• DocumentCode
    3484783
  • Title

    Rough and accurate segmentation of natural images using fuzzy region-growing algorithm

  • Author

    Maeda, J. ; Novianto, S. ; Saga, S. ; Suzuki, Y. ; Anh, V.V.

  • Author_Institution
    Dept. of Comput. Sci. & Syst. Eng., Muroran Inst. of Technol., Japan
  • Volume
    3
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    227
  • Abstract
    We present a rough and an accurate segmentation of natural images using a fuzzy region-growing algorithm. First, an optimum number of the blanket for local areas is determined to estimate the optimal local fractal dimension. Then, the intensity features and the local fractal-dimension feature are integrated into the fuzzy region-growing algorithm. In the proposed method, the intensity features are used to produce an accurate segmentation, while the fractal-dimension feature is used to yield a rough segmentation in a natural image. The effectiveness of the proposed method is confirmed through computer simulations that demonstrate a rough segmentation at the fine-texture regions and an accurate segmentation at the strong-edge regions simultaneously
  • Keywords
    fractals; fuzzy set theory; image segmentation; image texture; natural scenes; computer simulations; fine-texture regions; fuzzy region-growing algorithm; intensity features; local fractal-dimension feature; natural image segmentation; optimal local fractal dimension; strong-edge regions; Australia; Computer science; Computer simulation; Fractals; Humans; Image recognition; Image segmentation; Mathematics; Rough surfaces; Surface texture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
  • Conference_Location
    Kobe
  • Print_ISBN
    0-7803-5467-2
  • Type

    conf

  • DOI
    10.1109/ICIP.1999.817106
  • Filename
    817106