Name
Abstract | ||
|---|---|---|
This paper presents a new skeletonization method based on a novel concept — discrete local symmetry. A skeleton obtained from discrete local symmetries approaches the skeleton of the underlying continuous shape if the sampling is dense enough. Discrete local symmetries can be obtained by computing the constrained Delaunay triangulation of the underlying image. Internal triangles of a triangulation are divided into isolated triangles, end triangles, normal triangles and junction triangles. A discrete local symmetry corresponds to an isolated triangle, or an end triangle, or a normal triangle. Several measures are taken to remove skeletonization artifacts and suppress image noise. The proposed method can produce correct centre lines and junctions. It is efficient and robust against noise. The method is suitable for skeletonizing high-resolution images. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1016/S0031-3203(00)00131-X | Pattern Recognition |
Keywords | Field | DocType |
Skeletonization,Thinning,Constrained Delaunay triangulation,Binary image processing | Topology,Image noise,Triangulation (social science),Skeletonization,Sampling (statistics),Constrained Delaunay triangulation,Mathematics,Homogeneous space,Local symmetry,Delaunay triangulation | Journal |
Volume | Issue | ISSN |
34 | 10 | 0031-3203 |
Citations | PageRank | References |
12 | 0.67 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ju Jia Zou | 1 | 198 | 20.00 |
| Hung-Hsin Chang | 2 | 117 | 8.27 |
| Hong Yan | 3 | 3628 | 335.04 |