METHOD FOR CLASSIFYING IMAGES BY NEURONAL NETWORKS AND A CLASSIFIER OF PRE-LEARNED IMAGES, CORRESPONDING DEVICE AND COMPUTER PROGRAM

摘要

The invention relates to a method for classifying at least one input digital image (10) according to at least two categories of predetermined images. The inventive method consists in allocating at least one associated signature to an element belonging to a group comprising the point of interest of said image and the area of interest (11) of said input image, in assigning to each signature a characteristic dimension c vector obtained by applying the matrix (13) of c neuronal networks (14<SUB>l</SUB>, ..., 14<SUB>c</SUB>) to at least one dimension, wherein each neuronal network (14<SUB>l</SUB>, ..., 14<SUB>c</SUB>) is pre-configured during a learning phase and is associated to one image category and said characteristic vector is representative of a histogram of responses delivered by the neuronal network (14<SUB>l</SUB>, ..., 14<SUB>c</SUB>), in classifying said image (10) according to said categories with the aid of the classifier pre-configured during the learning stage according to the characteristic dimension c vector.