A New Local Segmentation Method Based on Binary Level Set and Morphological Operation

Local segmentation is the key work in image segmentation. Considering two existing problems, which are the instability of controlling narrow band and the low precision in local segmentation, this paper proposes a new Binary and Selective Morphological Operation Regularized Level Set (BSMORLS) method. Since the traditional signed distance function is replaced by binary level set in the method, and the binary property of the level set is maintained strictly in curve evolution, the stability of narrow band and the precision of one pixel width can be guaranteed. Optional morphological operator is utilized to increase the flexibility of curve smoothing, and sparse field is adopted to reduce the computational complexity. Experiments on some synthetic and medical images indicate the efficiency and robustness of the proposed local segmentation method.