Multi-Region Texture Image Segmentation Based on Constrained Level-Set Evolution Functions
A multi-region texture image segmentation method based on level-set is proposed in this paper. In the proposed method, each region is represented by one level-set function and these functions evolve simultaneously based on a constraint. The constraint is used to keep a balance between competing regions and to guarantee disjoint and non-overlapping regions. To speed up the curve evolution functions and to prevent them from getting stuck at undesired points, a region competition factor is applied. Edge- and edgeless-based active contours are applied in the proposed method to improve the robustness and the accuracy of the segmentation. The proposed multi-region texture segmentation method is fast and less sensitive to initializations as compared with existing techniques. Different segmentation examples are presented to illustrate the performance of the proposed method.