• DocumentCode
    584472
  • Title

    Image Segmentation Using Thresholding and Artificial Fish-Swarm Algorithm

  • Author

    Zhiwei, Ye ; Qinyun, Li ; Mengdi, Zeng ; Wei, Liu

  • Author_Institution
    Sch. of Comput. Sci., Hubei Univ. of Technol., Wuhan, China
  • fYear
    2012
  • fDate
    11-13 Aug. 2012
  • Firstpage
    1529
  • Lastpage
    1532
  • Abstract
    Image segmentation is an important technology for image processing. Many segmentation methods have been brought forward for image segmentation, among these methods thresholding is the simplest and effective method in image segmentation. In general, the thresholding method based on two-dimensional histogram can provide better results than that of one-dimension histogram. However, for more accurate thresholding, much more time has to pay. Thus, this paper proposes a novel approach to two-dimensional threshold selection based on artificial fish-swarm algorithm and two-dimensional Fisher function criterion. In final, experiments results demonstrate that the proposed method performs well which is a good method to help select optimum 2D thresholds.
  • Keywords
    image segmentation; optimisation; artificial fish-swarm algorithm; image processing; image segmentation; optimum 2D threshold selection; two-dimensional Fisher function criterion; two-dimensional histogram; Algorithm design and analysis; Computer science; Educational institutions; Histograms; Image segmentation; Marine animals; Signal processing algorithms; 2-D Fisher Function; Artificial fish-swarm algorithm; image segmentation; thresholding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Service System (CSSS), 2012 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-0721-5
  • Type

    conf

  • DOI
    10.1109/CSSS.2012.383
  • Filename
    6394622