国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

The traditional fuzzy C-means clustering (FCM) algorithm is sensitive to the initial clustering center and is easy to fall into local convergence,and lacks enough robustness,and also has big computational cost. A fast fuzzy clustering image segmentation method based on Improved Particle Swarm Optimization (PSOFCM) is proposed to solve those problems. Firstly,the image is filtered by the adaptive median filter and the robustness of the algorithm is enhanced. Secondly,the gray value of the image pixel is mapped to the two-dimensional histogram feature space in order to reduce calculation and optimize the algorithm objective function of FCM. Finally,the PSO algorithm is used to replace the FCM gradient iterative process,which enhances the global search ability,and reduces the dependence of the algorithm to the initial clustering center. Experimental results show that this method overcomes the dependence on initial clustering center of FCM algorithm,which brings high robustness and segmentation accuracy,and has faster convergence speed.