EFFICIENT SHAPE-MATCHING THROUGH MODEL-BASED SHAPE-RECOGNITION

An efficient shape matching method for shape recognition is proposed. It first uses a polygonal approximation technique to describe a shape. Then, using the proposed matching algorithm (based on some polygonal attributes), the dissimilarity measure between an input shape and its reference model is obtained. The input shape can be classified into th e class (model) which has the minimum dissimilarity measure with it. I n addition, it can provide the best matching orientation information f or the input shape and its model, so that further applications, such a s automated inspection and assembly, can be effectively performed. The proposed shape matching is invariant to translation, rotation, and sc ale changes of a shape. Experiments using noisy shapes and real images are performed, and the recognition results demonstrate that the propo sed method is very effective.