1 ) A method for facilitating recognition of objects, taking account of uncertainties about a certain number p of parameters describing these objects, wherein a discriminant analysis technique is used to classify said objects into predetermined categories, characterized in that it comprises: forming a learning base comprising data obtained by measurements or observations relative to objects that have already been recognized and classified in predetermined categories, each one being defined by variables of known statistical characteristics; constructing, by reference to the learning base, a classification function by means of a discriminant analysis technique, allowing to distribute, among said categories, the various objects to be classified from measurements available for said parameters, this function being formed by determining probability intervals of belonging of the objects to the various categories by taking into account uncertainties about the parameters in form of intervals of variable width, and assigning each object to at least one of the predetermined categories, if possible, according to the extent of the probability intervals and to the overlap thereof