Abstract
Active contour and surface models, also known as deformable models, constitute a class of powerful segmentation techniques. Geometric deformable models implemented via level-set methods have advantages over parametric ones due to their intrinsic behavior, parameterization independence, and ease of implementation. However, a long claimed advantage of geometric deformable models-the ability to automatically handle topology changes-turns out to be a liability in applications where the objects to be segmented have a known topology that must be preserved. In this paper, we present a geometric deformable model that preserves topology using the simple point concept from digital topology This algorithm maintains the other advantages of standard geometric deformable models including sub-pixel accuracy and production of nonintersecting curves (or surfaces). Several experiments on simulated and real data are provided to demonstrate the performance of the proposed algorithm.
Original language | English (US) |
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Pages (from-to) | II765-II770 |
Journal | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
Volume | 2 |
State | Published - Dec 1 2001 |
Event | 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Kauai, HI, United States Duration: Dec 8 2001 → Dec 14 2001 |
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition