earticle

영어

In this paper, a novel image segmentation algorithm based on fuzzy clustering and entropy analysis using space information for optical images is proposed. We adopt the general properties of Hopfield neural network (HNN) and multi-synapse neural network (MSNN) to gain the center of the clusters and the fuzzy membership degrees for solving the optimization problems. As far as the noise influence is concerned, we introduce a novel window to improve the robustness of the proposed algorithm. In the experimental analysis part, we compare our method with some state-of-the-art methodologies and adopt the well-known test image databases to conduct the experiment. The result indicates that compared to FCM and some other clustering methods, our entropy and neural network based algorithm performs better. Our approach is less time-consuming and more robust to noise.