信息与电子工程2011，Vol.9Issue(6)：754-758,5.
区间二型模糊C均值聚类在图像分割中的应用
An Interval Type-2 Fuzzy C-Means algorithm for image segmentation
摘要
Abstract
Cluster analysis is an important branch of non-supervision pattern recognition, and Fuzzy C-Means(FCM) algorithm is a classic algorithm in cluster analysis. However, FCM is founded with Type-1 fuzzy sets, which can not handle the uncertainties existing in data and algorithm itself. This paper introduces the Interval Type-2 Fuzzy C-Means(IT2FCM) algorithm, whose core is type-2 fuzzy set that has better performance on handling uncertainties than Type-1 fuzzy set. IT2FCM and FCM are used for image segmentation to compare their segmentation results. The experiment shows that IT2FCM has better performance on suppressing noise and better effects on segmenting images compared with FCM.关键词
区间二型模糊集/均值聚类算法/图像分割Key words
Interval Type-2 Fuzzy set/Fuzzy C-Means algorithm/image segmentation分类
信息技术与安全科学引用本文复制引用
邱存勇,肖建..区间二型模糊C均值聚类在图像分割中的应用[J].信息与电子工程,2011,9(6):754-758,5.基金项目
国家自然科学基金资助项目(60674057) （60674057）
中央高校专项资金资助项目(SWJTU09ZT11) （SWJTU09ZT11）
