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Proceedings Paper

New AFCM clustering algorithm
Author(s): Luping Xu; Weixing Xie; Wenhua Li
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Paper Abstract

This paper proposes an improvement of the approximate fuzzy c-means (AFCM) clustering algorithm, called BAFCM, that is based on a fast method for edge detection using fuzzy sets which is used to initialize the c clusters effectively. Our results show that the BAFCM requires about half as much computer time as the AFCM while yielding the same accuracy as the AFCM. One may use BAFCM to accelerate AFCM processing.

Paper Details

Date Published: 28 August 1995
PDF: 5 pages
Proc. SPIE 2620, International Conference on Intelligent Manufacturing, (28 August 1995); doi: 10.1117/12.217542
Show Author Affiliations
Luping Xu, Xidian Univ. (China)
Weixing Xie, Xidian Univ. (China)
Wenhua Li, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 2620:
International Conference on Intelligent Manufacturing
Shuzi Yang; Ji Zhou; Cheng-Gang Li, Editor(s)

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