Image Segmentation with Fuzzy Clustering Based on Generalized Entropy

Aimed at fuzzy clustering based on the generalized entropy, an image segmentation algorithm by joining space information of image is presented in this paper. For solving the optimization problem with generalized entropy’s fuzzy clustering, both Hopfield neural network and multi-synapse neural network are used in order to obtain cluster centers and fuzzy membership degrees. In addition, to improve anti-noise characteristic of algorithm, a window is introduced. In experiments, some commonly used images are selected to verify performance of algorithm presented. Experimental results show that the image segmentation of fuzzy clustering based on generalized entropy using neural network performs better compared to FCM and BCFCM_S1.