• DocumentCode
    2702782
  • Title

    An Improved Fuzzy Clustering Method to Detect Moving Objects

  • Author

    Lu, Yu ; Zhu, Hao ; Wu, Qinzhang

  • Author_Institution
    Chinese Acad. of Sci., Chengdu
  • fYear
    2007
  • fDate
    15-19 Dec. 2007
  • Firstpage
    15
  • Lastpage
    18
  • Abstract
    The classical fuzzy clustering method needs to determine the number of group for classification before all samples are processed and the number of group is fixed during iteration, which dose not help to ensure the classification precision. Considering this, an improved fuzzy clustering method with elastic grouping logic is proposed. The elastic grouping logic, based on the samples´ ascriptions and their distances to the centers of each group, can dynamically adjust the number of group and achieve the accurate classification. Our improved clustering method is applied in the optical flow field. The experimental results show that our method has superiority over the classical clustering method in precision and can detect the moving object with precision.
  • Keywords
    fuzzy set theory; image classification; object detection; pattern clustering; classification precision; elastic grouping logic; fuzzy clustering; moving objects detection; Automobiles; Clustering methods; Computational intelligence; Fuzzy logic; Image motion analysis; Motion detection; Object detection; Pattern recognition; Pixel; Security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security Workshops, 2007. CISW 2007. International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-0-7695-3073-4
  • Type

    conf

  • DOI
    10.1109/CISW.2007.4425435
  • Filename
    4425435