• DocumentCode
    2734453
  • Title

    A modified ant colony optimization based approach for image edge detection

  • Author

    Rajeswari, R. ; Rajesh, R.

  • Author_Institution
    Dept. of Comput. Applic., Bharathiar Univ., Coimbatore, India
  • fYear
    2011
  • fDate
    3-5 Nov. 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Ant Colony Optimization (ACO) is used to detect edges in digital images. Such techniques generate a pheromone matrix that represents the edge information at each pixel position on the routes formed by ants dispatched on the image. In this paper a modified ACO-based edge detection is proposed. Ants try to find possible edges by using a heuristic information based on the degree of edginess of each pixel. The proposed ACO-based approach also takes advantage of the fuzzy clustering to determine whether a pixel is edge or not. Experimental results demonstrate superior performance of the proposed approach.
  • Keywords
    edge detection; fuzzy set theory; image representation; optimisation; pattern clustering; digital images; edge information representation; fuzzy clustering; heuristic information; image edge detection; modified ACO-based edge detection; modified ant colony optimization; pheromone matrix; pixel position; Ant colony optimization; Cameras; Clustering algorithms; Data mining; Digital images; Image edge detection; Presses; aco-based algorithm; edge based heuristic information; edge detection; fuzzy clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Information Processing (ICIIP), 2011 International Conference on
  • Conference_Location
    Himachal Pradesh
  • Print_ISBN
    978-1-61284-859-4
  • Type

    conf

  • DOI
    10.1109/ICIIP.2011.6108930
  • Filename
    6108930