Fuzzy-C-means clustering based on the gray and spatial feature for image segmentation

CORC > 兰州理工大学 > 兰州理工大学

	Fuzzy-C-means clustering based on the gray and spatial feature for image segmentation
	Li, Ming; Li, Yun-song
	2006
页码	1641-1646
英文摘要	Fuzzy c-means (FCM) clustering algorithm has been widely used in automated image segmentation. However, the standard FCM algorithm is sensitive to noise because of taking no into account the gray and spatial information of pixel. The paper proposes an improved FCM algorithm for image segmentation. We use the degree of gray similarity and distribution statistics of the neighbor pixels to form a new membership function for clustering. Not only it is effective to remove the noise spots and reduce the spurious blobs, but also it is ease to correct the misclassified pixels. Experimental results on three types of image indicate that the propose algorithm is more accurate and robust than the standard FCM algorithm.
会议录	2006 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY, PTS 1 AND 2, PROCEEDINGS
会议录出版者	IEEE
会议录出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
语种	英语
WOS研究方向	Computer Science
WOS记录号	WOS:000243679800350
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/38259]
专题	兰州理工大学
通讯作者	Li, Ming
作者单位	Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Peoples R China
推荐引用方式 GB/T 7714	Li, Ming,Li, Yun-song. Fuzzy-C-means clustering based on the gray and spatial feature for image segmentation[C]. 见:.