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