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《Journal of Computer Research and Development》 2004-01
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A New Level Set Method of Piece-Wise Smooth Mumford-Shah Model for Image Segmentation

XIAO Liang 1, WU Hui-Zhong 1, WEI Zhi-Hui 1,2, and TANG Shu-Chun 3 1(Department of Computer Science and Technology, Nanjing University of Science & Technology, Nanjing 210094) 2(Graduate School, Nanjing University of Science & Technology, Nanjing 210094) 3(Fourth Institute of the Second Artillerist, Chinese People's Liberation Army, Beijing 100085)  
Image segmentation and contour detection is important for computer vision and pattern recognition, and the active contour for image segmentation is treated as the most popular study hotspots. A detailed analysis of Mumford-Shah model is given with emphasis on its active contour mechanism, and then a piece-wise smooth level set model is discussed. By constructing the new soft distance function to reinitialize the level set function during the iterations, and by combining the essentially non-oscillatory scheme and the predict-revised scheme, a new finite difference algorithm is proposed. This algorithm not only can detect multiple objects with various shapes of topology including convex and concave objects, but also has the ability to preserve the gray property of the multiple objects. Finally, some examples are given and it is shown that the new algorithm is stable and oscillation does not appear.
【Fund】: 国防预研基金项目 ( 5 14 0 40 40 10 1BQ0 2 ) ;; 高等学校博士学科点专项科研基金项目 ( 2 0 0 2 0 2 880 2 4)
【CateGory Index】: TP391.41
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