The Perturbing And Iterating Classifier Algorithm
Greg A. Roberts · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1983
A classification algorithm called the Perturbing and Iterating Classifier (PIC) is presented. This algorithm is a heuristic classifier that determines the classification of a segment by examining the number of self-consistent perturbations that are necessary for a segment's descriptor vector to become very close to a model descriptor vector. Unlike many other classifiers, this algorithm does not rely on the initial closeness or similarity of descriptor vectors. The theory of PIC is initially explained, an application of PIC in two dimensional shape matching is given, and then the physical interpretation of the algorithm is presented. An example of how PIC can discriminate shape over a wide range is also presented.