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Proceedings Paper

Rotation invariant texture classification based on Gabor wavelets
Author(s): Xudong Xie; Jianhua Lu; Jie Gong; Ning Zhang
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Paper Abstract

In this paper, an efficient rotation invariant texture classification method is proposed. Comparing with the previous texture classification method, which is also based on Gabor wavelets, two modifications are made in this paper. Firstly, an adaptive circular orientation normalization scheme is proposed. Because both the effects of orientation and frequency to Gabor features are considered, our method can effectively eliminate the disturbance from inter-frequency, and therefore has the ability to reduce the effect of image rotation. Secondly, besides the Gabor features, which mainly represent the local texture information of an image, the statistical property of the intensity values of an image is also used for texture classification in our algorithm. Our method is evaluated based on the Brodatz album, and the experimental results show that it outperforms the traditional algorithms.

Paper Details

Date Published: 15 November 2007
PDF: 6 pages
Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 678804 (15 November 2007); doi: 10.1117/12.748239
Show Author Affiliations
Xudong Xie, Tsinghua Univ. (China)
Jianhua Lu, Tsinghua Univ. (China)
Jie Gong, China Electronic System Engineering Co. (China)
Ning Zhang, China Electronic System Engineering Co. (China)

Published in SPIE Proceedings Vol. 6788:
MIPPR 2007: Pattern Recognition and Computer Vision
S. J. Maybank; Mingyue Ding; F. Wahl; Yaoting Zhu, Editor(s)

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