NDLI: Spatial credibilistic clustering algorithm in noise image segmentation

Content Provider	IEEE Xplore Digital Library
Author	Wen, P. Zheng, L. Zhou, J.
Copyright Year	2007
Description	Author affiliation: Tsinghua Univ., Beijing (Wen, P.; Zheng, L.; Zhou, J.)
Abstract	An image segmentation algorithm based on credibilistic clustering algorithm incorporating spatial continuity is presented in this paper. The probabilistic constraint that the memberships of a pixel across clusters must sum to 1 in fuzzy c-means algorithm is removed, and credibility measure is introduced into image segmentation for the first time. By introducing a novel dissimilarity index in the credibilistic clustering algorithm objective function, the proposed algorithm is not only capable of utilizing local contextual information to impose local spatial continuity, but also allows the suppression of noise and helps to resolve classification ambiguity. Some important issues of the proposed algorithm are investigated, and the computational experiments are given to show the good performance of the proposed algorithm.
Starting Page	543
Ending Page	547
File Size	457688
Page Count	5
File Format	PDF
ISBN	9781424415281
DOI	10.1109/IEEM.2007.4419248
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-02
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	spatial continuity Industrial engineering Time measurement Pattern recognition credibilistic clustering algorithm Computational complexity Image segmentation Image analysis Clustering algorithms fuzzy clustering Spatial resolution Pixel Fuzzy systems
Content Type	Text
Resource Type	Article

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