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.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et 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.
4.
SYSTEM AND METHOD FOR FIELD CALIBRATION OF A VISION SYSTEM
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.
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.
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.
G02B 7/09 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles avec mécanisme de mise au point ou pour faire varier le grossissement adaptés pour la mise au point automatique ou pour faire varier le grossissement de façon automatique
G02B 26/00 - Dispositifs ou dispositions optiques pour la commande de la lumière utilisant des éléments optiques mobiles ou déformables
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
7.
STATISTICAL ANALYSIS-BASED TECHNIQUES FOR DETERMINING A PREFERRED TRANSFORMATION TYPE FOR 3D IMAGE PROCESSING USING MACHINE LEARNING
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.
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.
G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
G06V 10/74 - Appariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
09 - Appareils et instruments scientifiques et électriques
Produits et 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.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et 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.
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.
G06F 18/40 - Dispositions logicielles spécialement adaptées à la reconnaissance des formes, p. ex. interfaces utilisateur ou boîtes à outils à cet effet
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p. ex. interaction avec des règles ou des cadrans
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
G06V 10/70 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique
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.
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
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.
G06V 10/14 - Caractéristiques optiques de l’appareil qui effectue l’acquisition ou des dispositifs d’éclairage
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/776 - ValidationÉvaluation des performances
G06V 10/98 - Détection ou correction d’erreurs, p. ex. en effectuant une deuxième exploration du motif ou par intervention humaineÉvaluation de la qualité des motifs acquis
16.
METHODS, SYSTEMS, AND MEDIA FOR GENERATING IMAGES OF MULTIPLE SIDES OF AN OBJECT
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.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et 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.
18.
Systems and Methods for Stitching Sequential Images of an Object
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.
G06T 11/60 - Édition de figures et de texteCombinaison de figures ou de texte
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p. ex. forme, nature, code
G06T 3/18 - Déformation d’images, p. ex. réarrangement de pixels individuellement
G06T 7/246 - Analyse du mouvement utilisant des procédés basés sur les caractéristiques, p. ex. le suivi des coins ou des segments
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
H04N 23/698 - Commande des caméras ou des modules de caméras pour obtenir un champ de vision élargi, p. ex. pour la capture d'images panoramiques
H04N 23/74 - Circuits de compensation de la variation de luminosité dans la scène en influençant la luminosité de la scène à l'aide de moyens d'éclairage
19.
SYSTEM AND METHOD FOR EXTRACTING AND MEASURING SHAPES OF OBJECTS HAVING CURVED SURFACES WITH A VISION SYSTEM
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.
G06T 3/067 - Remodelage ou dépliement de structures en arbre 3D sur des plans 2D
G06V 10/46 - Descripteurs pour la forme, descripteurs liés au contour ou aux points, p. ex. transformation de caractéristiques visuelles invariante à l’échelle [SIFT] ou sacs de mots [BoW]Caractéristiques régionales saillantes
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et 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.
22.
EASY LINE FINDER BASED ON DYNAMIC TIME WARPING METHOD
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.
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.
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.
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
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.
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.
G01B 9/02004 - Interféromètres caractérisés par la commande ou la génération des propriétés intrinsèques du rayonnement utilisant plusieurs fréquences utilisant le balayage des fréquences
G01B 11/24 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des contours ou des courbes
G01S 17/894 - Imagerie 3D avec mesure simultanée du temps de vol sur une matrice 2D de pixels récepteurs, p. ex. caméras à temps de vol ou lidar flash
G01S 7/4915 - Mesure du temps de retard, p. ex. détails opérationnels pour les composants de pixelsMesure de la phase
G01S 17/34 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes continues, soit modulées en amplitude, en fréquence ou en phase, soit non modulées utilisant la transmission d'ondes continues modulées en fréquence, tout en faisant un hétérodynage du signal reçu, ou d’un signal dérivé, avec un signal généré localement, associé au signal transmis simultanément
27.
SYSTEM AND METHOD FOR USE OF POLARIZED LIGHT TO IMAGE TRANSPARENT MATERIALS APPLIED TO OBJECTS
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.
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.
G01B 11/04 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer la longueur, la largeur ou l'épaisseur spécialement adaptés pour mesurer la longueur ou la largeur d'objets en mouvement
G01B 11/25 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des contours ou des courbes en projetant un motif, p. ex. des franges de moiré, sur l'objet
30.
SYSTEMS AND METHODS FOR TRANSLATIONAL TRIGGERING FOR IMAGE-BASED INSPECTION OF OBJECTS
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.
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.
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
H04N 23/959 - Systèmes de photographie numérique, p. ex. systèmes d'imagerie par champ lumineux pour l'imagerie à grande profondeur de champ en ajustant la profondeur de champ pendant la capture de l'image, p. ex. en maximisant ou en réglant la portée en fonction des caractéristiques de la scène
H04N 23/67 - Commande de la mise au point basée sur les signaux électroniques du capteur d'image
32.
SYSTEM AND METHOD FOR ESTIMATING BOX SHAPE REPRESENTATION OF A GENERALLY CUBOIDAL OBJECT
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.
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).
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.
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.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et 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
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et 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 Non-downloadable software for acquiring, processing, analyzing and understanding digital images and extracting visual data; 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; Non-downloadable software for logistics applications; Non-downloadable web-based software for machine vision; Non-downloadable cloud-computing software for machine vision
39.
INSPECTION METHOD BASED ON EDGE FIELD AND DEEP LEARNING
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.
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.
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
G06F 9/38 - Exécution simultanée d'instructions, p. ex. pipeline ou lecture en mémoire
G06F 12/0862 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p. ex. mémoires cache avec pré-lecture
41.
METHOD AND SYSTEM FOR ONE-DIMENSIONAL SIGNAL EXTRACTION FOR VARIOUS COMPUTER PROCESSORS
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.
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.
G01N 21/88 - Recherche de la présence de criques, de défauts ou de souillures
G01B 11/25 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des contours ou des courbes en projetant un motif, p. ex. des franges de moiré, sur l'objet
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.
G06V 10/24 - Alignement, centrage, détection de l’orientation ou correction de l’image
G06V 10/40 - Extraction de caractéristiques d’images ou de vidéos
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
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.
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.
F21K 9/62 - Agencements optiques intégrés dans la source lumineuse, p. ex. pour améliorer l’indice de rendu des couleurs ou l’extraction de lumière en utilisant des chambres de mélange, p. ex. des enceintes à parois réfléchissantes
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et 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.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et 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.
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.
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.
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.
G02B 7/10 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles avec mécanisme de mise au point ou pour faire varier le grossissement par déplacement axial relatif de plusieurs lentilles, p. ex. lentilles d'objectif à distance focale variable
G02B 3/14 - Lentilles remplies d'un fluide ou à l'intérieur desquelles le vide a été fait à distance focale variable
51.
Lens Assembly and Thermal Correction for Machine Vision System
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.
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).
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.
G06T 7/33 - Détermination des paramètres de transformation pour l'alignement des images, c.-à-d. recalage des images utilisant des procédés basés sur les caractéristiques
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/46 - Descripteurs pour la forme, descripteurs liés au contour ou aux points, p. ex. transformation de caractéristiques visuelles invariante à l’échelle [SIFT] ou sacs de mots [BoW]Caractéristiques régionales saillantes
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
G06V 10/772 - Détermination de motifs de référence représentatifs, p. ex. motifs de valeurs moyennes ou déformantsGénération de dictionnaires
54.
ILLUMINATION LINE GENERATION BY DOUBLE-DUTY DIFFUSION
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.
G01N 15/075 - Recherche de la concentration des suspensions de particules par des moyens optiques
G01N 21/31 - CouleurPropriétés spectrales, c.-à-d. comparaison de l'effet du matériau sur la lumière pour plusieurs longueurs d'ondes ou plusieurs bandes de longueurs d'ondes différentes en recherchant l'effet relatif du matériau pour les longueurs d'ondes caractéristiques d'éléments ou de molécules spécifiques, p. ex. spectrométrie d'absorption atomique
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.
G06T 11/60 - Édition de figures et de texteCombinaison de figures ou de texte
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p. ex. forme, nature, code
G06T 3/18 - Déformation d’images, p. ex. réarrangement de pixels individuellement
G06T 7/246 - Analyse du mouvement utilisant des procédés basés sur les caractéristiques, p. ex. le suivi des coins ou des segments
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
H04N 23/698 - Commande des caméras ou des modules de caméras pour obtenir un champ de vision élargi, p. ex. pour la capture d'images panoramiques
H04N 23/74 - Circuits de compensation de la variation de luminosité dans la scène en influençant la luminosité de la scène à l'aide de moyens d'éclairage
56.
System and method for three-dimensional scan of moving objects longer than the field of view
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.
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.
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.
G01B 11/30 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer la rugosité ou l'irrégularité des surfaces
59.
SYSTEMS AND METHODS FOR CONFIGURING MACHINE VISION TUNNELS
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.
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.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
G06F 18/2415 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques basées sur des modèles paramétriques ou probabilistes, p. ex. basées sur un rapport de vraisemblance ou un taux de faux positifs par rapport à un taux de faux négatifs
G06F 18/40 - Dispositions logicielles spécialement adaptées à la reconnaissance des formes, p. ex. interfaces utilisateur ou boîtes à outils à cet effet
G06T 7/143 - DécoupageDétection de bords impliquant des approches probabilistes, p. ex. la modélisation à "champs aléatoires de Markov [MRF]"
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/50 - Extraction de caractéristiques d’images ou de vidéos en effectuant des opérations dans des blocs d’imagesExtraction de caractéristiques d’images ou de vidéos en utilisant des histogrammes, p. ex. l’histogramme de gradient orienté [HoG]Extraction de caractéristiques d’images ou de vidéos en utilisant l’addition des valeurs d’intensité d’imageAnalyse de projection
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et 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.
62.
METHODS AND APPARATUS FOR DETERMINING ORIENTATIONS OF AN OBJECT IN THREE-DIMENSIONAL DATA
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.
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.
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.
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/50 - Extraction de caractéristiques d’images ou de vidéos en effectuant des opérations dans des blocs d’imagesExtraction de caractéristiques d’images ou de vidéos en utilisant des histogrammes, p. ex. l’histogramme de gradient orienté [HoG]Extraction de caractéristiques d’images ou de vidéos en utilisant l’addition des valeurs d’intensité d’imageAnalyse de projection
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
09 - Appareils et instruments scientifiques et électriques
Produits et 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
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).
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.
G01B 11/06 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer la longueur, la largeur ou l'épaisseur pour mesurer l'épaisseur
G01B 11/14 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer la distance ou la marge entre des objets ou des ouvertures espacés
G01B 11/28 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des superficies
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.
G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
B07C 3/14 - Appareillages caractérisés par les moyens utilisés pour détecter la destination utilisant des moyens de détection photosensibles
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
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.
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.
G01B 11/00 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques
G01B 11/25 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des contours ou des courbes en projetant un motif, p. ex. des franges de moiré, sur l'objet
G01C 3/08 - Utilisation de détecteurs électriques de radiations
G01S 7/481 - Caractéristiques de structure, p. ex. agencements d'éléments optiques
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.
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.
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.
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).
G02B 3/14 - Lentilles remplies d'un fluide ou à l'intérieur desquelles le vide a été fait à distance focale variable
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
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.
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.
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.
G02B 26/08 - Dispositifs ou dispositions optiques pour la commande de la lumière utilisant des éléments optiques mobiles ou déformables pour commander la direction de la lumière
G02B 27/28 - Systèmes ou appareils optiques non prévus dans aucun des groupes , pour polariser
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.
G02B 27/48 - Systèmes optiques utilisant la granulation produite par laser
G01B 11/14 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer la distance ou la marge entre des objets ou des ouvertures espacés
H04N 13/254 - Générateurs de signaux d’images utilisant des caméras à images stéréoscopiques en combinaison avec des sources de rayonnement électromagnétique pour l’éclairage du sujet
G01B 11/25 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des contours ou des courbes en projetant un motif, p. ex. des franges de moiré, sur l'objet
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.
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).
G01S 17/10 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes à modulation d'impulsion interrompues
G02B 7/04 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles avec mécanisme de mise au point ou pour faire varier le grossissement
G01S 17/36 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes continues, soit modulées en amplitude, en fréquence ou en phase, soit non modulées avec comparaison en phase entre le signal reçu et le signal transmis au même moment
G02B 7/08 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles avec mécanisme de mise au point ou pour faire varier le grossissement adaptés pour fonctionner en combinaison avec un mécanisme de télécommande
G02B 7/40 - Systèmes pour la génération automatique de signaux de mise au point utilisant le retard des ondes réfléchies, p. ex. d'ondes ultrasonores
G01S 17/86 - Combinaisons de systèmes lidar avec des systèmes autres que lidar, radar ou sonar, p. ex. avec des goniomètres
H04N 23/54 - Montage de tubes analyseurs, de capteurs d'images électroniques, de bobines de déviation ou de focalisation
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.
The techniques described herein relate to methods, apparatus, and computer readable media for measuring object characteristics by interpolating the object characteristics using stored associations. A first image of at least part of a ground surface with a first representation of a laser line projected onto the ground surface from a first pose is received. A first association between a known value of the characteristic of the ground surface of the first image with the first representation is determined. A second image of at least part of a first training object on the ground surface with a second representation of the laser line projected onto the first training object from the first pose is received. A second association between a known value of the characteristic of the first training object with the second representation is determined. The first and second association for measuring the characteristic of a new object are stored.
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.
This invention provides an aimer assembly for a vision system that is coaxial (on-axis) with the camera optical axis, thus providing an aligned aim point at a wide range of working distances. The aimer includes a projecting light element located aside the camera optical axis. The beam and received light from the imaged (illuminated) scene are selectively reflected or transmitted through a dichoric mirror assembly in a manner that permits the beam to be aligned with the optical axis and projected to the scene while only light from the scene is received by the sensor. The aimer beam and illuminator employ differing light wavelengths. In a further embodiment, an internal illuminator includes a plurality of light sources below the camera optical axis. Some of the light sources are covered by a prismatic structure for close distance, and other light sources are collimated, projecting over a longer distance.
G06K 7/015 - Alignement ou centrage du dispositif de lecture par rapport au support d'enregistrement
F21V 13/04 - Combinaisons de deux sortes d'éléments uniquement les éléments étant des réflecteurs et des réfracteurs
F21V 5/04 - Réfracteurs pour sources lumineuses de forme lenticulaire
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
G03B 3/00 - Dispositions pour la mise au point présentant un intérêt général pour les appareils photographiques, les appareils de projection ou les tireuses
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 pre-trained machine learning model and one or more other machine learning models that can be trained in a field training process. The pre-trained machine learning model may be a deep machine learning model.
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 20/70 - Étiquetage du contenu de scène, p. ex. en tirant des représentations syntaxiques ou sémantiques
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
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 pretrained machine learning model and one or more other machine learning models that can be trained in a field training process. The pre-trained machine learning model may be a deep machine learning model.
G06V 20/62 - Texte, p. ex. plaques d’immatriculation, textes superposés ou légendes des images de télévision
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
This invention provides a vision system having a housing and an interchangeable lens module is provided. The module is adapted to seat on a C-mount ring provided on the front, mounting face of the housing. The module is attached via a plurality of fasteners that pass through a frame of the module and into the mounting face. The module includes a connector in a fixed location, which mates with a connector well on the mounting face to provide power and control to a driver board that operates a variable (e.g. liquid) lens within the optics of the lens module. The driver board is connected to the lens body by a flexible printed circuit board (PCB), which also allows for axial motion of the lens body with respect to the frame. This axial motion can be effected by an adjustment ring that can include an indexed/lockable, geared, outer surface.
G03B 17/14 - Corps d'appareils avec moyens pour supporter des objectifs, des lentilles additionnelles, des filtres, des masques ou des tourelles de façon interchangeable
A method for an imaging module can include rotating an imaging assembly that includes an imaging device about a first pivot point of a bracket to a select first orientation, fastening the imaging assembly to the bracket at the first orientation, rotating a mirror assembly that includes a mirror about a second pivot point of the bracket to a select second orientation, and fastening the mirror assembly to the bracket at the second orientation. An adjustable, selectively oriented imaging assembly of a first imaging module can acquire images using an adjustable, selectively oriented mirror assembly of a second imaging module.
G02B 7/182 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour prismesMontures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour miroirs pour miroirs
G02B 7/198 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour prismesMontures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour miroirs pour miroirs avec des moyens pour régler la position du miroir par rapport à son support
A method for an imaging module can include rotating an imaging assembly that includes an imaging device about a first pivot point of a bracket to a select first orientation, fastening the imaging assembly to the bracket at the first orientation, rotating a mirror assembly that includes a mirror about a second pivot point of the bracket to a select second orientation, and fastening the mirror assembly to the bracket at the second orientation. An adjustable, selectively oriented imaging assembly of a first imaging module can acquire images using an adjustable, selectively oriented mirror assembly of a second imaging module.
G02B 7/182 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour prismesMontures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour miroirs pour miroirs
H04N 5/247 - Disposition des caméras de télévision
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
94.
MACHINE VISION SYSTEM AND METHOD WITH MULTISPECTRAL LIGHT ASSEMBLY
A multispectral light assembly for an illumination system includes a multispectral light source configured to generate a plurality of different wavelengths of light and a light pipe positioned in front of the multispectral light source and configured to provide color mixing for two or more of the plurality of different wavelengths. The multispectral light assembly also includes a diffusive surface on the light pipe and a projection lens positioned in front of the diffusive surface. A processor device may be in communication with the multispectral light assemblies and may be configured to control activation of the multispectral light source.
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
B60Q 1/02 - Agencement des dispositifs de signalisation optique ou d'éclairage, leur montage, leur support ou les circuits à cet effet les dispositifs étant principalement destinés à éclairer la route en avant du véhicule ou d'autres zones de la route ou des environs
F21K 9/23 - Sources lumineuses rétrocompatibles pour dispositifs d’éclairage avec un seul culot pour chaque source lumineuse, p. ex. pour le remplacement de lampes à incandescence avec un culot à baïonnette ou à vis
F21V 23/00 - Agencement des éléments du circuit électrique dans ou sur les dispositifs d’éclairage
G06K 7/12 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant une longueur d'onde choisie, p. ex. pour lire des marques rouges et ignorer des marques bleues
G02B 7/02 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles
G02B 7/08 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles avec mécanisme de mise au point ou pour faire varier le grossissement adaptés pour fonctionner en combinaison avec un mécanisme de télécommande
95.
Machine vision system with multispectral light assembly
A multispectral light assembly includes a multispectral light source configured to generate a plurality of different wavelengths of light, a light pipe positioned in front of the multispectral light source and configured to provide color mixing for two or more of the plurality of different wavelengths, a diffusive surface on the light pipe exit surface, and a projection lens positioned in front of the diffusive surface. A processor device is in communication with the multispectral light assemblies to control activation of the multispectral light source. A machine vision system includes an illumination assembly with a plurality of multispectral light assemblies, an optics assembly, a sensor assembly, and a processor device in communication with the optics assembly, the sensor assembly, and the illumination assembly.
F21K 9/62 - Agencements optiques intégrés dans la source lumineuse, p. ex. pour améliorer l’indice de rendu des couleurs ou l’extraction de lumière en utilisant des chambres de mélange, p. ex. des enceintes à parois réfléchissantes
A machine vision system can include an image sensor assembly including an image sensor, a lens assembly coupled to the image sensor assembly, an illumination assembly coupled to the lens assembly, and a removable front cover positioned in front of the illumination assembly. The illumination assembly can include a plurality of multispectral light assemblies. Each multispectral light assembly of the plurality of multispectral light assemblies can include a multispectral light source having a plurality of color LED dies configured to generate at least two different wavelengths of light, a light pipe positioned in front of the multispectral light source and having an exit surface, a diffusive surface on the exit surface of the light pipe, and a projection lens positioned in front of the diffusive surface. The machine vision system can also include an illumination sensor configured to detect light from the illumination assembly.
H04N 5/235 - Circuits pour la compensation des variations de la luminance de l'objet
F21V 8/00 - Utilisation de guides de lumière, p. ex. dispositifs à fibres optiques, dans les dispositifs ou systèmes d'éclairage
G01S 17/36 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes continues, soit modulées en amplitude, en fréquence ou en phase, soit non modulées avec comparaison en phase entre le signal reçu et le signal transmis au même moment
A computer-implemented method for scanning a side of an object (22). The method can include determining a scanning pattern for an imaging device (e.g., based on a distance between the side of the object and the imaging device), and moving the controllable mirror (30) according to the scanning pattern to acquire a plurality of images of the side of the object. A region of interest can be identified based on the plurality of images.
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
98.
SYSTEMS AND METHODS FOR ASSIGNING A SYMBOL TO AN OBJECT
A method for assigning a symbol to an object in an image includes receiving the image captured by an imaging device where the symbol may be located within the image. The method further includes receiving, in a first coordinate system, a three-dimensional (3D) location of one or more points that corresponds to pose information indicative of a 3D pose of the object in the image, mapping the 3D location of the one or more points of the object to a 2D location within the image, and assigning the symbol to the object based on a relationship between a 2D location of the symbol in the image and the 2D location of the one or more points of the object in the image.
A method for assigning a symbol to an object in an image includes receiving the image captured by an imaging device where the symbol may be located within the image. The method further includes receiving, in a first coordinate system, a three-dimensional (3D) location of one or more points that corresponds to pose information indicative of a 3D pose of the object in the image, mapping the 3D location of the one or more points of the object to a 2D location within the image, and assigning the symbol to the object based on a relationship between a 2D location of the symbol in the image and the 2D location of the one or more points of the object in the image.
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.
