A Novel Multi-Layer Level Set Method for Image Segmentation
In this paper, a new multi-layer level set method is proposed for multi-phase image segmentation. The proposed method is based on the conception of image layer and improved numerical solution of bimodal Chan-Vese model. One level set function is employed for curve evolution with a hierarchical form in sequential image layers. In addition, new initialization method and more efficient computational method for signed distance function are introduced. Moreover, the evolving curve can automatically stop on true boundaries in single image layer according to a termination criterion which is based on the length change of evolving curve. Specially, an adaptive improvement scheme is designed to speed up curve evolution process in a queue of sequential image layers, and the detection of background image layer is used to confirm the termination of the whole multi-layer level set evolution procedure. Finally, numerical experiments on some synthetic and real images have demonstrated the efficiency and robustness of our method. And the comparisons with multi-phase Chan-Vese method also show that our method has a less time-consuming computation and much faster convergence.
multi-layer level set segmentation image layer curve evolution termination criterion