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

In this paper, according to the traditional C-V level set model image segmentation of slow speed, low efficiency of initialization and weak ability to capture edge, puts forward a kind of improved C-V level set image segmentation model added edge information of image in model; in the numerical experiment, using narrow band method improved, thereby reducing the amount of computation, improve the efficiency of image segmentation. Experiments show that this algorithm is better than the traditional C-V model compared with the segmentation speed, and the algorithm has low complexity and high accuracy.