Skeletonization of binary digital patterns using a fast Euclidean distance transformation

Abstract

In this paper we present a new thinning algorithm based on distance transformation. Because the choice of a distance measure will influence the result of skeletonization, we introduce an approach to Euclidean distance transformation that achieves a better accuracy than D4 , D8 , or octagonal distance transformation. We have developed a fast method to compute the Euclidean distance transformation. Using this technique, we can extract a reliable skeleton efficiently to represent a binary pattern. Our method works well on real images and compares favorably with other methods.