Abstract：As an improved algorithm of Fuzzy C-Means (FCM), generalized fuzzy c-means algorithm with improved fuzzy partitions (GIFP-FCM) can reduce the influence of image noises on image segmentation to some extent. However, since the neighbor information is not taken into consideration, GIFP-FCM cannot work well on image with much noises. In order to solve this problem, a new objective function was established with neighbor information and local membership. Every pixel with local membership and neighbor information was recomputed to overcome the influences of noises. The experimental results on synthesized images and brain images show that the proposed algorithm can get the maximum partition coefficient and the minimum partition entropy, which shows the effectiveness of the proposed algorithm.
王海军 柳明. 基于局部隶属度和邻域信息的GIFP-FCM图像分割算法[J]. 计算机应用, 2013, 33(08): 2355-2358.
WANG Haijun LIU Ming. Generalized fuzzy c-means algorithm with improved fuzzy partitions based on local membership and neighbor information. Journal of Computer Applications, 2013, 33(08): 2355-2358.
2013, Vol. 33 
