A rotation and scale invariant texture description approach

Pengfei Xu; Hongxun Yao; Rongrong Ji; Xiaoshuai Sun; Xianming Liu

doi:10.1117/12.863520

4 August 2010 A rotation and scale invariant texture description approach

Pengfei Xu, Hongxun Yao, Rongrong Ji, Xiaoshuai Sun, Xianming Liu

Proceedings Volume 7744, Visual Communications and Image Processing 2010; 77442T (2010) https://doi.org/10.1117/12.863520
Event: Visual Communications and Image Processing 2010, 2010, Huangshan, China

Abstract

This paper presents a novel texture description approach, which is robust to variances in rotation, scale and illumination in images, to classify the texture of images. A limitation with traditional methods is that they are more or less sensitive to the mentioned changes in images. To overcome this problem, we propose a novel Local Haar Binary Pattern (LHBP) based framework to ensure invariance in global rotation, scale, and light change. Our method consists of two components: feature extraction and scale self-adaptive classification. The global rotation invariant LHBP histogram features are extracted against the variances of illumination and global rotation, and the scale self-adaptive strategy is used for optimizing the classification of different scale textures. Evaluation results on Outex and Brodatz databases illustrate the significant advantages of the proposed approach over existing algorithms.

Citation Download Citation

Pengfei Xu, Hongxun Yao, Rongrong Ji, Xiaoshuai Sun, and Xianming Liu "A rotation and scale invariant texture description approach", Proc. SPIE 7744, Visual Communications and Image Processing 2010, 77442T (4 August 2010); https://doi.org/10.1117/12.863520

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