Image processing method for an identity document

A method for processing an image of a candidate identity document that comprises a page of data comprising a plurality of glyphs of a plurality of fonts, the method comprising a step of:

• acquiring a digital image of the page of data of the candidate identity document, each digital image being able furthermore to be extracted from a video stream recorded by said communicating object;
• characterized in that it further comprises steps of:
• assigning a class or a super-class to the candidate identity document via automatic classification of said digital image by a machine-learning algorithm trained on a set of reference images in a training phase during which each glyph is learnt individually for each font of each class,
• extracting a set of glyphs from the digital image and storing each glyph in the form of an individual image,
• processing each individual image in order to obtain a set of at least one intermediate image, each intermediate image corresponding to one individual glyph, each intermediate image being obtained via at least one step comprising processing each individual image with a recurrent neural network, wherein processing each individual image with the recurrent neural network includes obtaining as output, by cosegmentation, a set of intermediate images that each correspond to a segmentation of the glyph obtained at the end of a glyph-recognition step,
• discriminating between each glyph of each font of said intermediate image using a respective discriminator neural network, each individual glyph being considered to be probably authentic when it corresponds to a glyph learnt in a training phase, and
• generating an output signal by combining the output signals of the discriminator neural networks, the value of which is representative of the probability that the candidate identity document is an authentic identity document or a fake.