DocumentCode :
2995839
Title :
Hybrid ant colony algorithm for texture classification
Author :
Zheng, Hong ; Wong, Alan ; Nahavandi, Saeid
Author_Institution :
Sch. of Eng. & Technol., Deakin Univ., Geelong, Vic., Australia
Volume :
4
fYear :
2003
fDate :
8-12 Dec. 2003
Firstpage :
2648
Abstract :
We present a novel ant colony algorithm integrating genetic algorithms and simplex algorithms. This method is able to not only speed up searching process for optimal solutions, but also improve the quality of the solutions. The proposed method is applied to set up a learning model for the "tuned" mask, which is used for texture classification. Experimental results on real world images and comparisons with genetic algorithms and genetic simplex algorithms are presented to illustrate the merit and feasibility of the proposed method.
Keywords :
evolutionary computation; image classification; image texture; learning (artificial intelligence); multi-agent systems; search problems; genetic algorithm; hybrid ant colony algorithm; learning model; simplex algorithm; texture classification; Ant colony optimization; Australia; Classification algorithms; Feature extraction; Genetic algorithms; Genetic engineering; Humans; Image texture analysis; Robustness; Visual perception;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN :
0-7803-7804-0
Type :
conf
DOI :
10.1109/CEC.2003.1299422
Filename :
1299422
Link To Document :
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