Multidimensional co-occurrence matrices for object recognition and matching

A novel method is proposed for object recognition and matching. It is based on the automatic search of features that characterize a certain object class using a training set consisting of both positive and negative examples. Special multidimensional co-occurrence matrices are used for the description and representation of some basic image structures. The features are extracted from the elements of this matrix and express quantitatively the relative abundance of some elementary structures, i.e., they are quotients of certain elements of the matrix. Only features which discriminate the classes clearly are used. The method is demonstrated in numerous applications, falling under the general problems of texture recognition, texture defect detection, and shape recognition. (C) 1996 Academic Press, Inc.