MORPHOLOGICAL SKELETON REPRESENTATION AND CODING OF BINARY IMAGES

The results are presented of a study on the use of morphological set operations to represent and encode a discrete binary image by parts of its skeleton, which is a thinned version of the image containing complete information about its shape and size. Using morphological erosions and openings, a finite image can be uniquely decomposed into a finite number of skeleton subsets, and then the image can be exactly reconstructed by dilating these skeleton subsets. The morphological skeleton approach is shown to unify many previous approaches to skeletonization, and some of its theoretical properties are investigated. Fast algorithms that reduce the original quadratic complexity to linear are developed for skeleton decomposition and reconstruction. Partial reconstructions of the image are quantified through the omission of subsets of skeleton points. The concepts of a globally and locally minimal skeleton are introduced, and fast algorithms are developed for obtaining minimal skeletons.