A novel boundary approach for shape representation and classification

Abstract

Shape is an important visual feature and it is one of the basic features used to describe image content. However, shape representation and classification is a difficult task. This paper presents a new boundary based shape representation and classification algorithm based on mathematical morphology. It consists of two steps. Firstly, an input shape is represented by using Hit Miss Transform (HMT) into a set of structuring elements. Secondly, the extracted shape of the image is classified based on shape features. Experimental results show that the integration of these strategies significantly improves shape database.