• DocumentCode
    1879001
  • Title

    Research of the Image Segmentation Based on Ant Colony Algorithm

  • Author

    Yan, Zhe ; Gu, Han-Ming

  • Author_Institution
    Inst. of Geophys. & Geomatics, China Univ. of Geosci., Wuhan, China
  • fYear
    2009
  • fDate
    27-29 May 2009
  • Firstpage
    106
  • Lastpage
    109
  • Abstract
    Ant colony algorithm, based on behavior of real ants, is a natural approach to establish from their nest to food source. An ant moves randomly and detects a previously laid pheromone on a path in order to find the shortest way between their nest and the food source. Ant system algorithm is an important methodology to apply on non-linear optimal problems recently. Each ant chooses the next position to visit in accordance with the visibility of the position and the pheromone intensity. In this paper, an ant colony algorithm for image segmentation is proposed. We discuss the ideas behind ant algorithms and describe how they have been implemented with regards to the image segmentation problem. The proposed approach has been tested on different images. The experimental results demonstrate the effectiveness and practicability of the proposed algorithm.
  • Keywords
    image segmentation; optimisation; ant colony algorithm; image segmentation; Artificial intelligence; Cities and towns; Distributed computing; Geophysics; Image analysis; Image segmentation; Insects; Intelligent networks; Software algorithms; Software engineering; ant colony; image segmentation; iterations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, 2009. SNPD '09. 10th ACIS International Conference on
  • Conference_Location
    Daegu
  • Print_ISBN
    978-0-7695-3642-2
  • Type

    conf

  • DOI
    10.1109/SNPD.2009.58
  • Filename
    5286684