Title :
An initialization method for multi-type prototype fuzzy clustering
Author :
Xinbo, Gao ; Zhong, Xue ; Jie, LI ; Weixin, Xie
Author_Institution :
Sch. of Electron. Eng., Xidian Univ., Xi´´an, China
Abstract :
Fuzzy clustering is an important branch of unsupervised classification, and has been widely used in pattern recognition and image processing. However, most existing fuzzy clustering algorithms are sensitive to initialization, and strongly depend on the number of clusters, which limits their applications. Moreover, it these algorithms also need to know the type and number of prototypes in advance in multi-type prototype fuzzy clustering. To overcome these limitations, a method for acquiring a priori knowledge about the clustering prototype is proposed in this paper, which obtains better performance in initializing multi-type prototype fuzzy clustering
Keywords :
fuzzy logic; mathematical morphology; pattern classification; pattern clustering; image processing; initialization method; mathematical morphology; multi-type prototype fuzzy clustering; pattern recognition; unsupervised classification; Clustering algorithms; Curve fitting; Design engineering; Finite impulse response filter; Fuzzy sets; Manufacturing automation; Morphology; Partitioning algorithms; Pattern recognition; Prototypes;
Conference_Titel :
Signal Processing Proceedings, 1998. ICSP '98. 1998 Fourth International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4325-5
DOI :
10.1109/ICOSP.1998.770834