1. A method of banknote classification wherein a banknote is scanned to obtain its two-dimensional image consisting of pixels, the image is separated into areas in compliance with a specified partitioning scheme; a function for each area is computed with a definite algorithm in such a way that its value depends on the values of the pixels within the area; a banknote feature vector is composed of calculated values by using the function values calculated for each area as coordinates in the feature space, and a conclusion is drawn about the banknote possible membership in at least one banknote class known beforehand; the conclusion is drawn on the base of a distance between the banknote and the class in the feature space; the class is represented by a class centroid vector known beforehand and by an allowable deviation vector known beforehand and by a maximum allowable distance to that class; to compute the distance between the banknote and the class known beforehand, for each separate coordinate in the feature space a module of difference is found between the value of this coordinate of the banknote feature vector and that of the centroid vector, followed by subtraction of the value of the allowable deviation vector for the given coordinate from the module; of all obtained values only positive ones are summed for the distance calculation, and a conclusion is drawn by comparing the distance between the banknote and the given class with the maximum allowable distance to the given class so that if the resulting distance does not exceed the maximum allowable distance to the given class, a conclusion is drawn about a possible membership of the banknote in the given class, but if the distance found exceeds the maximum allowable distance to the given class, a conclusion is drawn that the banknote does not belong to the given class.