• DocumentCode
    2097404
  • Title

    Region segmentation using K-mean clustering and genetic algorithms

  • Author

    Horita, Yuukou ; Murai, Tadahuni ; Miyahara, Makoto

  • Author_Institution
    Dept. of Electron. & Comput. Sci., Toyama Univ., Japan
  • Volume
    3
  • fYear
    1994
  • fDate
    13-16 Nov 1994
  • Firstpage
    1016
  • Abstract
    One of the hard problems in image recognition and understanding is region segmentation. A traditional segmentation method such as clustering is not fully useful for any image, because of the initial values of clusters and the evaluation functions of segmented clusters affect the results of region segmentation. To solve this problem, we introduce the genetic algorithm (GA) for clustering. The experimental result shows the satiable results of region segmentation which have been achieved by applying GA
  • Keywords
    genetic algorithms; image recognition; image segmentation; K-mean clustering; clustering; genetic algorithm; genetic algorithms; image recognition; region segmentation; Clustering methods; Color; Computer science; Genetic algorithms; Genetic engineering; Genetic mutations; Histograms; Image edge detection; Image recognition; Image segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
  • Conference_Location
    Austin, TX
  • Print_ISBN
    0-8186-6952-7
  • Type

    conf

  • DOI
    10.1109/ICIP.1994.413691
  • Filename
    413691