An automatic fuzzy c-means algorithm for image segmentation-Reference-Cited by-同舟云学术

An automatic fuzzy c-means algorithm for image segmentation

Published:2009-06-04 Issue:2 Volume:14 Page:123-128
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Li Yan-ling,Shen Yi

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-009-0442-0.pdf

Reference17 articles.

1. Ball G, Hall D (1967) A clustering technique for summarizing multivariate data. Behav Sci 12:153–155

2. Bezdek JC (1974) Cluster validity with fuzzy sets. J Cybern 3:58–73

3. Bezdek JC (1975) Mathematical models for systematic and taxonomy. In: Proceedings of eight international conference on numerical taxonomy, San Francisco, pp 143–166

4. Bezdek JC (1981) Pattern recognition with fuzzy objective function algorithms. Plenum Press, New York

5. Dunn JC (1974) A fuzzy relative of the ISODATA process and its use in detecting compact, well-separated clusters. J Cybern 3:32–57

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