模糊聚类算法综述  

Fuzzy Clustering Methods

作　　者：陈厦[1] 方方[1] 胡战利[2] 

机构地区：[1]成都理工大学信息科学与技术学院,四川成都610000 [2]中国科学院深圳先进技术研究院,广东深圳518000

出　　处：《生命科学仪器》2013年第6期33-37,共5页Life Science Instruments

摘　　要：模糊聚类算法是近年来图像分割技术领域的研究热点之一。本文在对模糊C均值聚类算法分析的基础上,结合目前在图像分割中的应用研究,对模糊C均值聚类算法的有效性进行了比较分析。从隶属度、聚类数和其它方面,评述改进的模糊C均值聚类算法。最后讨论模糊C均值聚类算法目前存在的问题和发展方向。Fuzzy clustering algorithm is one of the highlights in the field of image segmentation technology in recent years. In this paper, on the basis of the Fuzzy c-means（FCM）algorithm, combining with the current research in the application of image segmentation, we analyzed the effectiveness of the fuzzy c-means clustering algorithm. The improved fuzzy c-means clustering algorithm was reviewed from the membership degree, clustering number and other aspects. Finally, the existing problems and development direction of the fuzzy c-means clustering algorithm were discussed.

关 键 词：模糊聚类 图像分割 隶属度 

分 类 号：TP274.2[自动化与计算机技术—检测技术与自动化装置]