Name
Abstract | ||
|---|---|---|
In this paper we propose a genetic and greedy algorithm combination for the optimization of the Topological Active Nets (TAN) model. This is a deformable model used for image segmentation that integrates features of region-based and edge-based segmentation techniques, being able to fit the edges of the objects and model their inner topology. The hybrid approach we propose can optimize the active nets through the minimization of the model energy functions and, moreover, it can provide some segmentation results unreachable by the GA method alone such as changes in the net topology. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-71618-1_23 | ICANNGA (1) |
Keywords | Field | DocType |
edge-based segmentation technique,active nets optimization,active net,genetic-greedy hybrid approach,deformable model,greedy algorithm combination,inner topology,topological active nets,ga method,model energy function,segmentation results unreachable,image segmentation,genetics,greedy algorithm | Topology,Mathematical optimization,Scale-space segmentation,Force field (chemistry),Segmentation,Computer science,Segmentation-based object categorization,Greedy algorithm,Image segmentation,Minification,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | Citations |
4431 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Santos | 1 | 97 | 14.77 |
| Óscar Ibáñez | 2 | 96 | 11.32 |
| Noelia Barreira | 3 | 17 | 6.10 |
| Manuel G. Penedo | 4 | 185 | 35.91 |