A Systematic Evaluation of Skeletonization Algorithms

As a result of its central role in the preprocessing of image patterns, or because of its intrinsic appeal, the design of skeletonization algorithms has been a very active research area. However, few attempts have been made to evaluate the performance of different skeletonization algorithms. This paper presents the results of experiments to evaluate the performance of 20 skeletonization algorithms previously published in the literature. These algorithms have been implemented on the SUN 3/60 workstation in C and tested with a large variety of character patterns. A systematic comparison of these algorithms has been made based on the following criteria: reconstructibility, computation speed, similarity to the reference skeleton, quality of the skeleton, connectivity after skeletonization, and the degree of parallelism.