• DocumentCode
    3249486
  • Title

    Applications of genetic algorithms, geostatistics, and fuzzy c-means clustering to image segmentation

  • Author

    Pham, T. ; Wagner, M. ; Clark, D.

  • Author_Institution
    ADA Inc., Ottawa, Ont., Canada
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    741
  • Abstract
    We apply different advantages of the optimal genetic searching, geostatistics, and fuzzy c-means clustering to the segmentation of gray-level images. The proposed method can deal effectively with noisy image segmentation
  • Keywords
    fuzzy logic; genetic algorithms; image segmentation; pattern clustering; fuzzy c-means clustering; genetic algorithms; geostatistics; gray-level images; image segmentation; noisy image segmentation; optimal genetic searching; Australia; Clustering algorithms; Electronic mail; Equations; Fuzzy sets; Genetic algorithms; Image edge detection; Image segmentation; Pixel; Virtual colonoscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
  • Conference_Location
    Seoul
  • Print_ISBN
    0-7803-6657-3
  • Type

    conf

  • DOI
    10.1109/CEC.2001.934263
  • Filename
    934263
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3249486