A multiresolution texture gradient method for unsupervised segmentation
Hsu, Tao-I, Kuo, Jiann Ling and Wilson, Roland. (2000) A multiresolution texture gradient method for unsupervised segmentation. Pattern Recognition, Volume 33 (Number 11). pp. 1819-1833. ISSN 0031-3203Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/S0031-3203(99)00177-6
A texture segmentation algorithm is described, which is designed using a cooperative algorithm within the Multiresolution Fourier Transform (MFT) (Wilson et al., IEEE Trans. Inform. Theory 38(2) (1992) 674-690) framework. The magnitude spectrum of the MFT is employed as feature space wherein the detection of texture boundaries is estimated by means of the combination of boundary information and region properties. A pre-smoothing process is first applied to the MFT magnitudes to reduce the texture fluctuations followed by Sobel operator performed on the MFT magnitudes to give a texture boundary estimate. The refinement of the boundary estimate is accomplished by utilizing both boundary link probabilities and region link probability in an iterative manner. Results on a number of synthetic and natural textures that illustrate the effectiveness of the scheme are presented.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
T Technology > TK Electrical engineering. Electronics Nuclear engineering
|Divisions:||Faculty of Science > Computer Science|
|Journal or Publication Title:||Pattern Recognition|
|Official Date:||November 2000|
|Number of Pages:||15|
|Page Range:||pp. 1819-1833|
|Access rights to Published version:||Restricted or Subscription Access|
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