Abstract: A method for matching an image of a palm of an individual with at least one image from a plurality of reference palm images, which includes: creation of a reference base from the plurality of reference palm images comprising, for each reference palm image, a selection of at least one reference palm region and a coding into a reference regional biometric information item, determination of an individual palmary biometric information item from the image of the palm of the individual comprising a selection of at least one individual palm region and the coding thereof into individual regional biometric information item, for each image, comparison of each individual regional biometric information item with each reference regional biometric information item, and matching of the image of the palm of the individual with at least one image from the plurality of reference palm images, as a function of a result of the comparison.

Abstract: A method for generating an image of a palm based on a first partial image of a palm of the individual and on a second partial image of a palm including detecting first characteristic points in the first image and second characteristic points in the second image, generating a plurality of pairs of characteristic points by matching first characteristic points with second characteristic points, computing an overall geometric transformation associated with said matching, determining a local geometric transformation for each pair of points, and merging the first image with the second image as a function of the overall geometric transformation and of the local geometric transformations, in order to generate the palm image.

Abstract: A method for matching an image of a palm of an individual with at least one image from a plurality of reference palm images, which includes: creation of a reference base from the plurality of reference palm images comprising, for each reference palm image, a selection of at least one reference palm region and a coding into a reference regional biometric information item, determination of an individual palmary biometric information item from the image of the palm of the individual comprising a selection of at least one individual palm region and the coding thereof into individual regional biometric information item, for each image, comparison of each individual regional biometric information item with each reference regional biometric information item, and matching of the image of the palm of the individual with at least one image from the plurality of reference palm images, as a function of a result of the comparison.

Abstract: A method of detecting at least one element of interest visible on an input image, by means of a convolutional neural network, CNN, the method comprises the steps of: (a) extracting, by means of an ascending branch of a first subnetwork of said CNN of feature pyramid network, FPN, type, a plurality of initial feature maps (C1, C2, C3, C4, C5) representative of the input image at different scales, said FPN further comprising a descending branch and lateral connections between the ascending branch and the descending branch, at least one lateral connection comprising an attention module; (b) generating, by means of said descending branch of the FPN, a plurality of enriched feature maps (P2, P3, P4, P5) also representative of the input image at different scales, each enriched feature map (P2, P3, P4, P5) incorporating the information from the initial feature maps (C1, C2, C3, C4, C5) of smaller or equal scale; (d) detecting at least one element of interest visible on an input image, by means of a second subnetw

Abstract: A method for detecting at least one biometric trait visible in an input image, by means of a convolutional neural network, the method wherein it comprises the implementation, by data processing means of a client, of steps of: (a) Generating, by means of a feature extraction block of said CNN, a plurality of representation vectors each defining a candidate region of interest of said input image potentially containing a biometric trait, the representation vector of a candidate region of interest comprising at least one position value of the candidate region of interest, at least one size value of the candidate region of interest, an orientation value of the candidate region of interest, and an objectivity score of the candidate region of interest; (b) Selecting, by means of a filtering block of said CNN, at least one region of interest from said candidate regions based on the representation vectors thereof.

Abstract: A method for selecting an image of a fingerprint for identifying an individual is described. The method includes: acquiring a current image comprising a fingerprint and segmenting said fingerprint; determining a value representing a stability of said current image; determining a value representing the sharpness of said current image; determining a score, said score being a combination of said value representing a stability, of said value representing a sharpness and of a number of segmented fingerprints; and selecting said current image for identifying said individual in the case where said score is higher than a first threshold value, and otherwise storing said current image in memory as best image in the case where the score thereof is higher than a best score value, and repeating this method.

Abstract: A method for selecting an image of a fingerprint for identifying an individual is described. The method includes: acquiring a current image comprising a fingerprint and segmenting said fingerprint; determining a value representing a stability of said current image; determining a value representing the sharpness of said current image; determining a score, said score being a combination of said value representing a stability, of said value representing a sharpness and of a number of segmented fingerprints; and selecting said current image for identifying said individual in the case where said score is higher than a first threshold value, and otherwise storing said current image in memory as best image in the case where the score thereof is higher than a best score value, and repeating this method.

Abstract: The present invention relates to a method for extracting features of interest from a fingerprint represented by an input image, the method being characterized in that it comprises the implementation, by data processing means (21) of a client equipment (2), of steps of: (a) Estimation of at least one candidate angular deviation of an orientation of said input image with respect to a reference orientation, by means of a convolutional neural network, CNN; (b) Recalibration of said input image as a function of said estimated candidate angular deviation, so that the orientation of the recalibrated image matches said reference orientation; (c) Processing said recalibrated image so as to extract said features of interest from the fingerprint represented by said input image.

Abstract: A method for detecting at least one biometric trait visible in an input image, by means of a convolutional neural network, the method wherein it comprises the implementation, by data processing means of a client, of steps of: (a) Generating, by means of a feature extraction block of said CNN, a plurality of representation vectors each defining a candidate region of interest of said input image potentially containing a biometric trait, the representation vector of a candidate region of interest comprising at least one position value of the candidate region of interest, at least one size value of the candidate region of interest, an orientation value of the candidate region of interest, and an objectivity score of the candidate region of interest; (b) Selecting, by means of a filtering block of said CNN, at least one region of interest from said candidate regions based on the representation vectors thereof.

Abstract: A method of detecting at least one element of interest visible on an input image, by means of a convolutional neural network, CNN, the method comprises the steps of: (a) extracting, by means of an ascending branch of a first subnetwork of said CNN of feature pyramid network, FPN, type, a plurality of initial feature maps (C1, C2, C3, C4, C5) representative of the input image at different scales, said FPN further comprising a descending branch and lateral connections between the ascending branch and the descending branch, at least one lateral connection comprising an attention module; (b) generating, by means of said descending branch of the FPN, a plurality of enriched feature maps (P2, P3, P4, P5) also representative of the input image at different scales, each enriched feature map (P2, P3, P4, P5) incorporating the information from the initial feature maps (C1, C2, C3, C4, C5) of smaller or equal scale; (d) detecting at least one element of interest visible on an input image, by means of a second subnetw

Abstract: The present invention relates to a method for extracting features of interest from a fingerprint represented by an input image, the method being characterized in that it comprises the implementation, by data processing means (21) of a client equipment (2), of steps of: (a) Estimation of at least one candidate angular deviation of an orientation of said input image with respect to a reference orientation, by means of a convolutional neural network, CNN; (b) Recalibration of said input image as a function of said estimated candidate angular deviation, so that the orientation of the recalibrated image matches said reference orientation; (c) Processing said recalibrated image so as to extract said features of interest from the fingerprint represented by said input image.