Morphological decomposition of 2-D binary shapes into conditionally maximal convex polygons

Abstract

Mathematical morphology is an approach to image analysis based on the geometric concept of shape and size. Naturally, it provides a very effective tool for shape analysis. In this paper we present a morphological shape segmentation algorithm that decomposes a 2-D (two-dimensional) binary shape into a collection of restricted convex polygons. We use simple morphological operations to extract shape information from different skeleton subsets to form a group of conditionally maximal convex polygonal shape components. Then a set of more meaningful and natural convex polygonal components are constructed from these maximal components. The resulting algorithm is very simple and the decomposition is always unique. The components produced have well-defined mathematical characterizations and they seem to be in good agreement with the nature structures of the given shapes. The shape segments produced can be used to construct structural shape description and for other shape analysis purposes.