• DocumentCode
    480071
  • Title

    Application of an Improved Genetic Algorithm in Image Segmentation

  • Author

    Hui, Lei ; Shi, Cheng ; Min-si, Ao ; Yi-qi, Wu

  • Author_Institution
    Fac. of Mech. & Electron. Inf., China Univ. of Geosci., Wuhan
  • Volume
    3
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    898
  • Lastpage
    901
  • Abstract
    The selection of threshold is critical in image segmentation. Based on genetic algorithm, an improved method for selecting the optimal threshold in image segmentation is proposed. In the computational process, the improved GA adjusts crossover probability and mutation probability automatically according to the variance between the target and background, thus overcoming the problems of poor astringency and premature occurrence in Simple Genetic Algorithm. Moreover, the improved GA is used to find the optimum relation of the evaluation function on the basis of OTSU Principle in the paper. The experimental data demonstrate that this improved GA has a better convergence and stability than the Simple GA.
  • Keywords
    genetic algorithms; image segmentation; probability; genetic algorithm; image segmentation; optimal threshold; probability; Computer science; Convergence; Equations; Genetic algorithms; Genetic mutations; Geology; Histograms; Image segmentation; Pixel; Stability; image segmentation; improved genetic algorithm; segmentation threshold;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.794
  • Filename
    4722487