• DocumentCode
    506976
  • Title

    Hybrid Method of Spatial Credibilistic Clustering and Particle Swarm Optimization: Discussion and Application

  • Author

    Wen, Peihan ; Zhou, Jian ; Zheng, Li ; Chen, Xuan ; Anderson, Brian

  • Author_Institution
    Dept. of Ind. Eng., Tsinghua Univ., Beijing, China
  • Volume
    3
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    423
  • Lastpage
    427
  • Abstract
    As a critical unit of computer vision (CV) based applications, image segmentation is quite worth studying. Hybrid method of spatial credibilistic clustering and particle swarm optimization (SCCPSO) is a novel effective segmentation method. It´s proved to produce better results than other common methods. In this paper, SCCPSO is further investigated by discussing several key points such as membership function, initialization, pre-selection, and boundary conditions. Then the modified SCCPSO is put forth and applied in a CV-based inspection system to show its effectivity and better performance. The proposed method can be also used in other CV-based applications.
  • Keywords
    computer vision; image segmentation; particle swarm optimisation; pattern clustering; boundary condition; computer vision; image segmentation; membership function; particle swarm optimization; spatial credibilistic clustering; Application software; Boundary conditions; Clustering algorithms; Fuzzy systems; Image segmentation; Industrial engineering; Inspection; Particle production; Particle swarm optimization; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3735-1
  • Type

    conf

  • DOI
    10.1109/FSKD.2009.209
  • Filename
    5359007