Name
Abstract | ||
|---|---|---|
A new general image segmentation system is presented, based on the calculation of a tree representation of the original image in which image regions are assigned to tree nodes, followed by a correspondence process with a model tree, which embeds the a priori knowledge about the images. For this correspondence, an original algorithm is proposed, which performs the minimization of an error function that quantifies the difference between the input image tree and the model tree. We also present a new algorithm for automatically calculating the model tree from a set of manually segmented images. Results on synthetic and MR brain images are presented. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1016/j.patcog.2003.07.009 | Pattern Recognition |
Keywords | Field | DocType |
Computer vision,Image segmentation,Hierarchical analysis,Mathematical morphology,Watershed,Tree representation,Medical imaging | Error function,Scale-space segmentation,Pattern recognition,Computer science,Mathematical morphology,A priori and a posteriori,Decision tree model,Image segmentation,Minification,Artificial intelligence,Machine learning,Minimum spanning tree-based segmentation | Journal |
Volume | Issue | ISSN |
37 | 1 | 0031-3203 |
Citations | PageRank | References |
4 | 0.47 | 30 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vicente Grau | 1 | 244 | 15.68 |
| Mariano Alcañiz Raya | 2 | 509 | 45.46 |
| Carlos Monserrat | 3 | 120 | 12.34 |
| M. Carmen Juan | 4 | 133 | 16.83 |
| Luis Martı́-Bonmatı́ | 5 | 4 | 0.47 |