| Paper: | MA-P2.4 |
| Session: | Active-Contour, Level-Set, and Cluster-Based Segmentation Methods |
| Time: | Monday, September 17, 09:50 - 12:30 |
| Presentation: |
Poster
|
| Title: |
CONTENT ADAPTIVE HETEROGENEOUS SNAKES |
| Authors: |
Andras Hajdu; University of Debrecen | | |
| | Ioannis Pitas; University of Thessaloniki | | |
| Abstract: |
Active contour (snake) approaches have been proved to be efficient tools to extract object boundary precisely. One drawback of these methods is that state-of-the-art snake algorithms are usually computationally expensive. To overcome this difficulty, one approach is to reduce spatial resolution to make snake iteration faster. The disadvantage of this method is that the reduction of resolution ignores image content which may lead to losing useful image data. In this paper we propose a snake iteration method on quadtree representations derived from the image. In this way we can reduce resolution in a special and adaptive way. Once the iteration is finished on the sparse quadtree grid, final adjustments can be made by performing pixelwise snake iteration steps. |
