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Proceedings Paper

Cloud model based fuzzy C-means clustering and its application
Author(s): Kun Qin; Min Xu; Deyi Li
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Paper Abstract

The Algorithm of Fuzzy C-Means (FCM) clustering is used in many fields, such as data mining, image segmentation etc. But it has the problem of cluster center initialization. Good initial cluster centers will constrain the value function to the overall situation optimal solution rapidly, and inappropriate initial cluster centers, not only need more iterative times, but also may possibly cause the algorithm finally restrained to the partial optimal solution. Aim to resolve the problem of cluster center initialization, the paper proposes a new approach of FCM based on cloud model which is an efficient transformation model between quantitative number and qualitative concept, and applied it in the field of image segmentation, the experiment results prove the method can define good initial cluster centers and produce good quality of image segmentation.

Paper Details

Date Published: 8 August 2007
PDF: 9 pages
Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67520T (8 August 2007); doi: 10.1117/12.760463
Show Author Affiliations
Kun Qin, Wuhan Univ. (China)
Min Xu, Wuhan Univ. (China)
Deyi Li, China Institute of Electronic System Engineering (China)


Published in SPIE Proceedings Vol. 6752:
Geoinformatics 2007: Remotely Sensed Data and Information

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