• DocumentCode
    2016400
  • Title

    A improved k-means clustering algorithm combined with the genetic algorithm

  • Author

    Li, Xiaoping ; Zhang, Lei ; Li, Yinxiang ; Wang, Zhenghong

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Beijing Inst. of Technol., Beijing, China
  • fYear
    2010
  • fDate
    16-18 Aug. 2010
  • Firstpage
    121
  • Lastpage
    124
  • Abstract
    The cluster approach is one of the basic methods to pattern classification and system modeling. The clustering target is that according to some rules, divide the sample data set in the sample space into some subsets indicating different patterns or system behavior[1]. In the course of establishing the video image indexing, every step from building index according to the basic visual characters of extracted images, to forming category index trough extracting related programs, uses the clustering thought. So, how to choose a suitable effective clustering algorithm will directly affect the efficiency to establish the video image indexing and the performance of the whole management system. The k-means clustering algorithm is a relatively good one.
  • Keywords
    feature extraction; genetic algorithms; indexing; pattern classification; pattern clustering; video databases; video signal processing; K-means clustering algorithm; genetic algorithm; image extraction; pattern classification; sample data set; system modeling; video image indexing; Algorithm design and analysis; Biological cells; Indexes; genetic algorithm; k-means; k-means clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Content, Multimedia Technology and its Applications (IDC), 2010 6th International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-7607-7
  • Electronic_ISBN
    978-8-9886-7827-5
  • Type

    conf

  • Filename
    5568718