A Global Minimization Method for Image Segmentation
Li Wei-bin① Gao Er① Song Song-he①②
①(College of Science, National University of Defense Technology, Changsha 410073, China) ②(State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha 410073, China)
Abstract：Active contour models are successfully and widely used in image segmentation. However, they always get local minima which make wrong segmentation results. In this paper, based on previous work named background removed model, a convex energy which is obtained by approximating the Heaviside function in the previous nonconvex energy is proposed. By minimizing it, the evolution equation is given. Experimental results show that the proposed method is accurate, fast and antinoise. Moreover, it is not sensitive to the location of the initial curve.
李伟斌, 高二, 宋松和. 一种全局最小化的图像分割方法[J]. 电子与信息学报, 2013, 35(4): 791-796.
Li Wei-Bin, Gao Er, Song Song-He. A Global Minimization Method for Image Segmentation. , 2013, 35(4): 791-796.
2013, Vol. 35 
