Abstract
Active contour model, also called snake, adapts to edges in an image. A snake is defined as an energy minimizing spline - the snake's energy depends on its shape and location within the image. Problems associated with initialization and poor convergence to boundary concavities, however, have limited its utility. In this paper, we present a new external force field, named gravitation force field, for the snake model. We associate this force field with edge preserving smoothing to drive the snake for solving the problems. Our gravitation force field uses gradient values as particles to construct force field in the whole image. This force field will attract the active contour toward the edge boundary. The locations of the initial contour are very flexible, such that they can be very far away from the objects and can be inside, outside, or the mixture. The improved snake can converge toward the object boundary in a fast pace.
Original language | English (US) |
---|---|
Pages (from-to) | 197-209 |
Number of pages | 13 |
Journal | International Journal of Pattern Recognition and Artificial Intelligence |
Volume | 18 |
Issue number | 2 |
DOIs | |
State | Published - Mar 2004 |
All Science Journal Classification (ASJC) codes
- Software
- Computer Vision and Pattern Recognition
- Artificial Intelligence
Keywords
- Active contour model
- Edge detection
- Edge preserving smoothing
- Gradient vector flow
- Image processing
- Snake