A Novel Semi-fuzzy Clustering Algorithm with Application in Image Texture Segmentation

摘要：

Image texture segmentation is one of the important branches in image pattern recognition,which provides usefulness in many applications.Until now,how to find an effective way for accomplishing texture segmentation in practical applications is still a major task.In this paper,a novel semi-fuzzy clustering algorithm is presented.The basic idea is to extend Fisher discrimination method with fuzzy theory and define fuzzy Fisher criterion as the objective function of the proposed clustering algorithm.By iteratively optimizing this function,the final clustering results are obtained.Experimental results on its application in image texture segmentation show that the proposed algorithm has better performance when noise is present than the standard algorithm.

关键词： Fisher Criterion Optimal Discriminant Vector Semi-fuzzy clustering Fuzzy C-means Image Texture Segmentation

作者: Suqun Cao Shitong Wang Yunfeng Bo Xiaofeng Chen

作者单位: School of Information,Jiangnan University,Wuxi,214122,China Department of Mechanical Engineering,Hua School of Information,Jiangnan University,Wuxi,214122,China Department of Mechanical Engineering,Huaiyin Institute of Technology Huaian 223001,China

会议类型: 国际会议

会议名称: 2008年国际电子商务、工程及科学领域的分布式计算和应用学术研讨会(2008 International Symposium on Distributed Computing and Applications for Business Engineering and Science)

会议地点: 大连

会议语种:英文

页码: 214-218

在线出版日期: 2008-07-27（万方平台首次上网日期，不代表论文的发表时间）