Image Segmentation Based on Exponential Kernel Function
Dingding Yang, Liming Tang, Shiqiang Chen, Jun Li · 2017
For improving the accuracy and efficiency of image segmentation, an improved CV (Chan-Vese) model based on exponential kernel function is proposed. Firstly, according to the fast convergence character of exponential function, the efficiency is improved. Then the accuracy is more precise by modifying the energy function of the CV model. Finally, introducing level set function avoids the re-initialization and reduces the re-initialization time. Compared with the CV model, the CV model based on exponential kernel function has higher segmentation accuracy and stronger anti-noise ability, and needs less iteration times and running time.