Modified Fast Fuzzy C-means Algorithm for Image Segmentation

Because Fuzzy c-means (FCM) clustering algorithm has the problems of initializing the cluster centers and a huge number of computing in the iteration, this paper presents an improved method. It can optimize the data set to reduce the time for each of iteration, and then use cluster centers obtained by the sample density as the initial cluster centers to reduce the number of iterations required for convergence. Experiments show this method is able to solve the problem of initial centers, improve the speed of convergence and running and the clustering effects for image segmentation.