• DocumentCode
    3301305
  • Title

    Improved image segmentation method based on optimized threshold using Genetic Algorithm

  • Author

    Zhao, Xin ; Lee, Myung-Eun ; Kim, Soo-Hyung

  • Author_Institution
    Chonnam Nat. Univ., Gwangju
  • fYear
    2008
  • fDate
    March 31 2008-April 4 2008
  • Firstpage
    921
  • Lastpage
    922
  • Abstract
    In image segmentation, threshold segmentation is becoming more and more widely used because of its simplicity and efficiency. In this paper, an improved image segmentation method based on optimized threshold using genetic algorithm is proposed. Compared with the traditional threshold segmentation methods, this method has advantages that it can nicely segment the thin and it can efficiently reduce calculation time and it has good capability and stabilization nature. The results show that using this proposed method can obtain satisfactory segmentation effect.
  • Keywords
    genetic algorithms; image segmentation; genetic algorithm; image segmentation; optimized threshold; threshold segmentation; Biological cells; Entropy; Genetic algorithms; Genetic mutations; Image segmentation; Iterative algorithms; Iterative methods; Optimization methods; Random number generation; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Systems and Applications, 2008. AICCSA 2008. IEEE/ACS International Conference on
  • Conference_Location
    Doha
  • Print_ISBN
    978-1-4244-1967-8
  • Electronic_ISBN
    978-1-4244-1968-5
  • Type

    conf

  • DOI
    10.1109/AICCSA.2008.4493645
  • Filename
    4493645