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Local Self-Adaptive Chan-Vese Image Segmentation Model

SONG Jinping;LUO Shousheng;PANG Zhifeng;ZHU Ya'nan;School of Mathematics and Statistics,Henan University;  
The classic Chan-Vese(CV)model does not include the information of edges.So it only gives some unsuitable segmentation results when backgrounds and foregrounds have complex structures.In order to overcome these faults,we improved the classic CV model by employing the local information of image and computing mean values of backgrounds and foregrounds by the K-means method.Following the framework of the primal dual scheme,we gave the equivalent form of the proposed model and then used semi-implicit gradient method to solve it.Experiments on synthetic and natural images illustrate that the proposed mode is more effective for various kinds of images with complex features.
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