DocumentCode
3594987
Title
Fuzzy c-means in an MDL-framework
Author
Selb, Alexander ; Bischof, Horst ; Leonardis, Ales
Author_Institution
Pattern Recognition & Image Processing Group, Tech. Univ. Wien, Austria
Volume
2
fYear
2000
fDate
6/22/1905 12:00:00 AM
Firstpage
740
Abstract
In this paper we present a minimum description length (MDL) framework for fuzzy clustering algorithms. This framework enables us to find an optimal number of cluster centers. We applied our approach to the fuzzy c-means algorithm for which we designed a computationally efficient procedure. We report the results of our approach on a 2D clustering problem and on RGB color image segmentation
Keywords
computational complexity; fuzzy set theory; optimisation; pattern clustering; 2D clustering problem; MDL-framework; RGB color image segmentation; cluster center optimal number; computationally efficient procedure; fuzzy c-means; fuzzy clustering algorithms; minimum description length framework; Algorithm design and analysis; Clustering algorithms; Color; Encoding; Image processing; Image recognition; Image segmentation; Pattern recognition; Radial basis function networks; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2000. Proceedings. 15th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-0750-6
Type
conf
DOI
10.1109/ICPR.2000.906181
Filename
906181
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