• DocumentCode
    1487791
  • Title

    Multiseeded segmentation using fuzzy connectedness

  • Author

    Herman, Gabor T. ; Carvalho, Bruno M.

  • Author_Institution
    Center for Comput. Sci. & Appl. Math., Temple Univ., Philadelphia, PA, USA
  • Volume
    23
  • Issue
    5
  • fYear
    2001
  • fDate
    5/1/2001 12:00:00 AM
  • Firstpage
    460
  • Lastpage
    474
  • Abstract
    Fuzzy connectedness has been effectively used to segment out an object in a badly corrupted image. We generalize the approach by providing a definition which is shown to always determine a simultaneous segmentation of multiple objects. For any set of seed points, the segmentation is uniquely determined by the definition. An algorithm for finding this segmentation is presented and its output is illustrated. The algorithm is fast as compared to other segmentation algorithms in current use. We also report on an evaluation of the accuracy and robustness of the algorithm based on experiments in which several users were repeatedly asked to identify the seed points for the algorithm in a number of images
  • Keywords
    feature extraction; fuzzy set theory; image segmentation; object recognition; accuracy; fuzzy connectedness; multiseeded segmentation; robustness; seed points; Clustering algorithms; Feature extraction; Fuzzy sets; Image recognition; Image segmentation; Pixel; Psychology; Robustness; Statistics;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.922705
  • Filename
    922705