Share Email Print

Journal of Electronic Imaging

Efficient rotation- and scale-invariant texture classification method based on Gabor wavelets
Author(s): Xudong Xie; Qionghai Dai; Kin-Man Lam; Hongya Zhao
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 1 October 2008
PDF: 7 pages
J. Electron. Imag. 17(4) 043026 doi: 10.1117/1.3050071
Published in: Journal of Electronic Imaging Volume 17, Issue 4
Show Author Affiliations
Xudong Xie, Tsinghua Univ. (China)
Qionghai Dai, Tsinghua Univ. (China)
Kin-Man Lam, The Hong Kong Polytechnic Univ. (Hong Kong, China)
Hongya Zhao, City Univ. of Hong Kong (Hong Kong, China)

© SPIE. Terms of Use
Back to Top