Method for resizing an image, the method comprising the steps: obtaining an image of a user comprising at least one biometric identifier, wherein the biometric identifier comprises a plurality of biometric characteristics; determining a first frequency of at least part of the plurality of the biometric characteristics in the image; determining a second frequency based on the first frequency and a property of the biometric identifier; resizing the image based on a ratio of the first and the second frequency; obtaining a resized image.
A computer-implemented method for obtaining information on biometric features of a fingerprint of a user, the method comprising: - obtaining an image comprising an object carrying one or more biometric features of a user, the image having a size of NxM pixels - processing the image and determining information indicative at least of a presence of a biometric feature in the block and a kind of the biometric feature to obtain a result - outputting the result identifying the information wherein the result has a form of n x m blocks of identical size and the result associates information indicative at least of a presence of a biometric feature and a kind of the biometric feature with each block, wherein N is an integer multiple of n and M is an integer multiple of m.
G06V 10/40 - Extraction of image or video features
G06V 10/50 - Extraction of image or video features by performing operations within image blocksExtraction of image or video features by using histograms, e.g. histogram of oriented gradients [HoG]Extraction of image or video features by summing image-intensity valuesProjection analysis
4.
COMPUTER-IMPLEMENTED METHOD FOR OBTAINING INFORMATION ON BIOMETRIC FEATURES OF A USER
A computer-implemented method for obtaining information on biometric features of a fingerprint of a user, the method comprising obtaining an image comprising an object carrying one or more biometric features of a user, the image having a size of N×M pixels, processing the image and determining information indicative at least of a presence of a biometric feature in the block and a kind of the biometric feature to obtain a result, and outputting the result identifying the information wherein the result has a form of n×m blocks of identical size and the result associates information indicative at least of a presence of a biometric feature and a kind of the biometric feature with each block, wherein N is an integer multiple of n and M is an integer multiple of m.
A computer-implemented method for jointly training at least two different spoof-detection systems using a single data set, the single data set comprising at least two sub-sets of training data, wherein each sub-set comprises at least two different kinds of training data, the method comprising:
training, in a first training cycle, the at least two different spoof-detection systems a first sub-set of training data
determining, based on a result of the training, for each of the at least two different spoof-detection systems, a score for each of the at least two different kinds of training data in the sub-set of training data
weighting, based on the scores, each kind of training data in a second sub-set of training data to obtain weighted training data
training, in a subsequent training cycle, the at least two different spoof-detection systems using the weighted training data.
A computer-implemented method for jointly training at least two different spoof-detection systems using a single data set, the single data set comprising at least two sub-sets of training data, wherein each sub-set comprises at least two different kinds of training data, the method comprising: training, in a first training cycle, the at least two different spoof-detection systems a first sub-set of training data determining, based on a result of the training, for each of the at least two different spoof-detection systems, a score for each of the at least two different kinds of training data in the sub-set of training data weighting, based on the scores, each kind of training data in a second sub-set of training data to obtain weighted training data training, in a subsequent training cycle, the at least two different spoof-detection systems using the weighted training data.
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 40/40 - Spoof detection, e.g. liveness detection
Method for resizing an image, the method comprising the steps: obtaining an image of a user comprising at least one biometric identifier, wherein the biometric identifier comprises a plurality of biometric characteristics; determining a first frequency of at least part of the plurality of the biometric characteristics in the image; determining a second frequency based on the first frequency and a property of the biometric identifier; resizing the image based on a ratio of the first and the second frequency; obtaining a resized image.
A computer-implemented method for determining an affine transformation for transforming a second image so that features of the second image coincide with corresponding features of a first image, the computer-implemented method comprising obtaining the second image comprising the features and obtaining the first image comprising the corresponding features, processing the images by a transformation calculator, thereby determining an indication of whether the affine transformation exists and determining parameters defining the affine transformation, and outputting the affine transformation, comprising outputting the indication of whether the affine transformation exists and outputting a data structure indicative of the parameters defining the affine transformation.
G06T 7/33 - Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
G06T 3/4046 - Scaling of whole images or parts thereof, e.g. expanding or contracting using neural networks
G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
Method for differentiating a real object in an image from a spoof of the real object, the method comprising, obtaining an image comprising at least one object, wherein the object comprises at least one biometric identifier, such as a finger, a fingerprint, a face or a palm; extracting three-dimensional information and semantic information from the image, wherein the semantic information relates the at least one object in the image to the at least one biometric identifier and/or relates different objects in the image to each other; merging the extracted three-dimensional and semantic information to a combined information; processing the combined information by a classifier; outputting by the classifier a data set which indicates whether the at least one object in the image is the real object or a spoof of the real object.
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 40/40 - Spoof detection, e.g. liveness detection
11.
METHOD AND SYSTEM FOR IDENTIFYING SPOOFS OF IMAGES
A method for differentiating a real object in an image from a spoof of the real object, the method comprising obtaining an image comprising at least one object, wherein the object comprises at least one biometric identifier, such as a finger, a fingerprint, a face or a palm, extracting three-dimensional information and semantic information from the image, wherein the semantic information relates the at least one object in the image to the at least one biometric identifier and/or relates different objects in the image to each other, merging the extracted three-dimensional and semantic information to a combined information, processing the combined information by a classifier, and outputting by the classifier a data set which indicates whether the at least one object in the image is the real object or a spoof of the real object.
G06V 10/40 - Extraction of image or video features
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
G06V 40/10 - Human or animal bodies, e.g. vehicle occupants or pedestriansBody parts, e.g. hands
12.
COMPUTER-IMPLEMENTED METHOD FOR DETERMINING AN AFFINE TRANSFORMATION
A computer-implemented method for determining an affine transformation for transforming a second image so that features of the second image coincide with corresponding features of a first image, the computer-implemented method comprising: obtaining the second image comprising the features and obtaining the first image comprising the corresponding features; processing the images by a transformation calculator, thereby determining an indication whether the affine transformation exists and determining parameters defining the affine transformation; outputting the affine transformation, comprising outputting the indication whether the affine transformation exists and outputting a data structure indicative of the parameters defining the affine transformation.
A computer-implemented method for determining an affine transformation for transforming a second image so that features of the second image coincide with corresponding features of a first image, the computer-implemented method comprising obtaining the second image comprising the features and obtaining the first image comprising the corresponding features, processing the images by a transformation calculator, thereby determining an indication of whether the affine transformation exists and determining parameters defining the affine transformation, and outputting the affine transformation, comprising outputting the indication of whether the affine transformation exists and outputting a data structure indicative of the parameters defining the affine transformation.
G06T 3/4046 - Scaling of whole images or parts thereof, e.g. expanding or contracting using neural networks
G06T 7/33 - Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
A computer-implemented method for determining an affine transformation for transforming a second image so that features of the second image coincide with corresponding features of a first image, the computer-implemented method comprising: obtaining the second image comprising the features and obtaining the first image comprising the corresponding features; processing the images by a transformation calculator, thereby determining an indication whether the affine transformation exists and determining parameters defining the affine transformation; outputting the affine transformation, comprising outputting the indication whether the affine transformation exists and outputting a data structure indicative of the parameters defining the affine transformation.
A computer-implemented method for obtaining a combined image from two images, the computer-implemented method comprising: obtaining a first original image and a second original image of a biometric feature of a user, the biometric feature comprising a plurality of characteristics; determining a frequency of at least some of the characteristics in the first original image and in the second original image; resizing, based on the determined frequency, the first original image and/or the second original image to obtain a first image and a second image; identifying, in the first image and in the second image, the characteristics and store the first and second image and the identified characteristics; for at least some of the identified characteristics in the first image, identifying corresponding identified characteristics in the second image; deriving an affine transformation for transforming the at least some of the identified characteristics in the second image into the corresponding identified characteristics in the first image; modifying at least a portion of the second image using the affine transformation and obtaining a combined image comprising at least one portion of the first image and the at least one modified portion of the second image.
A computer-implemented method for obtaining a combined image from two images, the computer-implemented method comprising: obtaining a first image and a second image of a biometric feature of a user, the biometric feature comprising a plurality of characteristics; identifying, in the first image and in the second image, the characteristics; storing the first and second image and the identified characteristics; for at least some of the identified characteristics in the first image, identifying corresponding identified characteristics in the second image;
deriving a transformation for transforming the at least some of the identified characteristics in the second image into the corresponding identified characteristics in the first image; and modifying at least a portion of the second image using the transformation and obtaining a combined image comprising at least one portion of the first image and the at least one modified portion of the second image.
A method for obtaining a combined image comprises: obtaining two original images of a user's biometric feature comprising a plurality of characteristics; determining a frequency of the characteristics in the first original image and in the second original image; resizing, based on the determined frequency, the first and/or second original images to obtain a first image and a second image; identifying, in the first image and in the second image, a subset of the plurality of characteristics; for some of the identified characteristics in the first image, identifying corresponding identified characteristics in the second image; deriving an affine transformation for transforming the identified characteristics in the second image into the corresponding identified characteristics in the first image; modifying a portion of the second image using the affine transformation; and obtaining the combined image comprising one portion of the first image and the modified portion of the second image.
G06V 40/18 - Eye characteristics, e.g. of the iris
19.
Method for verifying the identity of a user by identifying an object within an image that has a biometric characteristic of the user and separating a portion of the image comprising the biometric characteristic from other portions of the image
A method includes obtaining, by a processing device from an optical sensor of a mobile device, an image of an object; processing, by the processing device, the image using a neural network, wherein processing the image includes distinguishing, using the neural network, a first portion of the image including a region of interest, ROI, from a second portion of the image, wherein processing the image comprises processing the image by an encoder to obtain an encoded image and processing the encoded image by a decoder to obtain a decoded output image; after processing the image, extracting, by the processing device, a biometric characteristic of the object from the ROI; extracting, by the processing device, a biometric characteristic of the object from the ROI; and processing, by the processing device, the biometric characteristic of the object to determine whether the biometric characteristic of the object identifies a user.
Method for verifying the identity of a user by identifying an object within an image that has a biometric characteristic of the user and mobile device for executing the method
A method includes obtaining, by a processing device from an optical sensor of a mobile device, an image; processing, by the processing device, the image by using a neural network to identify a position of an object in the image and the object in the image, thereby obtaining an identified object; after processing the image, extracting, by the processing device from the identified object, a biometric characteristic, and providing, by the processing device, at least the biometric characteristic as input to determine whether the biometric characteristic identifies a user.
A computer-implemented method for identifying a user uses a computing device comprising an illumination source that, when activated, emits visible light, the method comprising taking two images of a scene potentially comprising a living body part carrying a biometric characteristic, wherein a first image is taken without the illumination source activated and the second image is taken with the illumination source activated, transferring the first image and the second image to a neural network and processing, by the neural network the first image and the second image, by comparing the first image and the second image, thereby determining whether the first image and the second image are of the living body part, and, if it is determined that the first image and the second image are of the living body part, performing an identification algorithm to find a biometric characteristic for identifying the user.
G06V 10/50 - Extraction of image or video features by performing operations within image blocksExtraction of image or video features by using histograms, e.g. histogram of oriented gradients [HoG]Extraction of image or video features by summing image-intensity valuesProjection analysis
G06V 10/56 - Extraction of image or video features relating to colour
G06V 10/60 - Extraction of image or video features relating to illumination properties, e.g. using a reflectance or lighting model
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 40/40 - Spoof detection, e.g. liveness detection
22.
Method for distinguishing a real three-dimensional object from a two-dimensional spoof of the real object
A method for distinguishing a real three-dimensional object from a two-dimensional spoof of the real three-dimensional object, the method comprising: obtaining, by an optical sensor of a mobile device, an image containing an object that is either the two-dimensional spoof or the real three-dimensional object; providing the image to a neural network; processing the image by the neural network by calculating: 1) a distance map representative of the distance of pixels to the optical sensor, the pixels constituting at least a portion of the object within the image, or 2) a reflection pattern representative of light reflection associated with pixels constituting at least a portion of the object within the image; comparing the distance map or the reflection pattern with a learned distance map or a learned reflection pattern; and obtaining as a final output a determination the image contains either the two-dimensional spoof or the real three-dimensional object.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
A method includes obtaining, by a processing device from an optical sensor of a mobile device, an image of an object. The method further includes processing, by the processing device, the image to identify the object in the image. Processing the image includes calculating at least one of a distance map or a reflection pattern. Processing the image further includes comparing the calculated distance map or the calculated reflection pattern with a known distance map or a known reflection pattern to determine whether the image contains a spoof or a real object. The method further includes obtaining, by the processing device from the image, data including a biometric characteristic of the user. The method further includes sending, by the processing device to a third party computing device, data including at least the biometric characteristic.
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
A method for identifying a user using an image of an object of the user, the method comprising: obtaining, by an optical sensor of a mobile device, the image of the object, wherein the object comprises a biometric characteristic of the user; providing the image to a neural network; processing the image by the neural network to identify-a position of the object and the object in the image; extracting, from the identified object, the biometric characteristic; storing the biometric characteristic in a storage device; and providing at least the biometric characteristic as input to an identification means to determine whether the biometric characteristic identifies the user.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 40/40 - Spoof detection, e.g. liveness detection
H04N 23/56 - Cameras or camera modules comprising electronic image sensorsControl thereof provided with illuminating means
25.
Method for verifying the identity of a user by identifying an object within an image that has a biometric characteristic of the user and separating a portion of the image comprising the biometric characteristic from other portions of the image
A method includes obtaining, by a processing device from an optical sensor of a mobile device, an image of an object; processing, by the processing device, the image using a neural network, wherein processing the image includes distinguishing, using the neural network, a first portion of the image including a region of interest, ROI, from a second portion of the image; after processing the image, extracting, by the processing device, a biometric characteristic of the object from the ROI; and processing, by the processing device, the biometric characteristic of the object to determine whether the biometric characteristic of the object identifies a user.
Method for verifying the identity of a user by identifying an object within an image that has a biometric characteristic of the user and mobile device for executing the method
A method includes obtaining, by a processing device from an optical sensor of a mobile device, an image, processing, by the processing device, the image by using a neural network to identify a position of an object in the image and the object in the image, thereby obtaining an identified object, after processing the image, extracting, by the processing device from the identified object, a biometric characteristic, and providing, by the processing device, at least the biometric characteristic as input to determine whether the biometric characteristic identifies a user.
A computer-implemented method for identifying a user, the method using a computing device comprising an illumination source that, when activated, emits visible light, the method comprising taking two images of a scene potentially comprising a living body part carrying a biometric characteristic, wherein a first image is taken without the illumination source being activated and the second image is taken with the illumination source being activated, transferring the first image and the second image to a neural network and processing, by the neural network the first image and the second image, wherein the processing comprises comparing the first image and the second image, thereby determining whether the first image and the second image are images of a living body part, the method further comprising, if it is determined that the first image and the second image are images of a living body part, performing an identification algorithm to find a biometric characteristic for identifying the user and, if it is determined that the first image and the second image are not images of a living body part, not performing the identification algorithm.
A method for distinguishing a real three-dimensional object from a two-dimensional spoof of the real object, the method comprising: obtaining, by an optical sensor of a mobile device, an image containing either the spoof or the real object; providing the image to a neural network; processing the image by the neural network by: calculating at least one of: 1) a distance map representative of the distance of a plurality of pixels to the optical sensor; or 2) a reflection pattern representative of light reflection associated with a plurality of pixels constituting at least a portion of the object within the image; and comparing at least one of the calculated distance map or the calculated reflection pattern with a learned distance map or a learned reflection pattern, to determine that the image contains either the spoof or the real object.
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
A method for obtaining data from an image of an object of a user that has a biometric characteristic of the user, like a fingerprint or a set of fingerprints of fingertips, a palm of the hand of the user, a face of the user, an eye of the user, a bottom of a foot of the user, the method comprising: on a mobile device, performing the following steps: obtaining, by an optical sensor of the mobile device, the image of the object wherein the image contains either the spoof or the real object; processing, in an identification-step, the image, thereby identifying both, the position of the object and the object in the image; wherein processing further comprises a liveliness-detection step, comprising calculating at least one of: a distance map representative of a distance of a plurality of pixels to the optical sensor, the pixels constituting at least a portion of the object within the image; a reflection pattern representative of light
A method for obtaining data from an image of an object of a user that has a biometric characteristic of the user, like a fingerprint or a set of fingerprints of fingertips, a palm of the hand of the user, a face of the user, an eye of the user, a bottom of a foot of the user, the method comprising: on a mobile device, performing the following steps: obtaining, by an optical sensor of the mobile device, the image of the object wherein the image contains either the spoof or the real object; processing, in an identification-step, the image, thereby identifying both, the position of the object and the object in the image; wherein processing further comprises a liveliness-detection step, comprising calculating at least one of: a distance map representative of a distance of a plurality of pixels to the optical sensor, the pixels constituting at least a portion of the object within the image; a reflection pattern representative of light reflection associated with a plurality of pixels constituting at least a portion of the object within the image; and wherein processing further comprises a comparison-step comprising comparing at least one of the calculated distance map or the calculated reflection pattern with a known distance map or a known reflection pattern, thereby determining, based on an outcome of the comparison, that the image contains either the spoof or the real object; obtaining, from the image, after the processing, data comprising at least the biometric characteristic and optionally storing the data in a storage device; sending, to a third party computing device, data comprising at least the biometric characteristic.
A method for identifying a user using an image of an object of the user that has a biometric characteristic of the user, like a fingerprint or a set of fingerprints of fingertips, the method comprising: obtaining, by an optical sensor of a mobile device, the image of the object; providing the image to a neural network; processing the image by the neural network, thereby identifying both, the position of the object and the object in the image; extracting, from the identified object, the biometric characteristic; storing the biometric characteristic in a storage device and/or providing at least the biometric characteristic as input to an identification means, comprising processing the input in order to determine whether the biometric characteristic identifies the user.
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 40/10 - Human or animal bodies, e.g. vehicle occupants or pedestriansBody parts, e.g. hands
32.
METHOD FOR VERIFYING THE IDENTITY OF A USER BY IDENTIFYING AN OBJECT WITHIN AN IMAGE THAT HAS A BIOMETRIC CHARACTERISTIC OF THE USER AND SEPARATING A PORTION OF THE IMAGE COMPRISING THE BIOMETRIC CHARACTERISTIC FROM OTHER PORTIONS OF THE IMAGE
A method for identifying a user using an image of an object of the user that has a biometric characteristic of the user, like a fingerprint or a set of fingerprints of fingertips, the method comprising: obtaining, by an optical sensor of a mobile device, the image of the object; providing the image or a part of the image to a neural network; processing the image or the part of the image by the neural network, comprising distinguishing, by the neural network, a portion of the image or the part of the image comprising the region of interest, ROI, from another portion of the image; extracting, from the image or the part of the image, the ROI; storing the portion comprising the ROI in a storage device and/or providing the portion comprising the ROI as input to an identification means, comprising extracting the biometric characteristic of the ROI and processing the extracted biometric characteristic in order to determine whether the extracted biometric characteristic identifies the user.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
33.
METHOD FOR VERIFYING THE IDENTITY OF A USER BY IDENTIFYING AN OBJECT WITHIN AN IMAGE THAT HAS A BIOMETRIC CHARACTERISTIC OF THE USER AND MOBILE DEVICE FOR EXECUTING THE METHOD
A method for identifying a user using an image of an object of the user that has a biometric characteristic of the user, wherein the object is one of a palm of the hand of the user, a face of the user, an eye of the user, a bottom of a foot of the user, the method comprising: obtaining, by an optical sensor of a mobile device, the image of the object; providing the image to a neural network; processing the image by the neural network, thereby identifying both, the position of the object and the object in the image; extracting, from the identified object, the biometric characteristic; storing the biometric characteristic in a storage device and/or providing at least the biometric characteristic as input to an identification means, comprising processing the input in order to determine whether the biometric characteristic identifies the user.
A method for distinguishing a real three-dimensional object, like a finger of a hand, from a two- dimensional spoof of the real object, the method comprising: obtaining, by an optical sensor of a mobile device, an image, wherein the image contains either the spoof or the real object; providing the image to a neural network; processing the image by the neural network; wherein processing comprises calculating at least one of: a distance map representative of the distance of a plurality of pixels to the optical sensor, the pixels constituting at least a portion of the object within the image; a reflection pattern representative of light reflection associated with a plurality of pixels constituting at least a portion of the object within the image; and wherein processing further comprises comparing at least one of the calculated distance map or the calculated reflection pattern with a learned distance map or a learned reflection pattern, thereby determining, based on an outcome of the comparison, that the image contains either the spoof or the real object.
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
A method for distinguishing a real three-dimensional object, like a finger of a hand, from a two- dimensional spoof of the real object, the method comprising: obtaining, by an optical sensor of a mobile device, an image, wherein the image contains either the spoof or the real object; providing the image to a neural network; processing the image by the neural network; wherein processing comprises calculating at least one of: a distance map representative of the distance of a plurality of pixels to the optical sensor, the pixels constituting at least a portion of the object within the image; a reflection pattern representative of light reflection associated with a plurality of pixels constituting at least a portion of the object within the image; and wherein processing further comprises comparing at least one of the calculated distance map or the calculated reflection pattern with a learned distance map or a learned reflection pattern, thereby determining, based on an outcome of the comparison, that the image contains either the spoof or the real object.
A method for identifying a user using an image of an object of the user that has a biometric characteristic of the user, like a fingerprint or a set of fingerprints of fingertips, the method comprising: obtaining, by an optical sensor of a mobile device, the image of the object; providing the image to a neural network; processing the image by the neural network, thereby identifying both, the position of the object and the object in the image; extracting, from the identified object, the biometric characteristic; storing the biometric characteristic in a storage device and/or providing at least the biometric characteristic as input to an identification means, comprising processing the input in order to determine whether the biometric characteristic identifies the user.
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
A method for identifying a user using an image of an object of the user that has a biometric characteristic of the user, like a fingerprint or a set of fingerprints of fingertips, the method comprising: obtaining, by an optical sensor of a mobile device, the image of the object; providing the image to a neural network; processing the image by the neural network, thereby identifying both, the position of the object and the object in the image; extracting, from the identified object, the biometric characteristic; storing the biometric characteristic in a storage device and/or providing at least the biometric characteristic as input to an identification means, comprising processing the input in order to determine whether the biometric characteristic identifies the user.
A method for identifying a user using an image of an object of the user that has a biometric characteristic of the user, like a fingerprint or a set of fingerprints of fingertips, the method comprising: obtaining, by an optical sensor of a mobile device, the image of the object; providing the image to a neural network; processing the image by the neural network, thereby identifying both, the position of the object and the object in the image; extracting, from the identified object, the biometric characteristic; storing the biometric characteristic in a storage device and/or providing at least the biometric characteristic as input to an identification means, comprising processing the input in order to determine whether the biometric characteristic identifies the user.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Computer programming services, namely, development and implementation of authentication software and hardware systems for use in connection with secure servers and mobile device technology to validate personal identifications using biometric features stored on a computer network or handheld device; Computer programming services, namely, design and development of computer systems used for the identification and authentication of the person; technical assistance, namely, providing technical advice for the implementation of systems for identification and the authentication of persons; design, development and updating of mobile application software, computer programs and computer software for capturing and interpreting fingerprints, palm prints, features of the iris, veins, the voice, baby feet prints, facial features or other biometric features in the field of identification and authentication of persons; Consulting in the field of user authentication and security system design
