• 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