Modified FCM clustering based on kernel mapping

Zeyu Li; Shiwei Tang; Jing Xue; Jun Jiang

doi:10.1117/12.441658

24 September 2001 Modified FCM clustering based on kernel mapping

Zeyu Li, Shiwei Tang, Jing Xue, Jun Jiang

Proceedings Volume 4554, Object Detection, Classification, and Tracking Technologies; (2001) https://doi.org/10.1117/12.441658
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

Abstract

A modified method for performing nonlinear form of Fuzzy C-Means (FCM) clustering algorithm (K-FCM) is proposed. By the use of kernel mapping, the non-linear clustering problem can be efficiently transformed into a linear problem in high-dimensional, even infinite, feature space. At the same time, we need not to know the explicit form of the non-linear mapping. That means that the computational complexity will not raised largely. The experimental result reveals the efficient and effective of the method proposed in this paper.

Citation Download Citation

Zeyu Li, Shiwei Tang, Jing Xue, and Jun Jiang "Modified FCM clustering based on kernel mapping", Proc. SPIE 4554, Object Detection, Classification, and Tracking Technologies, (24 September 2001); https://doi.org/10.1117/12.441658

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