• DocumentCode
    2814375
  • Title

    Segmentation of a sonar image from a small underwater target using the improved fuzzy clustering algorithm

  • Author

    Guo, Haitao ; Zhou, Jun ; Song, Ruili ; Wu, Junpeng

  • Author_Institution
    Electr. Eng. Coll., Northeast Dianli Univ., Jilin, China
  • fYear
    2011
  • fDate
    15-17 July 2011
  • Firstpage
    5218
  • Lastpage
    5220
  • Abstract
    This paper expatiates on the improved fuzzy c-means (FCM) clustering algorithm. In the algorithm, the membership values are determined via the improved method, and the number of the centers of FCM clustering are determined via the number of the peaks of the two-dimensional histogram on the gray-level values of pixels and gradient values of pixel neighborhoods. The application to segmentation of a sonar image of a small underwater target shows that the improved FCM clustering algorithm can segment the image into the shadow and echo regions of the target, and that the improved algorithm is more intelligent and timesaving than the traditionary FCM clustering algorithm.
  • Keywords
    fuzzy set theory; image segmentation; pattern clustering; sonar imaging; FCM clustering algorithm; fuzzy c-means clustering algorithm; gradient values; gray-level values; pixel neighborhoods; small underwater target; sonar image segmentation; two-dimensional histogram; Clustering algorithms; Computers; Educational institutions; Electrical engineering; Histograms; Image segmentation; Sonar; fuzzy clustering; image segmentation; small underwater target; sonar image;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechanic Automation and Control Engineering (MACE), 2011 Second International Conference on
  • Conference_Location
    Hohhot
  • Print_ISBN
    978-1-4244-9436-1
  • Type

    conf

  • DOI
    10.1109/MACE.2011.5988166
  • Filename
    5988166