Abstract: A method for extracting a signature of a fingerprint shown on a source image is described. For this purpose, the source image is transformed into the frequency domain. One or more ridge frequencies are next determined by means of a convolutional neural network applied to said transformed image, n being an integer greater than or equal to 1. The source image is normalized in response to said n ridge frequencies determined. One or more signatures of said fingerprint are finally extracted from said n normalized images.

Abstract: The present invention relates to a method of segmenting an input image representing at least one biometric trait, by means of a convolutional neural network, CNN, the method being characterized in that it comprises the implementation, by data processing means (21) of a client (2), of steps of (b) generating, by means of a first subnetwork of said CNN, referred to as a specialization block, a confidence mask associated with a ridge orientation map of the at least one biometric trait represented by said input image, referred to as a RFM mask; said RFM mask being applied to at least the input image so as to obtain a focused input image; (c) segmenting, by means of a second subnetwork of said CNN, referred to as a segmentation block, the focused input image.

Abstract: A method for extracting a signature of a fingerprint shown on a source image is described. For this purpose, the source image is transformed into the frequency domain. One or more ridge frequencies are next determined by means of a convolutional neural network applied to said transformed image, n being an integer greater than or equal to 1. The source image is normalized in response to said n ridge frequencies determined. One or more signatures of said fingerprint are finally extracted from said n normalized images.

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 (2), of steps of: (a) Binarization of said input image by means of a convolutional neural network, CNN, in such a way as to generate an image called binary; (b) Processing said binary image so as to extract said features of interest from the fingerprint represented by said input image.

Abstract: The present invention relates to a method of segmenting an input image representing at least one biometric trait, by means of a convolutional neural network, CNN, the method being characterized in that it comprises the implementation, by data processing means (21) of a client (2), of steps of: (b) generating, by means of a first subnetwork of said CNN, referred to as a specialization block, a confidence mask associated with a ridge orientation map of the at least one biometric trait represented by said input image, referred to as a RFM mask; said RFM mask being applied to at least the input image so as to obtain a focused input image; (c) segmenting, by means of a second subnetwork of said CNN, referred to as a segmentation block, the focused input image

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 (2), of steps of: (a) Binarization of said input image by means of a convolutional neural network, CNN, in such a way as to generate an image called binary; (b) Processing said binary image so as to extract said features of interest from the fingerprint represented by said input image.