Abstract
In this paper, we propose a new level set-based partial differential equation (PDE) for the purpose of bimodal segmentation. The PDE is derived from an energy functional which is a modified version of the fitting term of the Chan-Vese model. The energy functional is designed to obtain a stationary global minimum, i.e., the level set function which evolves by the Euler-Lagrange equation of the energy functional has a unique convergence state. The existence of a global minimum makes the algorithm invariant to the initialization of the level set function, whereas the existence of a convergence state makes it possible to set a termination criterion on the algorithm. Furthermore, since the level set function converges to one of the two fixed values which are determined by the amount of the shifting of the Heaviside functions, an initialization of the level set function close to those values can result in a fast convergence.
| Original language | English |
|---|---|
| Pages (from-to) | 2843-2852 |
| Number of pages | 10 |
| Journal | IEEE Transactions on Image Processing |
| Volume | 15 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - 2006 Sept |
Bibliographical note
Funding Information:Manuscript received July 11, 2006; revised December 23, 2006. This work was supported by the Korea Science and Engineering Foundation under Grant R11-2002-103. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Vicent Caselles. The authors are with Yonsei University, Department of Mathematics, Seoul, Korea (e-mail: [email protected]; [email protected]). Digital Object Identifier 10.1109/TIP.2006.877308
All Science Journal Classification (ASJC) codes
- Software
- Computer Graphics and Computer-Aided Design