关键词: 图像分割, 主动轮廓线, Cauchy-Schwarz散度, Split-Bregman迭代

Abstract: Based on the Cauchy-Schwarz divergence, a new image segmentation model using active contour is proposed, which consists of a geometric regularization term and a data fitting term. Particularly, the data fitting item is constructed by measuring the Cauchy-Schwarz divergence between the probability density functions of intensity in different regions, and the probability density functions are estimated with nonparametric method. In order to obtain a global and optimal solution for the new model quickly, the latest convexification technology and the Split-Bregman rapid iteration method are used. The experimental segmentation results for some images are demonstrated to show some desirable performances and faster convergence rate of this model.

Key words: image segmentation, active contours, Cauchy-Schwarz divergence, Split-Bregman iteration