• DocumentCode
    2037270
  • Title

    A fuzzy-based feature tuning algorithm applied to image segmentation

  • Author

    Chia-Horng Huang ; Yi-Wei Yu ; Wang, Junghua

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan
  • Volume
    4
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    2140
  • Abstract
    Over-segmentation is a serious problem in conventional watershed analysis owing to the topographic relief inherent in the input image. Currently in watershed segmentation methods, merging regions one by one is the most well known cure for the over-segmentation problem, K. Haris et al.(1998) proposed a merging algorithm called fast nearest neighbor region merging based on the observation that it is not necessary to keep all RAG in the heap, only a small portion of them is used to construct nearest neighbor graph (NNG). Although the performance of merging is greatly improved, the required computation time is in proportional to the initial number of regions in NNG. In this paper we propose the fuzzy-based feature tuning (FFT) algorithm that can simultaneously adjust ?i of all region by referencing their adjacent neighboring regions, where ?i is defined as the average gray value over region i
  • Keywords
    fuzzy logic; image segmentation; merging; average gray value; fast nearest neighbor region merging; fuzzy-based feature tuning algorithm; heap; image segmentation; merging algorithm; nearest neighbor graph; topographic relief; watershed analysis; Clustering algorithms; Filters; Gray-scale; Image analysis; Image segmentation; Merging; Nearest neighbor searches; Performance analysis; Smoothing methods; Surface topography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 2001 IEEE International Conference on
  • Conference_Location
    Tucson, AZ
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-7087-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2001.972872
  • Filename
    972872