Skeletonization of ribbon-like shapes based on regularity and singularity analyses

A major problem with traditional skeletonization algorithms is that their results do not always conform to human perceptions since they often contain unwanted artifacts. This paper presents an indirect skeletonization method to reduce these artifacts. The method is based on analyzing regularities and singularities of shapes. A shape is first partitioned into a set of triangles using the constrained Delaunay triangulation technique. Then, regular and singular regions of the shape are identified from the partitioning. Finally, singular regions are stabilized to produce a better result. Experiments show that skeletons obtained from the proposed method closely resemble human perceptions of the underlying shapes.