Graphics Processing Unit Based Fuzzy C-means Clustering Segmentation
基于图形处理器的模糊C均值聚类分割算法

In order to accelerate the segmentation algorithm of FCM(fuzzy c-means clustering),an accelerating algorithm based on GPU(graphics processing unit) was proposed.Firstly,this method analyses the various phases of FCM algorithm which could be paralleled.Then,in order to adapt to the GPU’s hardware architecture,this method transforms the computing of membership grade and clustering center and the classifying of every pixels according to the membership grade with CUDA(Compute Unified Device Architecture).Experimental results show that the efficiency of the FCM segmentation algorithm accelerated by GPU is improved obviously compared with CPU’s serial algorithm.In view of the parallel features of most image processing algorithms,the acceleration based on GPU is universal.