计算机应用研究2011，Vol.28Issue(12)：4773-4775,3.DOI:10.3969/j.issn.1001-3695.2011.12.100
基于分水岭和改进的模糊聚类图像分割
Image segmentation based on watershed and improved fuzzy C-means clustering
摘要
Abstract
In order to solve the problems in FCM (fuzzy C-means clustering) such as the original cluster centers to be given in advance, not considering neighbor information and high complexity, this paper proposed an image segmentation based on wa-tershed and improved FCM. Dividing image with the help of watershed algorithm, and gained the primary results. It made full use of the ability of global optimization PSO ( particle swarm optimization) to obtain the accurate original cluster centers of FCM. It had been established a novel objective function which contained neighbor information. The experimental results show that this method has higher segmentation speed and stronger anti-noise property, and it realizes significant image segmentation.关键词
分水岭算法/粒子群算法/模糊聚类/图像分割Key words
watershed algorithm/ PSO algorithm/ fuzzy clustering/ image segmentation/分类
信息技术与安全科学引用本文复制引用
龚劬,姚玉敏..基于分水岭和改进的模糊聚类图像分割[J].计算机应用研究,2011,28(12):4773-4775,3.基金项目
中央高校基金资助项目(CDJXS11100032) （CDJXS11100032）
