Name
Abstract | ||
|---|---|---|
A simple and efficient curvilinear feature extraction algorithm is described. The algorithm is based on minimum spanning trees of edge points and closely related to Zahn's previous work on Gestalt clustering. Examples drawn from real world images are shown to demonstrate the capabilities and applicabilities of the algorithm. Stimulating interest and inducing application of the algorithm in the areas of computer vision and image understanding are among the major objectives of the paper. |
Year | DOI | Venue |
|---|---|---|
1984 | 10.1016/0734-189X(84)90221-4 | Computer Vision, Graphics, and Image Processing |
Keywords | Field | DocType |
feature extraction,minimum spanning tree | Computer vision,Feature extraction algorithm,Pattern recognition,Gestalt psychology,Image processing,Feature extraction,Artificial intelligence,Curvilinear coordinates,Spanning tree,Cluster analysis,Minimum spanning tree-based segmentation,Mathematics | Journal |
Volume | Issue | ISSN |
26 | 3 | 0734-189X |
Citations | PageRank | References |
4 | 0.62 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minsoo Suk | 1 | 184 | 28.95 |
| Oh-young Song | 2 | 271 | 26.40 |