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