1. A method for sorting articles bearing graphical patterns to be referred to as input patterns, the method comprising the steps of: converting each input pattern to a pixel array, storing the pixel array in a digital pattern-recognition machine, classifying each input pattern, and performing a prescribed physical manipulation of each article in response to the result of classifying the pattern borne by that article; wherein the machine comprises a storage device and a library of prototype patterns stored within the storage device, each prototype pattern belongs to one of a multiplicity of known classes, and each prototype pattern is labeled with its respective class, and the classifying step comprises, in said machine: a) for each input pattern, retrieving each of the prototype patterns from the storage device and evaluating a distance function d.sub.1 between the input pattern and each of the prototype patterns, wherein d.sub.1 is the first of a plurality of distance functions d.sub.i, i=1,. .. , M, M a positive integer at least 2; b) responsive to (a), keeping the K.sub.1 closest prototype patterns and eliminating from consideration the rest of the prototype patterns, wherein K.sub.1 is a positive integer less than the total number of prototype patterns in the library; c) evaluating at least one further distance function d.sub.j between the input pattern and at least some of the K.sub.1 closest prototype patterns, wherein j is a positive integer at least 2 and at most M; d) responsive to the evaluation of each further distance function d.sub.i, i=2,. .. M, keeping the K.sub.i closest prototype patterns and eliminating from consideration the rest of the prototype patterns, wherein K.sub.i is a positive integer less than K.sub.i-1 ; and e) choosing the best class, according to an appropriate decision procedure, from the classes represented in a population of prototype patterns that is limited in response to the evaluation of the last distance function d.sub.M, wherein: f) each evaluation of step (c) is carded out between the input pattern and the K.sub.j-1 closest prototype patterns that were kept in response to the evaluation of the last preceding distance function d.sub.j-1 ; g) at least one of the further distance functions d.sub.i, i at least 2, such distance to be referred to as a tangent distance of complexity L.sub.i, is evaluated with reference to a set of image transformations that are selected to leave the respective classes of the prototype patterns invariant, and such evaluation comprises the further steps of: generating L.sub.i tangent vectors from a subset of said image transformations, wherein L.sub.i is at least 1, and the L.sub.i tangent vectors define an input hyperplane containing the input pattern; and evaluating a Euclidean distance with respect to a transformed pattern lying on the input hyperplane.