Rotation invariant texture classification based on Gabor wavelets

Xudong Xie; Jianhua Lu; Jie Gong; Ning Zhang

doi:10.1117/12.748239

15 November 2007 Rotation invariant texture classification based on Gabor wavelets

Xudong Xie, Jianhua Lu, Jie Gong, Ning Zhang

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 678804 (2007) https://doi.org/10.1117/12.748239
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Xudong Xie, Jianhua Lu, Jie Gong, and Ning Zhang "Rotation invariant texture classification based on Gabor wavelets", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 678804 (15 November 2007); https://doi.org/10.1117/12.748239

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