Simulated Annealing based Maximum Likelihood Clustering Algorithm for Image Segmentation
基于模拟退火的最大似然聚类图像分割算法

Image segmentation can be regarded as the problem of two-class pattern classification. How to apply the maximum likelihood clustering algorithm to image segmentation is discussed in this paper. Simulated annealing technology is used to solve the problem of maximum likelihood clustering, which avoids the local optimal solution of iterative method. It shows better image segmentation effect than the famous Otsu algorithm and iterative method with less classification error than iterative method.