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An Improved C-V Image Segmentation Method Based on Level Set Model

Image segmentation method based on Chan-Vese level set model has wide potential application. However its complex computing restricts its application. In order to improve the speed of image segmentation, this paper presents a new level set initialization method on Chan-Vese level set model. After a simple iterative, we can separate out the outline of objects. Experiments show that the method is simple and efficient, with good separation effects.