Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/4339
Title: Efficient rotation- and scale-invariant texture classification method based on Gabor wavelets
Authors: Xie, X
Dai, Q
Lam, KMK 
Zhao, H
Keywords: Feature extraction
Gabor filters
Image classification
Image texture
Search problems
Statistical analysis
Wavelet transforms
Issue Date: Oct-2008
Publisher: SPIE and IS&T
Source: Journal of electronic imaging, Oct.-Dec. 2008, v. 17, no. 4, 043026, p. 1-7 How to cite?
Journal: Journal of electronic imaging 
Abstract: An efficient texture classification method is proposed that considers the effects of both the rotation and scale of texture images. In our method, the Gabor wavelets are adopted to extract local features of an image and the statistical properties of its gray-level intensities are used to represent the global features. Then, an adaptive, circular orientation normalization scheme is proposed to make the feature invariant to rotation, and an elastic cross-frequency searching mechanism is devised to reduce the effect of scaling. Our method is evaluated based on the Brodatz album and the Outex database, and the experimental results show that it outperforms the traditional algorithms.
URI: http://hdl.handle.net/10397/4339
ISSN: 1017-9909
DOI: 10.1117/1.3050071
Rights: Copyright 2008 Society of Photo-Optical Instrumentation Engineers and IS&T. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
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