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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 |
Issue Date: | Oct-2008 | Source: | Journal of electronic imaging, Oct.-Dec. 2008, v. 17, no. 4, 043026, p. 1-7 | 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. | Keywords: | Feature extraction Gabor filters Image classification Image texture Search problems Statistical analysis Wavelet transforms |
Publisher: | SPIE-International Society for Optical Engineering | Journal: | Journal of electronic imaging | ISSN: | 1017-9909 | EISSN: | 1560-229X | 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. |
Appears in Collections: | Journal/Magazine Article |
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Xie_Efficient_rotation_scale.pdf | 429.14 kB | Adobe PDF | View/Open |
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