

      
Serial Number 98867901
Status Pending
Filing Date 2024-11-22
Owner Cognex Corporation ()
NICE Classes  ?
  • 09 - Scientific and electric apparatus and instruments
  • 42 - Scientific, technological and industrial services, research and design

Goods & Services

Downloadable and recorded computer software for industrial machine vision, using deep learning, algorithm-based machine learning, machine vision, and imaging-based automatic inspection and analysis technologies; Downloadable and recorded computer software for industrial machine learning using deep learning, algorithm-based machine learning, and imaging-based automatic inspection and analysis technologies; Downloadable and recorded computer application software for industrial machine vision using deep learning, algorithm-based machine learning, machine vision, and imaging-based automatic inspection and analysis technologies; Downloadable and recorded computer application software for logistics inventory management, tracking, and defect detection Providing on-line non downloadable software for industrial machine vision using deep learning, algorithm-based machine learning, machine vision, and imaging-based automatic inspection and analysis technologies; Providing on-line non-downloadable software for industrial machine learning using deep learning, algorithm-based machine learning, and imaging-based automatic inspection and analysis technologies; Providing on-line non-downloadable application software for logistics inventory management, tracking, and defect detection; Providing on-line non-downloadable web-based software for machine vision; Providing on-line non-downloadable cloud-computing software for machine vision

54.

INSPECTION METHOD BASED ON EDGE FIELD AND DEEP LEARNING

      
Application Number 18786962
Status Pending
Filing Date 2024-07-29
First Publication Date 2024-11-21
Owner COGNEX CORPORATION (USA)
Inventor
  • Cho, Hunmin
  • Im, Jonggyu
  • Park, Jongkwan

Abstract

Disclosed is a defect inspection device. The defect inspection device may include a lighting system designed for transmitting a lighting pattern having different illuminances for each area on a surface of an inspection object; a photographing unit for obtaining an image data of the inspection object; one or more processors for processing the image data; and a memory for storing a deep learning-based model. In addition, the one or more processors are adapted to control, the lighting system to transmit a lighting pattern having a different illuminance for each area on a surface of an inspection object, input, an image data obtained by the photographing unit into the deep learning-based model, wherein the image data includes a rapid change of illuminance in at least a part of the object surface; and determine, a defect on a surface of the inspection object using the deep learning-based model.

IPC Classes  ?

55.

METHOD AND SYSTEM FOR ONE-DIMENSIONAL SIGNAL EXTRACTION FOR VARIOUS COMPUTER PROCESSORS

      
Application Number US2024027758
Publication Number 2024/233357
Status In Force
Filing Date 2024-05-03
Publication Date 2024-11-14
Owner COGNEX CORPORATION (USA)
Inventor
  • Silver, William, M.
  • Teng, Da

Abstract

Methods and systems for extracting a one-dimensional (ID) signal from a two-dimensional (2D) digital image along a projection line are provided herein. The methods and systems store the digital image in a memory hierarchy wherein non-blocking prefetch operations can fetch pixels from a main store to a data cache. A prefetch plan, pixel processing plan, and prefetch distance are selected responsive to the orientation of the projection line. The prefetch plan uses a first address order that is designed to be favorable for efficiently fetching pixels from the main store to the data cache for the given orientation. The pixel processing plan uses a second address order that is designed to be favorable for computing a ID signal along the projection line. The pixel processing plan is used in coordination with the prefetch plan to compute the one-dimensional signal, so that pixels are fetched from the main store to the data cache in advance of being used by the pixel operations by an amount of time that is responsive to the prefetch distance.

IPC Classes  ?

  • G06K 7/14 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
  • G06T 1/60 - Memory management
  • G06F 9/38 - Concurrent instruction execution, e.g. pipeline or look ahead
  • G06F 12/0862 - Addressing of a memory level in which the access to the desired data or data block requires associative addressing means, e.g. caches with prefetch

56.

METHOD AND SYSTEM FOR ONE-DIMENSIONAL SIGNAL EXTRACTION FOR VARIOUS COMPUTER PROCESSORS

      
Application Number 18655026
Status Pending
Filing Date 2024-05-03
First Publication Date 2024-11-07
Owner Cognex Corporation (USA)
Inventor
  • Silver, William M.
  • Teng, Da

Abstract

Methods and systems for extracting a one-dimensional (1D) signal from a two-dimensional (2D) digital image along a projection line are provided herein. The methods and systems store the digital image in a memory hierarchy wherein non-blocking prefetch operations can fetch pixels from a main store to a data cache. A prefetch plan, pixel processing plan, and prefetch distance are selected responsive to the orientation of the projection line. The prefetch plan uses a first memory address order that is designed to be favorable for efficiently fetching pixels from the main store to the data cache for the given orientation. The pixel processing plan uses a second address order that is designed to be favorable for computing a 1D signal along the projection line. The pixel processing plan is used in coordination with the prefetch plan to compute the one-dimensional signal, so that pixels are fetched from the main store to the data cache in advance of being used by the pixel operations by an amount of time that is responsive to the prefetch distance.

IPC Classes  ?

57.

SYSTEM AND METHOD FOR ILLUMINATION OF AN IMAGED SCENE USING A PROGRAMMABLE LIGHT SOURCE

      
Application Number US2024022864
Publication Number 2024/211433
Status In Force
Filing Date 2024-04-03
Publication Date 2024-10-10
Owner COGNEX CORPORATION (USA)
Inventor
  • Li, David, Y.
  • Jacobson, Lowell, D.
  • Wang, Lei

Abstract

A vision system is described that acquires images in a scene with a camera assembly 110 and analyzes features in the acquired images with a vision system processor 120. It includes an illumination panel 132, having a grid of individually addressable light sources, of at least one color of light that generates an illumination pattern. The panel defines a width and a length, in which the length is greater than the width and the grid is oriented approximately in a first plane. A beam splitter 162 allows an optical axis OA of the camera assembly or the grid direction of light propagation to extend through the beam splitter onto the scene. The light sources can comprise multicolor LEDs. A controller 130 can address the multicolor LEDs via a serial data bus. A controller can further synchronize the LED display pattern and image acquisition.

IPC Classes  ?

  • G01N 21/88 - Investigating the presence of flaws, defects or contamination
  • G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object

58.

SYSTEMS AND METHODS FOR DETECTING OBJECTS

      
Application Number US2024023313
Publication Number 2024/211740
Status In Force
Filing Date 2024-04-05
Publication Date 2024-10-10
Owner COGNEX CORPORATION (USA)
Inventor Hanhart, Philippe

Abstract

The techniques described herein relate to computerized methods and apparatuses for detecting objects in an image. The techniques described herein further relate to computerized methods and apparatuses for detecting one or more objects using a machine learning model that can be trained to predict pose of an object using a plurality of feature vectors. The feature vectors may be extracted from a feature map of an image at locations that are arranged in a circular pattern.

IPC Classes  ?

  • G06V 10/24 - Aligning, centring, orientation detection or correction of the image
  • G06V 10/40 - Extraction of image or video features
  • G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
  • G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
  • G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
  • G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
  • G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level

59.

ILLUMINATION ASSEMBLY FOR A MACHINE VISION SYSTEM

      
Application Number 18601822
Status Pending
Filing Date 2024-03-11
First Publication Date 2024-09-12
Owner COGNEX CORPORATION (USA)
Inventor
  • Fernández Dorado, José
  • Garcia Campos, Pablo
  • Visser, Martijn
  • Weber, Andreas
  • Nunnink, Laurens
  • Fioravanti, Fabio

Abstract

An illumination assembly for a machine vision system includes a housing comprising a first shelf defining a first position within the housing and a second shelf defining a second position within the housing. a circuit board disposed within the housing, a plurality of light sources disposed within the housing and configured to be coupled to the circuit board, and a plurality of illumination optics assemblies disposed within the housing and removably coupled to the housing. Each illumination optics assembly corresponds to one of the plurality of light sources. The housing is configured to support the circuit board at one of the first position or the second position within the housing based on an illumination optics assembly type of the plurality of illumination optics assemblies.

IPC Classes  ?

  • G03B 15/05 - Combinations of cameras with electronic flash apparatusElectronic flash units

60.

ILLUMINATION ASSEMBLY FOR A MACHINE VISION SYSTEM

      
Application Number US2024019445
Publication Number 2024/187195
Status In Force
Filing Date 2024-03-11
Publication Date 2024-09-12
Owner COGNEX CORPORATION (USA)
Inventor
  • Fernández Dorado, José
  • Garcia Campos, Pablo
  • Visser, Martijn
  • Weber, Andreas
  • Nunnink, Laurens
  • Fioravanti, Fabio

Abstract

An illumination assembly for a machine vision system includes a housing comprising a first shelf defining a first position within the housing and a second shelf defining a second position within the housing, a circuit board disposed within the housing, a plurality of light sources disposed within the housing and configured to be coupled to the circuit board, and a plurality of illumination optics assemblies disposed within the housing and removably coupled to the housing. Each illumination optics assembly corresponds to one of the plurality of light sources. The housing is configured to support the circuit board at one of the first position or the second position within the housing based on an illumination optics assembly type of the plurality of illumination optics assemblies.

IPC Classes  ?

  • F21K 9/62 - Optical arrangements integrated in the light source, e.g. for improving the colour rendering index or the light extraction using mixing chambers, e.g. housings with reflective walls

61.

In-Sight SnAPP

      
Application Number 1802917
Status Registered
Filing Date 2024-02-27
Registration Date 2024-02-27
Owner Cognex Corporation (USA)
NICE Classes  ?
  • 09 - Scientific and electric apparatus and instruments
  • 42 - Scientific, technological and industrial services, research and design

Goods & Services

Computers and computer peripheral devices; computer machine vision hardware, namely readers, scanners, and cameras; computer hardware for use in measuring, classification, defect detection, verification, or identifying defects in machine vision applications; scientific, research, photographic, audio visual, optical, measuring, signalling, detecting, testing, and inspecting apparatus and instruments; apparatus and instruments for recording, transmitting, reproducing or processing images or data; image capturing and developing devices; artificial intelligence apparatus for the processing of images; optical inspection apparatus for industrial use; sensor, detection, data capture and monitoring apparatus and software; image scanning apparatus; bar code decoders, terminals, scanners and readers; inspection mirrors; laser detectors and sensors; cameras containing image sensors and linear image sensors; optical character readers; portable and handheld digital electronic devices for recording, organizing, transmitting, manipulating, and reviewing text, data, image, and audio files; downloadable software applications; downloadable software used for monitoring, measurement, gauging, defect detection, classification, verification, barcode reading, and inspecting purposes; downloadable software for machine vision applications; downloadable computer software for remote monitoring and analysis; computer software for controlling data, data transmission and data evaluation; data analytics software; downloadable computer software incorporating artificial intelligence for collecting, analysing and organising data; software for machine learning intelligent gateways for real-time data analysis; software for the analysis of business data; downloadable software and scanners for qualitative and quantitative analysis; artificial intelligence software; artificial intelligence and machine learning software for machine vision devices; application programming interface (API) for software computer peripherals for displaying data, images, and video; computer software, downloadable, for collecting, transmitting, managing and analysing data in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify, analyze, inspect, and detect defects in products; computer software platforms, downloadable, and cloud computing software for providing data forwarding services and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; downloadable cloud-computing software for providing data analytics services in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; integrated computer systems comprised of hardware, software, hand-held control pad, and camera for machine vision manufacture and assembly applications, namely, locating identifying, gauging, and inspecting objects, namely, consumer products, components parts, food and beverage products, pharmaceuticals, automotive, pharmaceuticals, medical devices and products, electronics, and semiconductors; machine vision readers and scanners comprised of hardware and software used to read, measure, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; downloadable software for use with portable and handheld digital electronic devices for recording, organizing, transmitting, manipulating, and reviewing text, data, image, and audio files parts and fittings for the aforesaid goods; none of the aforementioned for use in connection with photo editing and/or sharing, video editing and/or sharing for the purposes of online networking or social sharing services, augmented reality (AR) and/or virtual reality (VR) products and services, audio editing and/or sharing, media content editing and/or sharing, online networking or social sharing services. Industrial analysis and industrial research services; quality control and authentication services; design and development of computer hardware and software; design and development of computer hardware including artificial intelligence hardware, image scanning apparatus, bar code decoders, terminals, scanners and readers, inspection mirrors and optical inspection apparatus for industrial use; design and development of computer hardware including sensor, detection, data capture and monitoring apparatus, sensors, verifiers, and cameras; computer hardware design services for industrial use; software as a service [SaaS]; platform as a service [PaaS]; software as a service [SaaS] and platform as a services [PaaS] in the field of machine vision technology, artificial intelligence, deep learning, image and inspection purposes; providing technical information and consulting in the field of data analytics, machine learning, or artificial intelligence; non-downloadable computer software for remote monitoring and analysis; non-downloadable computer software for machine vision data, data transmission and data evaluation; non-downloadable software for machine vision purposes; non-downloadable data analytics software; non-downloadable computer software incorporating artificial intelligence for collecting, analysing and organising data; non-downloadable software for machine learning; non-downloadable software for the analysis of business data; non-downloadable software for qualitative and quantitative analysis; non-downloadable software used for barcode reading and vision-based inspecting purposes; non-downloadable artificial intelligence software; non-downloadable artificial intelligence and machine learning software for machine vision devices; non-downloadable computer software for collecting, transmitting, managing, and analysing data in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify, analyze, inspect, and detect defects in products in assorted manufacturing, industrial, logistical, engineering and factory applications; non-downloadable computer software for collecting, transmitting, managing and analysing data in the nature of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; non-downloadable cloud computer software for collecting, transmitting, managing, and analysing data in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure identify, analyze, inspect, and detect defects in products in assorted manufacturing, industrial, logistical, engineering and factory applications; non-downloadable cloud computing software for providing data forwarding services and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; platform as a service (PaaS) featuring computer software platforms for data forwarding and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; platform as a service (PaaS) featuring computer software platforms for providing device and data management in the nature of managing networked machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications in the internet of things (IoT); design and development of integrated computer systems comprised of hardware, software, hand-held control pad, and camera for machine vision manufacture and assembly applications, namely, locating identifying, gauging, and inspecting objects, namely, consumer products, components parts, food and beverage products, pharmaceuticals, automotive, pharmaceuticals, medical devices and products, electronics, and semiconductors; design and development of machine vision readers and scanners comprised of hardware and software used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; advisory and consulting services relating to the aforesaid; none of the aforementioned for use in connection with photo editing and/or sharing, video editing and/or sharing for the purposes of online networking or social sharing services, augmented reality (AR) and/or virtual reality (VR) products and services, audio editing and/or sharing, media content editing and/or sharing, online networking or social sharing services.

62.

SnAPP

      
Application Number 1802916
Status Registered
Filing Date 2024-02-27
Registration Date 2024-02-27
Owner Cognex Corporation (USA)
NICE Classes  ?
  • 09 - Scientific and electric apparatus and instruments
  • 42 - Scientific, technological and industrial services, research and design

Goods & Services

Computers and computer peripheral devices; computer machine vision hardware, namely readers, scanners, and cameras; computer hardware for use in measuring, classification, defect detection, verification, or identifying defects in machine vision applications; scientific, research, photographic, audio visual, optical, measuring, signalling, detecting, testing, and inspecting apparatus and instruments; apparatus and instruments for recording, transmitting, reproducing or processing images or data; image capturing and developing devices; artificial intelligence apparatus for the processing of images; optical inspection apparatus for industrial use; sensor, detection, data capture and monitoring apparatus and software; image scanning apparatus; bar code decoders, terminals, scanners and readers; inspection mirrors; laser detectors and sensors; cameras containing image sensors and linear image sensors; optical character readers; portable and handheld digital electronic devices for recording, organizing, transmitting, manipulating, and reviewing text, data, image, and audio files; downloadable software applications; downloadable software used for monitoring, measurement, gauging, defect detection, classification, verification, barcode reading, and inspecting purposes; downloadable software for machine vision applications; downloadable computer software for remote monitoring and analysis; computer software for controlling data, data transmission and data evaluation; data analytics software; downloadable computer software incorporating artificial intelligence for collecting, analysing and organising data; software for machine learning intelligent gateways for real-time data analysis; software for the analysis of business data; downloadable software and scanners for qualitative and quantitative analysis; artificial intelligence software; artificial intelligence and machine learning software for machine vision devices; application programming interface (API) for software computer peripherals for displaying data, images, and video; computer software, downloadable, for collecting, transmitting, managing and analysing data in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify, analyze, inspect, and detect defects in products; computer software platforms, downloadable, and cloud computing software for providing data forwarding services and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; downloadable cloud-computing software for providing data analytics services in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; integrated computer systems comprised of hardware, software, hand-held control pad, and camera for machine vision manufacture and assembly applications, namely, locating identifying, gauging, and inspecting objects, namely, consumer products, components parts, food and beverage products, pharmaceuticals, automotive, pharmaceuticals, medical devices and products, electronics, and semiconductors; machine vision readers and scanners comprised of hardware and software used to read, measure, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; downloadable software for use with portable and handheld digital electronic devices for recording, organizing, transmitting, manipulating, and reviewing text, data, image, and audio files parts and fittings for the aforesaid goods; none of the aforementioned for use in connection with photo editing and/or sharing, video editing and/or sharing for the purposes of online networking or social sharing services, augmented reality (AR) and/or virtual reality (VR) products and services, audio editing and/or sharing, media content editing and/or sharing, online networking or social sharing services. Industrial analysis and industrial research services; quality control and authentication services; design and development of computer hardware and software; design and development of computer hardware including artificial intelligence hardware, image scanning apparatus, bar code decoders, terminals, scanners and readers, inspection mirrors and optical inspection apparatus for industrial use; design and development of computer hardware including sensor, detection, data capture and monitoring apparatus, sensors, verifiers, and cameras; computer hardware design services for industrial use; software as a service [SaaS]; platform as a service [PaaS]; software as a service [SaaS] and platform as a services [PaaS] in the field of machine vision technology, artificial intelligence, deep learning, image and inspection purposes; providing technical information and consulting in the field of data analytics, machine learning, or artificial intelligence; non-downloadable computer software for remote monitoring and analysis; non-downloadable computer software for machine vision data, data transmission and data evaluation; non-downloadable software for machine vision purposes; non-downloadable data analytics software; non-downloadable computer software incorporating artificial intelligence for collecting, analysing and organising data; non-downloadable software for machine learning; non-downloadable software for the analysis of business data; non-downloadable software for qualitative and quantitative analysis; non-downloadable software used for barcode reading and vision-based inspecting purposes; non-downloadable artificial intelligence software; non-downloadable artificial intelligence and machine learning software for machine vision devices; non-downloadable computer software for collecting, transmitting, managing, and analysing data in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify, analyze, inspect, and detect defects in products in assorted manufacturing, industrial, logistical, engineering and factory applications; non-downloadable computer software for collecting, transmitting, managing and analysing data in the nature of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; non-downloadable cloud computer software for collecting, transmitting, managing, and analysing data in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure identify, analyze, inspect, and detect defects in products in assorted manufacturing, industrial, logistical, engineering and factory applications; non-downloadable cloud computing software for providing data forwarding services and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; platform as a service (PaaS) featuring computer software platforms for data forwarding and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; platform as a service (PaaS) featuring computer software platforms for providing device and data management in the nature of managing networked machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications in the internet of things (IoT); design and development of integrated computer systems comprised of hardware, software, hand-held control pad, and camera for machine vision manufacture and assembly applications, namely, locating identifying, gauging, and inspecting objects, namely, consumer products, components parts, food and beverage products, pharmaceuticals, automotive, pharmaceuticals, medical devices and products, electronics, and semiconductors; design and development of machine vision readers and scanners comprised of hardware and software used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; advisory and consulting services relating to the aforesaid; none of the aforementioned for use in connection with photo editing and/or sharing, video editing and/or sharing for the purposes of online networking or social sharing services, augmented reality (AR) and/or virtual reality (VR) products and services, audio editing and/or sharing, media content editing and/or sharing, online networking or social sharing services.

63.

HIGH PERFORMANCE MACHINE VISION SYSTEM

      
Application Number US2024013158
Publication Number 2024/159126
Status In Force
Filing Date 2024-01-26
Publication Date 2024-08-02
Owner COGNEX CORPORATION (USA)
Inventor
  • Wurz, Caitlin
  • Surana, Deepak
  • Molnar, Gyula Mate
  • Thanigai Arasu, Divya
  • Corbett, Michael
  • Tutuianu, Nicolas
  • Savvides, Andreas

Abstract

The techniques described herein provide high performance machine vision systems. A high performance machine vision system includes a live dashboard, a performance dashboard, and a result browser. The live dashboard provides, for viewing, a live stream of images and associated machine vision data. The live dashboard enables real-time analysis of the machine vision system, such as to determine whether the system including, for example, tunnels, is being triggered properly, and whether packages are moving through the system correctly. The performance dashboard provides, for viewing, graphical analyses of various data associated with the machine vision system. The performance dashboard enables real-time analysis of the machine vision system, such as to determine whether the system is functioning properly, etc. The result browser provides presentations by various metrics such as individual triggers. The result browser enables customized analyses of the machine vision system, which may expose hidden problems in the system.

IPC Classes  ?

  • G06K 7/00 - Methods or arrangements for sensing record carriers

64.

OPTICAL SYSTEMS WITH ADAPTABLE VIEWING ANGLE CONTROL

      
Application Number US2024013189
Publication Number 2024/159145
Status In Force
Filing Date 2024-01-26
Publication Date 2024-08-02
Owner COGNEX CORPORATION (USA)
Inventor
  • Fernandez Dorado, Jose
  • Nunnink, Laurens

Abstract

Optical systems and methods are disclosed. The systems and methods can include two liquid lenses and an aperture positioned between the two liquid lenses along an optical axis of an imaging device, which axis passes through the two liquid lenses. The systems and methods can retrieve liquid lens settings and set desired focal distances to achieve a variety of outcomes. The systems and methods can operate based on geometric arrangements of flexible membranes associated with the liquid lenses. In some cases, a desired focal distance can be used to configure the settings for the liquid lenses. In some cases, the liquid lens settings are tailored for acquisition speeds associated with rapid scanning and decoding of code candidates.

IPC Classes  ?

  • G02B 3/12 - Fluid-filled or evacuated lenses
  • G02B 3/14 - Fluid-filled or evacuated lenses of variable focal length
  • G02B 13/00 - Optical objectives specially designed for the purposes specified below

65.

OPTICAL SYSTEMS WITH IMPROVED ADAPTABLE VIEWING ANGLE CONTROL

      
Application Number 18424316
Status Pending
Filing Date 2024-01-26
First Publication Date 2024-08-01
Owner COGNEX CORPORATION (USA)
Inventor
  • Fernandez Dorado, José
  • Nunnink, Laurens

Abstract

Optical systems and methods are disclosed. The systems and methods can include two liquid lenses and an aperture positioned between the two liquid lenses along an optical axis of an imaging device, which axis passes through the two liquid lenses. The systems and methods can retrieve liquid lens settings and set desired focal distances to achieve a variety of outcomes. The systems and methods can operate based on geometric arrangements of flexible membranes associated with the liquid lenses. In some cases, a desired focal distance can be used to configure the settings for the liquid lenses. In some cases, the liquid lens settings are tailored for acquisition speeds associated with rapid scanning and decoding of code candidates.

IPC Classes  ?

  • G02B 7/10 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses with mechanism for focusing or varying magnification by relative axial movement of several lenses, e.g. of varifocal objective lens
  • G02B 3/14 - Fluid-filled or evacuated lenses of variable focal length

66.

Lens Assembly and Thermal Correction for Machine Vision System

      
Application Number 18417651
Status Pending
Filing Date 2024-01-19
First Publication Date 2024-07-25
Owner Cognex Corporation (USA)
Inventor
  • Oteo Lozano, Esther
  • Kempf, Iii, Torsten
  • Dippel, Nicole
  • Azcona Guerrero, Francisco
  • Weber, Andreas
  • Nunnink, Laurens

Abstract

A modular lens assembly for a machine vision system includes a lens housing, a liquid lens disposed within the lens housing, a solid lens element disposed within the lens housing, and a lens processor device disposed within the lens housing and coupled to the liquid lens. The lens processor device may be configured to determine a control signal to control the liquid lens.

IPC Classes  ?

  • G02B 7/28 - Systems for automatic generation of focusing signals
  • G02B 3/14 - Fluid-filled or evacuated lenses of variable focal length
  • G02B 7/02 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses

67.

LENS ASSEMBLY AND THERMAL CORRECTION FOR MACHINE VISION SYSTEM

      
Application Number US2024012190
Publication Number 2024/155908
Status In Force
Filing Date 2024-01-19
Publication Date 2024-07-25
Owner COGNEX CORPORATION (USA)
Inventor
  • Oteo Lozano, Esther
  • Kempf, Torsten
  • Dippel, Nicole
  • Azcona Guerrero, Francisco
  • Weber, Andreas
  • Nunnink, Laurens

Abstract

A modular lens assembly (200) for a machine vision system includes a lens housing (210), a liquid lens (220) disposed within the lens housing (210), a solid lens element (222) disposed within the lens housing (210), and a lens processor device (224) disposed within the lens housing (210) and coupled to the liquid lens (220). The lens processor device (224) may be configured to determine a control signal to control the liquid lens (220).

IPC Classes  ?

  • G02B 3/14 - Fluid-filled or evacuated lenses of variable focal length

68.

System and method for efficiently scoring probes in an image with a vision system

      
Application Number 18208660
Grant Number 12548191
Status In Force
Filing Date 2023-06-12
First Publication Date 2024-07-11
Grant Date 2026-02-10
Owner Cognex Corporation (USA)
Inventor Bogan, Nathaniel R.

Abstract

A system and method for scoring trained probes for use in analyzing one or more candidate poses of a runtime image is provided. A set of probes with location and gradient direction based on a trained model are applied to one or more candidate poses based upon a runtime image. The applied probes each respectively include a discrete set of position offsets with respect to the gradient direction thereof. A match score is computed for each of the probes, which includes estimating a best match position for each of the probes respectively relative to one of the offsets thereof, and generating a set of individual probe scores for each of the probes, respectively at the estimated best match position.

IPC Classes  ?

  • G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
  • G06F 18/28 - Determining representative reference patterns, e.g. by averaging or distortingGenerating dictionaries
  • G06T 7/00 - Image analysis
  • G06T 7/33 - Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
  • G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
  • G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]Salient regional features
  • G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
  • G06V 10/772 - Determining representative reference patterns, e.g. averaging or distorting patternsGenerating dictionaries

69.

Illumination line generation by double-duty diffusion

      
Application Number 18497851
Grant Number 12529828
Status In Force
Filing Date 2023-10-30
First Publication Date 2024-06-06
Grant Date 2026-01-20
Owner Cognex Corporation (USA)
Inventor
  • Ruhnau, Thomas
  • Aljasem, Khaled
  • Oteo Lozano, Esther
  • Filhaber, John F.

Abstract

An optical system includes a light source operable to produce input light, a linear diffuser, and a reflector. The light source, linear diffuser, and reflector are arranged and configured to direct the input light from the light source to the linear diffuser, project diffused light from the linear diffuser to the reflector, reflect the diffused light from the reflector to the linear diffuser as reflected light, and modify the reflected light at the linear diffuser to output a planar fan of diffused light, so that an illumination line forms at an intersection of the planar fan and an object. A system includes an optical sub-system configured to generate a planar fan of diffused light by passing input light through a single linear diffuser twice, and a control sub-system configured to operate the optical sub-system to control use of the planar fan of diffused light.

IPC Classes  ?

  • G02B 5/02 - Diffusing elementsAfocal elements
  • G01N 15/075 - Investigating concentration of particle suspensions by optical means
  • G01N 21/31 - Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
  • G01N 21/64 - FluorescencePhosphorescence
  • G01N 21/95 - Investigating the presence of flaws, defects or contamination characterised by the material or shape of the object to be examined
  • G01N 33/00 - Investigating or analysing materials by specific methods not covered by groups
  • G02B 17/06 - Catoptric systems, e.g. image erecting and reversing system using mirrors only

70.

Systems and methods for stitching sequential images of an object

      
Application Number 18342956
Grant Number 12361617
Status In Force
Filing Date 2023-06-28
First Publication Date 2024-05-30
Grant Date 2025-07-15
Owner Cognex Corporation (USA)
Inventor
  • Negro, James A.
  • Ye, Xiangyun
  • El-Barkouky, Ahmed

Abstract

A system may comprise a transport device for moving at least one object, wherein at least one substantially planar surface of the object is moved in a known plane locally around a viewing area, wherein the substantially planar surface of the object is occluded except when the at least one substantially planar surface passes by the viewing area, at least one 2D digital optical sensor configured to capture at least two sequential 2D digital images of the at least one substantially planar surface of the at least one object that is moved in the known plane around the viewing area, and a controller operatively coupled to the 2D digital optical sensor, the controller performing the steps of: a) receiving a first digital image, b) receiving a second digital image, and c) stitching the first digital image and the second digital image using a stitching algorithm to generate a stitched image.

IPC Classes  ?

  • G06T 11/60 - Editing figures and textCombining figures or text
  • G06K 19/06 - Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
  • G06T 3/18 - Image warping, e.g. rearranging pixels individually
  • G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
  • G06V 20/40 - ScenesScene-specific elements in video content
  • H04N 23/698 - Control of cameras or camera modules for achieving an enlarged field of view, e.g. panoramic image capture
  • H04N 23/74 - Circuitry for compensating brightness variation in the scene by influencing the scene brightness using illuminating means

71.

System and method for three-dimensional scan of moving objects longer than the field of view

      
Application Number 18242192
Grant Number 12340435
Status In Force
Filing Date 2023-09-05
First Publication Date 2024-05-30
Grant Date 2025-06-24
Owner Cognex Corporation (USA)
Inventor
  • Carey, Ben R.
  • Parrett, Andrew
  • Liu, Yukang
  • Chiang, Gilbert

Abstract

This invention provides a system and method for using an area scan sensor of a vision system, in conjunction with an encoder or other knowledge of motion, to capture an accurate measurement of an object larger than a single field of view (FOV) of the sensor. It identifies features/edges of the object, which are tracked from image to image, thereby providing a lightweight way to process the overall extents of the object for dimensioning purposes. Logic automatically determines if the object is longer than the FOV, and thereby causes a sequence of image acquisition snapshots to occur while the moving/conveyed object remains within the FOV until the object is no longer present in the FOV. At that point, acquisition ceases and the individual images are combined as segments in an overall image. These images can be processed to derive overall dimensions of the object based on input application details.

IPC Classes  ?

  • G06T 7/292 - Multi-camera tracking
  • G06T 1/00 - General purpose image data processing
  • G06T 7/00 - Image analysis
  • G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
  • G06T 7/80 - Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
  • G06V 20/64 - Three-dimensional objects

72.

ILLUMINATION LINE GENERATION BY DOUBLE-DUTY DIFFUSION

      
Application Number US2023036258
Publication Number 2024/097120
Status In Force
Filing Date 2023-10-30
Publication Date 2024-05-10
Owner COGNEX CORPORATION (USA)
Inventor
  • Ruhnau, Thomas
  • Aljasem, Khaled
  • Oteo Lozano, Esther
  • Filhaber, John F.

Abstract

An optical system includes a light source operable to produce input light, a linear diffuser, and a reflector. The light source, linear diffuser, and reflector are arranged and configured to direct the input light from the light source to the linear diffuser, project diffused light from the linear diffuser to the reflector, reflect the diffused light from the reflector to the linear diffuser as reflected light, and modify the reflected light at the linear diffuser to output a planar fan of diffused light, so that an illumination line forms at an intersection of the planar fan and an object. A system includes an optical sub-system configured to generate a planar fan of diffused light by passing input light through a single linear diffuser twice, and a control sub-system configured to operate the optical sub-system to control use of the planar fan of diffused light.

IPC Classes  ?

  • G02B 5/02 - Diffusing elementsAfocal elements
  • G02B 27/09 - Beam shaping, e.g. changing the cross-sectioned area, not otherwise provided for

73.

SYSTEMS AND METHODS FOR DEFLECTOMETRY

      
Application Number US2023075730
Publication Number 2024/076922
Status In Force
Filing Date 2023-10-02
Publication Date 2024-04-11
Owner COGNEX CORPORATION (USA)
Inventor
  • Jacobson, Lowell D.
  • Wang, Lei

Abstract

Systems and methods for deflectometry are disclosed. The deflectometry display is divided into subregions, with the subregions collectively covering the entire display. Deflectometry data sets are acquired for each of the subregions and all of the data is processed to compute fused deflectometry images having enhanced quality. By using display subregions, smaller portions of the object of interest are illuminated, so the amount of diffuse reflection is correspondingly reduced. By focusing on smaller regions of deflectometry patterns, the ratio of specular-to-diffuse reflection intensity can be increased. This allows display brightness and camera acquisition time to be increased without saturation and improves signal-to-noise ratio quality of the specular signal, which improves the quality of the subsequently computed deflectometry images.

IPC Classes  ?

  • G01N 21/88 - Investigating the presence of flaws, defects or contamination
  • G06T 7/00 - Image analysis
  • G01B 11/30 - Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces

74.

SYSTEMS AND METHODS FOR CONFIGURING MACHINE VISION TUNNELS

      
Application Number US2023074949
Publication Number 2024/064924
Status In Force
Filing Date 2023-09-22
Publication Date 2024-03-28
Owner COGNEX CORPORATION (USA)
Inventor
  • Sanz Rodriguez, Saul
  • Ruetten, Jens
  • Depre, Tony
  • Stroo, Bart

Abstract

Systems and methods are provided for generating machine vision tunnel configurations. The systems and methods described herein may automatically generate a configuration summary of tunnel configurations for a prospective machine vision tunnel based on received parameters. The configuration summary may be modified via operator interaction with the configuration summary. The systems and methods described herein may also automatically generate and transmit a bill of materials report, a tunnel commissioning report, or a graphical representation of an approved tunnel configuration, including generating some or all of these data sets dynamically in response to operator inputs.

IPC Classes  ?

75.

SYSTEM AND METHOD FOR FINDING AND CLASSIFYING LINES IN AN IMAGE WITH A VISION SYSTEM

      
Application Number 18220182
Status Pending
Filing Date 2023-07-10
First Publication Date 2024-03-07
Owner Cognex Corporation (USA)
Inventor
  • Wang, Lei
  • Anand, Vivek
  • Jacobson, Lowell D.

Abstract

This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.

IPC Classes  ?

  • G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
  • G06F 18/214 - Generating training patternsBootstrap methods, e.g. bagging or boosting
  • G06F 18/2415 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
  • G06F 18/40 - Software arrangements specially adapted for pattern recognition, e.g. user interfaces or toolboxes therefor
  • G06T 7/13 - Edge detection
  • G06T 7/143 - SegmentationEdge detection involving probabilistic approaches, e.g. Markov random field [MRF] modelling
  • G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
  • G06V 10/50 - Extraction of image or video features by performing operations within image blocksExtraction of image or video features by using histograms, e.g. histogram of oriented gradients [HoG]Extraction of image or video features by summing image-intensity valuesProjection analysis

76.

SnAPP

      
Application Number 234257400
Status Pending
Filing Date 2024-02-27
Owner Cognex Corporation (USA)
NICE Classes  ?
  • 09 - Scientific and electric apparatus and instruments
  • 42 - Scientific, technological and industrial services, research and design

Goods & Services

(1) Computers and computer peripheral devices; computer machine vision hardware, namely readers, scanners, and cameras; computer hardware for use in measuring, classification, defect detection, verification, or identifying defects in machine vision applications; scientific, research, photographic, audio visual, optical, measuring, signalling, detecting, testing, and inspecting apparatus and instruments; apparatus and instruments for recording, transmitting, reproducing or processing images or data; image capturing and developing devices; artificial intelligence apparatus for the processing of images; optical inspection apparatus for industrial use; sensor, detection, data capture and monitoring apparatus and software; image scanning apparatus; bar code decoders, terminals, scanners and readers; inspection mirrors; laser detectors and sensors; cameras containing image sensors and linear image sensors; optical character readers; portable and handheld digital electronic devices for recording, organizing, transmitting, manipulating, and reviewing text, data, image, and audio files; downloadable software applications; downloadable software used for monitoring, measurement, gauging, defect detection, classification, verification, barcode reading, and inspecting purposes; downloadable software for machine vision applications; downloadable computer software for remote monitoring and analysis; computer software for controlling data, data transmission and data evaluation; data analytics software; downloadable computer software incorporating artificial intelligence for collecting, analysing and organising data; software for machine learning intelligent gateways for real-time data analysis; software for the analysis of business data; downloadable software and scanners for qualitative and quantitative analysis; artificial intelligence software; artificial intelligence and machine learning software for machine vision devices; application programming interface (API) for software computer peripherals for displaying data, images, and video; computer software, downloadable, for collecting, transmitting, managing and analysing data in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify, analyze, inspect, and detect defects in products; computer software platforms, downloadable, and cloud computing software for providing data forwarding services and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; downloadable cloud-computing software for providing data analytics services in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; integrated computer systems comprised of hardware, software, hand-held control pad, and camera for machine vision manufacture and assembly applications, namely, locating identifying, gauging, and inspecting objects, namely, consumer products, components parts, food and beverage products, pharmaceuticals, automotive, pharmaceuticals, medical devices and products, electronics, and semiconductors; machine vision readers and scanners comprised of hardware and software used to read, measure, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; downloadable software for use with portable and handheld digital electronic devices for recording, organizing, transmitting, manipulating, and reviewing text, data, image, and audio files parts and fittings for the aforesaid goods; none of the aforementioned for use in connection with photo editing and/or sharing, video editing and/or sharing for the purposes of online networking or social sharing services, augmented reality (AR) and/or virtual reality (VR) products and services, audio editing and/or sharing, media content editing and/or sharing, online networking or social sharing services. (1) Industrial analysis and industrial research services; quality control and authentication services; design and development of computer hardware and software; design and development of computer hardware including artificial intelligence hardware, image scanning apparatus, bar code decoders, terminals, scanners and readers, inspection mirrors and optical inspection apparatus for industrial use; design and development of computer hardware including sensor, detection, data capture and monitoring apparatus, sensors, verifiers, and cameras; computer hardware design services for industrial use; software as a service [SaaS]; platform as a service [PaaS]; software as a service [SaaS] and platform as a services [PaaS] in the field of machine vision technology, artificial intelligence, deep learning, image and inspection purposes; providing technical information and consulting in the field of data analytics, machine learning, or artificial intelligence; non-downloadable computer software for remote monitoring and analysis; non-downloadable computer software for machine vision data, data transmission and data evaluation; non-downloadable software for machine vision purposes; non-downloadable data analytics software; non-downloadable computer software incorporating artificial intelligence for collecting, analysing and organising data; non-downloadable software for machine learning; non-downloadable software for the analysis of business data; non-downloadable software for qualitative and quantitative analysis; non-downloadable software used for barcode reading and vision-based inspecting purposes; non-downloadable artificial intelligence software; non-downloadable artificial intelligence and machine learning software for machine vision devices; non-downloadable computer software for collecting, transmitting, managing, and analysing data in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure, identify, analyze, inspect, and detect defects in products in assorted manufacturing, industrial, logistical, engineering and factory applications; non-downloadable computer software for collecting, transmitting, managing and analysing data in the nature of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; non-downloadable cloud computer software for collecting, transmitting, managing, and analysing data in the nature of processing images, graphics and text for machine vision readers and scanners used to read, measure identify, analyze, inspect, and detect defects in products in assorted manufacturing, industrial, logistical, engineering and factory applications; non-downloadable cloud computing software for providing data forwarding services and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; platform as a service (PaaS) featuring computer software platforms for data forwarding and data analytics services in the nature of transmission of data for machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications; platform as a service (PaaS) featuring computer software platforms for providing device and data management in the nature of managing networked machine vision readers and scanners used to read, measure, identify and analyze various types of codes and image information in assorted manufacturing, industrial, logistical, engineering and factory applications in the internet of things (IoT); design and development of integrated computer systems comprised of hardware, software, hand-held control pad, and camera for machine vision manufacture and assembly applications, namely, locating identifying, gauging, and inspecting objects, namely, consumer products, components parts, food and beverage products, pharmaceuticals, automotive, pharmaceuticals, medical devices and products, electronics, and semiconductors; design and development of machine vision readers and scanners comprised of hardware and software used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; advisory and consulting services relating to the aforesaid; none of the aforementioned for use in connection with photo editing and/or sharing, video editing and/or sharing for the purposes of online networking or social sharing services, augmented reality (AR) and/or virtual reality (VR) products and services, audio editing and/or sharing, media content editing and/or sharing, online networking or social sharing services.

77.

METHODS AND APPARATUS FOR DETERMINING ORIENTATIONS OF AN OBJECT IN THREE-DIMENSIONAL DATA

      
Application Number 18448824
Status Pending
Filing Date 2023-08-11
First Publication Date 2024-02-15
Owner Cognex Corporation (USA)
Inventor
  • Vaidya, Nitin M.
  • Bogan, Nathaniel

Abstract

The techniques described herein relate to methods, apparatus, and computer readable media configured to determining a candidate three-dimensional (3D) orientation of an object represented by a three-dimensional (3D) point cloud. The method includes receiving data indicative of a 3D point cloud comprising a plurality of 3D points, determining a first histogram for the plurality of 3D points based on geometric features determined based on the plurality of 3D points, accessing data indicative of a second histogram of geometric features of a 3D representation of a reference object, computing, for each of a plurality of different rotations between the first histogram and the second histogram in 3D space, a scoring metric for the associated rotation, and determining the candidate 3D orientation based on the scoring metrics of the plurality of different rotations.

IPC Classes  ?

  • G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
  • G06T 7/60 - Analysis of geometric attributes

78.

METHODS AND APPARATUS FOR DETERMINING ORIENTATIONS OF AN OBJECT IN THREE-DIMENSIONAL DATA

      
Application Number US2023072102
Publication Number 2024/036320
Status In Force
Filing Date 2023-08-11
Publication Date 2024-02-15
Owner COGNEX CORPORATION (USA)
Inventor
  • Vaidya, Nitin, M.
  • Bogan, Nathaniel

Abstract

The techniques described herein relate to methods, apparatus, and computer readable media configured to determining a candidate three-dimensional (3D) orientation of an object represented by a three-dimensional (3D) point cloud. The method includes receiving data indicative of a 3D point cloud comprising a plurality of 3D points, determining a first histogram for the plurality of 3D points based on geometric features determined based, on the plurality of 3D points, accessing data indicative of a. second histogram of geometric features of a 3D representation of a reference object, computing, for each of a plurality of different rotations between the first histogram and the second histogram in 3D space, a scoring metric for the associated rotation, and determining the candidate 3D orientation based on the scoring metrics of the plurality of different rotations.

IPC Classes  ?

  • G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods

79.

Imaging device with housing

      
Application Number 29773796
Grant Number D1012155
Status In Force
Filing Date 2021-03-11
First Publication Date 2024-01-23
Grant Date 2024-01-23
Owner Cognex Corporation (USA)
Inventor
  • Orban, Laszlo
  • Campos, Pablo Garcia
  • Könnecke, Christoph
  • Schnabler, Roman
  • Mayer, Lars

80.

Lighting assembly for imaging

      
Application Number 29829231
Grant Number D1012338
Status In Force
Filing Date 2022-03-03
First Publication Date 2024-01-23
Grant Date 2024-01-23
Owner Cognex Corporation (USA)
Inventor
  • Harman, James
  • Messenger Bouricius, Marina Emily Charlotte
  • Ciftci, Yasin Salih
  • Mehmed, Yusein

81.

System and method for finding and classifying patterns in an image with a vision system

      
Application Number 18103432
Grant Number 12147895
Status In Force
Filing Date 2023-01-30
First Publication Date 2024-01-04
Grant Date 2024-11-19
Owner Cognex Corporation (USA)
Inventor
  • Wang, Lei
  • Anand, Vivek
  • Jacobson, Lowell D.
  • Li, David Y.

Abstract

This invention provides a system and method for finding patterns in images that incorporates neural net classifiers. A pattern finding tool is coupled with a classifier that can be run before or after the tool to have labeled pattern results with sub-pixel accuracy. In the case of a pattern finding tool that can detect multiple templates, its performance is improved when a neural net classifier informs the pattern finding tool to work only on a subset of the originally trained templates. Similarly, in the case of a pattern finding tool that initially detects a pattern, a neural network classifier can then determine whether it has found the correct pattern. The neural network can also reconstruct/clean-up an imaged shape, and/or to eliminate pixels less relevant to the shape of interest, therefore reducing the search time, as well significantly increasing the chance of lock on the correct shapes.

IPC Classes  ?

  • G06N 3/08 - Learning methods
  • G06F 18/214 - Generating training patternsBootstrap methods, e.g. bagging or boosting
  • G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
  • G06V 10/50 - Extraction of image or video features by performing operations within image blocksExtraction of image or video features by using histograms, e.g. histogram of oriented gradients [HoG]Extraction of image or video features by summing image-intensity valuesProjection analysis
  • G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
  • G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

82.

EDGE INTELLIGENCE

      
Serial Number 98338135
Status Registered
Filing Date 2024-01-02
Registration Date 2025-01-14
Owner Cognex Corporation ()
NICE Classes  ? 09 - Scientific and electric apparatus and instruments

Goods & Services

Computer software platforms, downloadable, for providing device management in the nature of managing networked machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications in the internet of things (IOT); Computer software platforms, downloadable, for providing data management for machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; Computer software platforms, downloadable, for providing data forwarding in the nature of transmission of data for machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; Computer software platforms, downloadable, for providing data analytics services in the nature of, processing images, graphics and text for machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; Computer software platforms, recorded, for providing device management in the nature of managing networked machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications in the internet of things (IOT); Computer software platforms, recorded, for providing data management for machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; Computer software platforms, recorded, for providing data forwarding in the nature of transmission of data for machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; Computer software platforms, recorded, for providing data analytics services in the nature of processing images, graphics and text for machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; Downloadable cloud-computing software for providing device management in the nature of managing networked machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications in the internet of things (IOT); Downloadable cloud-computing software for providing data management for machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; Downloadable cloud-computing software for providing data forwarding in the nature of transmission of data for machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications; Downloadable cloud-computing software for providing data analytics services in the nature of processing images, graphics and text for machine vision readers and scanners used to read, identify and analyze various types of codes in assorted manufacturing, industrial, logistical, engineering and factory applications

83.

Methods and apparatus for using range data to predict object features

      
Application Number 18297916
Grant Number 12038267
Status In Force
Filing Date 2023-04-10
First Publication Date 2023-12-14
Grant Date 2024-07-16
Owner Cognex Corporation (USA)
Inventor
  • Gao, Chen
  • Bachelder, Ivan

Abstract

Embodiments relate to predicting height information for an object. First distance data is determined at a first time when an object is at a first position that is only partially within the field-of-view. Second distance data is determined at a second, later time when the object is at a second, different position that is only partially within the field-of-view. A distance measurement model that models a physical parameter of the object within the field-of-view is determined for the object based on the first and second distance data. Third distance data indicative of an estimated distance to the object prior to the object being entirely within the field-of-view of the distance sensing device is determined based on the first distance data, the second distance data, and the distance measurement model. Data indicative of a height of the object is determined based on the third distance data.

IPC Classes  ?

  • G01B 11/06 - Measuring arrangements characterised by the use of optical techniques for measuring length, width, or thickness for measuring thickness
  • G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
  • G01B 11/28 - Measuring arrangements characterised by the use of optical techniques for measuring areas

84.

Symbology reader with multi-core processor

      
Application Number 18120944
Grant Number 12149801
Status In Force
Filing Date 2023-03-13
First Publication Date 2023-12-14
Grant Date 2024-11-19
Owner Cognex Corporation (USA)
Inventor
  • Nunnink, Laurens
  • Reuter, Richard
  • Winzen, Frank
  • Joussen, Mario
  • Kesten, Joerg
  • Negro, James A.

Abstract

This invention provides a vision system camera, and associated methods of operation, having a multi-core processor, high-speed, high-resolution imager, FOVE, auto-focus lens and imager-connected pre-processor to pre-process image data provides the acquisition and processing speed, as well as the image resolution that are highly desirable in a wide range of applications. This arrangement effectively scans objects that require a wide field of view, vary in size and move relatively quickly with respect to the system field of view. This vision system provides a physical package with a wide variety of physical interconnections to support various options and control functions. The package effectively dissipates internally generated heat by arranging components to optimize heat transfer to the ambient environment and includes dissipating structure (e.g. fins) to facilitate such transfer. The system also enables a wide range of multi-core processes to optimize and load-balance both image processing and system operation (i.e. auto-regulation tasks).

IPC Classes  ?

  • H04N 23/00 - Cameras or camera modules comprising electronic image sensorsControl thereof
  • H04N 23/67 - Focus control based on electronic image sensor signals

85.

FLEXURE ARRANGEMENTS FOR OPTICAL COMPONENTS

      
Application Number 18303981
Status Pending
Filing Date 2023-04-20
First Publication Date 2023-12-14
Owner COGNEX CORPORATION (USA)
Inventor Filhaber, John

Abstract

An optical system can include a receiver secured to a first optical component and a flexure arrangement secured to a second optical component. The flexure arrangement can include a plurality of flexures, each with a free end that can extend away from the second optical component and into a corresponding cavity of the receiver. Each of the cavities can be sized to receive adhesive that secures the corresponding flexure within the cavity when the adhesive has hardened, and to permit adjustment of the corresponding flexure within the cavity, before the adhesive has hardened, to adjust an alignment of the first and second optical components relative to multiple degrees of freedom.

IPC Classes  ?

  • G02B 27/62 - Optical apparatus specially adapted for adjusting optical elements during the assembly of optical systems
  • G02B 7/00 - Mountings, adjusting means, or light-tight connections, for optical elements
  • G02B 7/02 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses
  • B29C 65/54 - Applying the adhesive between pre-assembled parts
  • B29C 65/78 - Means for handling the parts to be joined, e.g. for making containers or hollow articles

86.

Boundary estimation systems and methods

      
Application Number 18117764
Grant Number 12087013
Status In Force
Filing Date 2023-03-06
First Publication Date 2023-12-14
Grant Date 2024-09-10
Owner Cognex Corporation (USA)
Inventor
  • Gauthier, Georges
  • Romeo, Anthony
  • Link, John Jeffrey

Abstract

A system or method can analyze symbols on a set of objects having different sizes. The system can identify a characteristic object dimension corresponding to the set of objects. An image of a first object can be received, and, a first virtual object boundary feature (e.g., edge) in the image can be identified for the first object based on the characteristic object dimension. A first symbol can be identified in the image, and whether the first symbol is positioned on the first object can be determined, based on the first virtual object boundary feature.

IPC Classes  ?

  • G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
  • B07C 3/14 - Apparatus characterised by the means used for detection of the destination using light-responsive detecting means
  • G06K 7/14 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
  • G06T 7/13 - Edge detection

87.

Multiple channel locating

      
Application Number 18143820
Grant Number 12435968
Status In Force
Filing Date 2023-05-05
First Publication Date 2023-12-07
Grant Date 2025-10-07
Owner Cognex Corporation (USA)
Inventor
  • Moore, Eric
  • Braker, Benjamin
  • Feldkhun, Daniel

Abstract

Methods, systems, and apparatuses are provided for estimating a location on an object in a three-dimensional scene. Multiple radiation patterns are produced by spatially modulating each of multiple first radiations with a distinct combination of one or more modulating structures, each first radiation having at least one of a distinct radiation path, a distinct source, a distinct source spectrum, or a distinct source polarization with respect to the other first radiations. The location on the object is illuminated with a portion of each of two or more of the radiation patterns, the location producing multiple object radiations, each object radiation produced in response to one of the multiple radiation patterns. Multiple measured values are produced by detecting the object radiations from the location on the object due to each pattern separately using one or more detector elements. The location on the object is estimated based on the multiple measured values.

IPC Classes  ?

  • G01B 11/00 - Measuring arrangements characterised by the use of optical techniques
  • G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
  • G01C 3/08 - Use of electric radiation detectors
  • G01S 7/481 - Constructional features, e.g. arrangements of optical elements
  • G01S 7/484 - Transmitters
  • G01S 7/486 - Receivers
  • G01S 7/499 - Details of systems according to groups , , of systems according to group using polarisation effects
  • G01S 17/48 - Active triangulation systems, i.e. using the transmission and reflection of electromagnetic waves other than radio waves
  • G01S 17/89 - Lidar systems, specially adapted for specific applications for mapping or imaging

88.

SYSTEMS AND METHODS FOR COMMISSIONING A MACHINE VISION SYSTEM

      
Application Number US2023066773
Publication Number 2023/220590
Status In Force
Filing Date 2023-05-09
Publication Date 2023-11-16
Owner COGNEX CORPORATION (USA)
Inventor
  • Wurz, Caitlin
  • Liu, Humberto Andres, Leon
  • Atkins Iii, Henry
  • Tanmay, Sinha
  • Surana, Deepak
  • Gauthier, Georges
  • El-Barkouky, Ahmed
  • Brodeur, Patrick
  • Lutzke, Patrick
  • Ruetten, Jens
  • Depre, Tony

Abstract

Methods and systems are provided for commissioning machine vision systems. The methods and systems described herein may automatically configure, or otherwise assist users in configuring, a machine vision system based on a specification package.

IPC Classes  ?

  • G06T 7/80 - Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration

89.

SYSTEM AND METHOD FOR FIELD CALIBRATION OF A VISION SYSTEM

      
Application Number US2023066778
Publication Number 2023/220593
Status In Force
Filing Date 2023-05-09
Publication Date 2023-11-16
Owner COGNEX CORPORATION (USA)
Inventor
  • Wurz, Caitlin
  • Liu, Humberto Andres Leon
  • Brodeur, Patrick
  • Gauthier, Georges
  • Sposato, Kyle
  • Corbett, Michael
  • El-Barkouky, Ahmed

Abstract

A method for three-dimensional (3D) field calibration of a machine vision system includes receiving a set of calibration parameters and an identification of one or more machine vision system imaging devices, determining a camera acquisition parameter for calibration based on the set of calibration parameters, validating the set of calibration parameters and the camera acquisition parameter, and controlling the imaging device(s) to collect image data of a calibration target. The image data may be collected using the determined camera acquisition parameter. The method further includes generating a set of calibration data for the imaging device(s) using the collected image data for the imaging device(s). The set of calibration data can include a maximum error. The method further includes generating a report including the set of calibration data for the imaging device(s) and an indication of whether the maximum error for the imaging device(s) is within an acceptable tolerance and displaying the report on a display.

IPC Classes  ?

  • G06T 7/80 - Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration

90.

SYSTEM AND METHOD FOR DYNAMIC TESTING OF A MACHINE VISION SYSTEM

      
Application Number US2023066779
Publication Number 2023/220594
Status In Force
Filing Date 2023-05-09
Publication Date 2023-11-16
Owner COGNEX CORPORATION (USA)
Inventor
  • Wurz, Caitlin
  • Liu, Humberto Andres Leon
  • Brodeur, Patrick
  • Gauthier, Georges
  • Sposato, Kyle
  • Corbett, Michael
  • Sanz Rodriguez, Saul
  • Ruetten, Jens

Abstract

A method for dynamic testing of a machine vision system includes receiving a set of testing parameters and a selection of a tunnel system. The machine vision system can include the tunnel system and the tunnel system can include a conveyor and at least one imaging device. The method can further include validating the testing parameters and controlling the at least one imaging device to acquire a set of image data of a testing target positioned at a predetermined justification on the conveyor. The testing target can include a plurality of target symbols. The method can further include determining a test result by analyzing the set of image data to determine if the at least one imaging device reads a target symbol associated with the at least one imaging device and generating a report including the test result.

IPC Classes  ?

  • G06T 7/80 - Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration

91.

MACHINE VISION SYSTEM AND METHOD WITH HYBRID ZOOM OPTICAL ASSEMBLY

      
Application Number US2023066413
Publication Number 2023/212735
Status In Force
Filing Date 2023-04-28
Publication Date 2023-11-02
Owner COGNEX CORPORATION (USA)
Inventor
  • Fernandez Dorado, Jose
  • Nunnink, Laurens

Abstract

An optical assembly (120) for a machine vision system (100) having an image sensor (104) includes a lens assembly (108) and a motor system (118) coupled to the lens assembly (108). The lens assembly (108) can include a plurality of solid lens elements (126) and a liquid lens (128), where the liquid lens (128) includes an adjustable membrane (136). The motor system (118) can be configured to move the lens assembly (108) to adjust a distance between the lens assembly (108) and the image sensor (104) of the vision system (100).

IPC Classes  ?

  • G02B 3/14 - Fluid-filled or evacuated lenses of variable focal length
  • G06K 7/10 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation
  • H04N 23/55 - Optical parts specially adapted for electronic image sensorsMounting thereof

92.

Lighting device for imaging systems with light pattern

      
Application Number 29727864
Grant Number D0998872
Status In Force
Filing Date 2020-03-13
First Publication Date 2023-09-12
Grant Date 2023-09-12
Owner COGNEX CORPORATION (USA)
Inventor Pierce, Brian

93.

SYSTEM AND METHOD FOR USE OF POLARIZED LIGHT TO IMAGE TRANSPARENT MATERIALS APPLIED TO OBJECTS

      
Application Number US2023014354
Publication Number 2023/167984
Status In Force
Filing Date 2023-03-02
Publication Date 2023-09-07
Owner COGNEX CORPORATION (USA)
Inventor
  • Carey, Ben, R.
  • Norkett, Ryan, D.
  • Molnar, Gergely, G.

Abstract

This invention provides a system and method inspecting transparent or translucent features on a substrate of an object. A vision system camera, having an image sensor that provides image data to a vision system processor, receives light from a field of view that includes the object through a light-polarizing filter assembly. An illumination source projects polarized light onto the substrate within the field of view. A vision system process locates and registers the substrate, and locates thereon, based upon registration, the transparent or translucent features. A vision system process then performs inspection on the features using predetermined thresholds. The substrate can be a shipping box on a conveyor, having flaps sealed at a seam by transparent tape. Alternatively, a plurality of illuminators or cameras can project and receive polarized light oriented in a plurality of polarization angles, which generates a plurality of images that are combined into a result image.

IPC Classes  ?

  • G01N 21/21 - Polarisation-affecting properties
  • G01N 21/88 - Investigating the presence of flaws, defects or contamination
  • G01N 21/90 - Investigating the presence of flaws, defects or contamination in a container or its contents
  • G01N 21/95 - Investigating the presence of flaws, defects or contamination characterised by the material or shape of the object to be examined
  • G01N 21/84 - Systems specially adapted for particular applications

94.

CONFIGURABLE LIGHT EMISSION BY SELECTIVE BEAM-SWEEPING

      
Application Number US2023013644
Publication Number 2023/164009
Status In Force
Filing Date 2023-02-22
Publication Date 2023-08-31
Owner COGNEX CORPORATION (USA)
Inventor
  • Aljasem, Khalid
  • Eggert, Florian
  • Ruhnau, Thomas
  • Schweier, Andre
  • Filhaber, John

Abstract

An opto-electronic system includes a laser operable to produce a laser beam; an optical element including two or more beam-shaping portions, each of the two or more beam-shaping portions having a different optical property; a beam deflector arranged to sweep the laser beam across the optical element to produce output light; and electronics communicatively coupled with the laser, the beam deflector, or both the laser and the beam deflector. The electronics are configured to cause selective impingement of the laser beam onto a proper subset of the two or more beam-shaping portions of the optical element to modify one or more optical parameters of the output light.

IPC Classes  ?

  • G02B 27/09 - Beam shaping, e.g. changing the cross-sectioned area, not otherwise provided for
  • G02B 26/10 - Scanning systems

95.

CONFIGURABLE LIGHT EMISSION BY SELECTIVE BEAM-SWEEPING

      
Application Number 18172750
Status Pending
Filing Date 2023-02-22
First Publication Date 2023-08-31
Owner Cognex Corporation (USA)
Inventor
  • Aljasem, Khaled
  • Eggert, Florian
  • Ruhnau, Thomas
  • Schweier, André
  • Filhaber, John

Abstract

An opto-electronic system includes a laser operable to produce a laser beam; an optical element including two or more beam-shaping portions, each of the two or more beam-shaping portions having a different optical property; a beam deflector arranged to sweep the laser beam across the optical element to produce output light; and electronics communicatively coupled with the laser, the beam deflector, or both the laser and the beam deflector. The electronics are configured to cause selective impingement of the laser beam onto a proper subset of the two or more beam-shaping portions of the optical element to modify one or more optical parameters of the output light.

IPC Classes  ?

  • G02B 26/10 - Scanning systems
  • G02B 26/08 - Optical devices or arrangements for the control of light using movable or deformable optical elements for controlling the direction of light
  • G02B 27/28 - Optical systems or apparatus not provided for by any of the groups , for polarising

96.

QUICKSORT

      
Application Number 1745349
Status Registered
Filing Date 2023-07-21
Registration Date 2023-07-21
Owner Cognex Corporation (USA)
NICE Classes  ? 09 - Scientific and electric apparatus and instruments

Goods & Services

Image processing software for finding bar codes in an image in order to locate and decode the code.

97.

System and method for reduced-speckle laser line generation

      
Application Number 17977958
Grant Number 12493196
Status In Force
Filing Date 2022-10-31
First Publication Date 2023-07-27
Grant Date 2025-12-09
Owner Cognex Corporation (USA)
Inventor Filhaber, John F.

Abstract

An illumination apparatus for reducing speckle effect in light reflected off an illumination target includes a laser; a linear diffuser positioned in an optical path between an illumination target and the laser to diffuse collimated laser light in a planar fan of diffused light that spreads in one dimension across at least a portion of the illumination target; and a beam deflector to direct the collimated laser light incident on the beam deflector to sweep across different locations on the linear diffuser within an exposure time for illumination of the illumination target by the diffused light. The different locations span a distance across the linear diffuser that provides sufficient uncorrelated speckle patterns, at an image sensor, in light reflected from an intersection of the planar fan of light with the illumination target to add incoherently when imaged by the image sensor within the exposure time.

IPC Classes  ?

  • H04N 13/254 - Image signal generators using stereoscopic image cameras in combination with electromagnetic radiation sources for illuminating objects
  • G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
  • G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
  • G02B 5/02 - Diffusing elementsAfocal elements
  • G02B 26/10 - Scanning systems
  • G02B 27/30 - Collimators
  • G02B 27/48 - Laser speckle optics

98.

Methods and apparatus for generating a three-dimensional reconstruction of an object with reduced distortion

      
Application Number 18099544
Grant Number 11954767
Status In Force
Filing Date 2023-01-20
First Publication Date 2023-07-13
Grant Date 2024-04-09
Owner Cognex Corporation (USA)
Inventor
  • Schaffer, Martin
  • Große, Marcus

Abstract

Methods, systems, and computer readable media for generating a three-dimensional reconstruction of an object with reduced distortion are described. In some aspects, a system includes at least two image sensors, at least two projectors, and a processor. Each image sensor is configured to capture one or more images of an object. Each projector is configured to illuminate the object with an associated optical pattern and from a different perspective. The processor is configured to perform the acts of receiving, from each image sensor, for each projector, images of the object illuminated with the associated optical pattern and generating, from the received images, a three-dimensional reconstruction of the object. The three-dimensional reconstruction has reduced distortion due to the received images of the object being generated when each projector illuminates the object with an associated optical pattern from the different perspective.

IPC Classes  ?

  • G06T 11/00 - 2D [Two Dimensional] image generation
  • H04N 5/72 - Modifying the appearance of television pictures by optical filters or diffusing screens
  • H04N 13/00 - Stereoscopic video systemsMulti-view video systemsDetails thereof
  • H04N 13/243 - Image signal generators using stereoscopic image cameras using three or more 2D image sensors
  • H04N 13/296 - Synchronisation thereofControl thereof

99.

Lens assembly with integrated feedback loop and time-of-flight sensor

      
Application Number 17892943
Grant Number 11782156
Status In Force
Filing Date 2022-08-22
First Publication Date 2023-06-22
Grant Date 2023-10-10
Owner Cognex Corporation (USA)
Inventor
  • Weber, Andreas
  • Nunnink, Laurens
  • Delasauce, Rene
  • Equitz, William

Abstract

This invention provides an integrated time-of-flight sensor that delivers distance information to a processor associated with the camera assembly and vison system. The distance is processed with the above-described feedback control, to auto-focus the camera assembly's variable lens during runtime operation based on the particular size/shape object(s) within the field of view. The shortest measured distance is used to set the focus distance of the lens. To correct for calibration or drift errors, a further image-based focus optimization can occur around the measured distance and/or based on the measured temperature. The distance information generated by the time-of-flight sensor can be employed to perform other functions. Other functions include self-triggering of image acquisition, object size dimensioning, detection and analysis of object defects and/or gap detection between objects in the field of view and software-controlled range detection to prevent unintentional reading of (e.g.) IDs on objects outside a defined range (presentation mode).

IPC Classes  ?

  • G01S 17/10 - Systems determining position data of a target for measuring distance only using transmission of interrupted, pulse-modulated waves
  • G01S 7/486 - Receivers
  • G02B 7/04 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses with mechanism for focusing or varying magnification
  • G01S 17/36 - Systems determining position data of a target for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated with phase comparison between the received signal and the contemporaneously transmitted signal
  • G02B 7/08 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses with mechanism for focusing or varying magnification adapted to co-operate with a remote control mechanism
  • G02B 7/40 - Systems for automatic generation of focusing signals using time delay of the reflected waves, e.g. of ultrasonic waves
  • G01S 17/86 - Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
  • H04N 23/54 - Mounting of pick-up tubes, electronic image sensors, deviation or focusing coils
  • H04N 23/55 - Optical parts specially adapted for electronic image sensorsMounting thereof
  • H04N 23/67 - Focus control based on electronic image sensor signals

100.

GRAPHICAL PROGRAMMING ENVIRONMENT

      
Application Number 18076183
Status Pending
Filing Date 2022-12-06
First Publication Date 2023-06-08
Owner Cognex Corporation (USA)
Inventor
  • Palmieri, Lou
  • Vanca, Robert
  • Dunning, James
  • Horvath, Adam

Abstract

The techniques described herein relate to methods, apparatus, and computer readable media for editing a graphical program using a graphical programming interface. Editing the graphical program may include displaying, via the graphical programming interface, a plurality of existing graphical components that provide functionality for at least one computer program thread; receiving data indicating a selection of a new graphical component for inserting into the plurality of existing graphical components; determining, based on an associated graphical component of the plurality of existing graphical components, a set of one or more placement locations for inserting the new graphical component; and displaying, on the graphical programming interface, the set of one or more placement locations.

IPC Classes  ?

  • G06F 8/34 - Graphical or visual programming
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