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
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;
Conference_Titel :
Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-5467-2
DOI :
10.1109/ICIP.1999.817106