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
fDate :
6/22/1905 12:00:00 AM
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;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.906181
