An Image Segmentation Algorithm Based on Fuzzy C-Means Clustering

Abstract

Image segmentation algorithm based on fuzzy c-means clustering is an important algorithm in the image segmentation field. It has been used widely. However, it is not successfully to segment the noise image because the algorithm disregards of special constraint information. It only considers the gray information. Therefore, we proposed a weighed FCM algorithm based on Gaussian kernel function for image segmentation. The original Euclidean distance is replaced by a kernel-induced distance in the algorithm. Then, a bound term is added to the objective function to compensate the influence of the spatial information. The experimental results illustrate that the proposed method is more effective to image segmentation.