A MACHINE LEARNING APPROACH FOR ACQUIRING DESCRIPTIVE CLASSIFICATION RULES OF SHAPE CONTOURS

We devise a method to generate descriptive classification rules of sha pe contours by using inductive learning. The classification rules are represented in the form of logic programs. We first transform input ob jects from pixel representation into predicate representation. The tra nsformation consists of preprocessing, feature extraction and symbolic transformation. We then use FOIL which is an indictive logic programm ing system to produce classification rules. Experiments on two sets of data were performed to justify our proposed method. Copyright (C) 199 7 pattern Recognition Society.