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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mao Wang Evans, J. Hassebrook, L. Knapp, C. |
| Copyright Year | 1992 |
| Abstract | Energy-minimizing active contour models or snakes can be used in many applications such as edge detection, motion tracking, image matching, computer vision, and three-dimensional (3-D) reconstruction. We present a novel snake that is superior both in accuracy and convergence speed over previous snake algorithms. High performance is achieved by using spline representation and dividing the energy-minimization process into multiple stages. The first stage is designed to optimize the convergence speed in order to allow the snake to quickly approach the minimum-energy state. The second stage is devoted to snake refinement and to local minimization of energy, thereby driving the snake to a quasiminimum-energy state. The third stage uses the Bellman (1957) optimality principle to fine-tune the snake to the global minimum-energy state. This three-stage scheme is optimized for both accuracy and speed. |
| Sponsorship | IEEE Signal Processing Society |
| Starting Page | 1586 |
| Ending Page | 1591 |
| Page Count | 6 |
| File Size | 1076814 |
| File Format | |
| ISSN | 10577149 |
| Volume Number | 5 |
| Issue Number | 11 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1996-11-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Active contours Convergence Application software Image edge detection Tracking Image matching Computer vision Image reconstruction Spline Design optimization |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Graphics and Computer-Aided Design Software |
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