• DocumentCode
    3158547
  • Title

    Digital image edge detection using an ant colony optimization based on genetic algorithm

  • Author

    Rahebi, Javad ; Elmi, Zahra ; Nia, Ali Farzam ; Shayan, Kamran

  • Author_Institution
    Fac. of Electr. Eng., Sadjad Univ. of Mashhad, Mashhad, Iran
  • fYear
    2010
  • fDate
    28-30 June 2010
  • Firstpage
    145
  • Lastpage
    149
  • Abstract
    In this paper a new method for enhancement of digital image edge detection using ant colony optimization based on genetic algorithm has been used. In the proposed method first by the series of answers has been formed by artificial ants and then formed in a manner i.e. useful for genetic algorithm, then the answers played the role as initial population for genetic algorithm and the next population is made by genetic algorithm. Our method compared with Jing Tian method enjoys higher speed, less processing time and more answer´s optimum. Also the proposed method has a better edge than other classical methods (such as sobel, etc).
  • Keywords
    edge detection; genetic algorithms; Jing Tian method; ant colony optimization; artificial ants; digital image edge detection; genetic algorithm; Ant colony optimization; Digital images; Fluctuations; Genetic algorithms; Genetic engineering; Image edge detection; Java; Pixel; Ant colony optimization; Edge detection; Genetic Algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cybernetics and Intelligent Systems (CIS), 2010 IEEE Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-6499-9
  • Type

    conf

  • DOI
    10.1109/ICCIS.2010.5518567
  • Filename
    5518567