Title :
Quantum fuzzy particle swarm optimization algorithm for image clustering
Author :
Zhong, Qingqing ; Yao, Min ; Jiang, Wei
Author_Institution :
Coll. of Comput. Sci., Zhejiang Univ., Hangzhou, China
Abstract :
In this paper, a novel quantum fuzzy particle swarm optimization (QFPSO) approach has been proposed for image clustering. The particle swarm optimization is used to search the global optimal clustering center. Moreover, the quantum encoding is introduced and the quantum operation is implemented on each particle to overcome the premature convergence problem effectively. The experimental results showed that QFPSO algorithm for image clustering performs much better than other contrast methods.
Keywords :
convergence; fuzzy set theory; particle swarm optimisation; pattern clustering; image clustering; premature convergence problem; quantum fuzzy particle swarm optimization algorithm; Clustering algorithms; Convergence; Educational institutions; Encoding; Feature extraction; Image classification; Particle swarm optimization; Quantum computing; Shape; Space technology; fuzzy; image clustering; particle swarm optimization; premature convergence; quantum;
Conference_Titel :
Image Analysis and Signal Processing (IASP), 2010 International Conference on
Conference_Location :
Zhejiang
Print_ISBN :
978-1-4244-5554-6
Electronic_ISBN :
978-1-4244-5556-0
DOI :
10.1109/IASP.2010.5476115
