Skeleton location and evaluation based on local digital width in ribbon-like images

In this paper, we present a model for characterising the skeleton of line images. For comparative purposes, we base our theoretical model formulation on the ideal ribbon-like non-branching image. The model developed is first contrasted with Blum's model and the wave propagation model. The aim of the proposed model is to avoid spurious branches of the skeleton and to refine the definition of centrality at sharp angles of the input image. The underlying concept of this model is based on a new definition for local width, derived from the idea of minimum base segment. This is first introduced in the real space, and then discretised for characterising a discrete skeleton. A graph theoretic approach, which is model-independent, is introduced for locating skeletons of non-branching images. By applying the graph-theoretic algorithm, performance evaluation of the proposed model is contrasted with Blum's original model by investigating reconstruction performance of the output skeletons. (C) 1997 Pattern Recognition Society. Published by Elsevier Science Ltd.