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An improved LBP algorithm for texture and face classification

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Abstract

Local Binary Pattern (LBP) has achieved great success in texture classification due to its accuracy and efficiency. Traditional LBP method encodes local features by binarying the difference in local neighborhood and then represents a given image using the histogram of the binary patterns. However, it ignores the directional statistical information. In this paper, some directional statistical features—including the mean and standard deviation of the local absolute difference—are integrated into the feature extraction to improve the classification ability of the extracted features. In order to reduce estimation errors of the local absolute difference, we further utilize the least square estimate technique to optimize the weight and minimize the local absolute difference, which leads to more stable directional features. In addition, a novel rotation invariant texture classification approach is presented. Experimental results on several texture and face datasets show that the proposed approach significantly improves the classification accuracy of the traditional LBP.

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Acknowledgments

This paper is supported by “the National Natural Science Foundation of China” (No.61272109), “the Fundamental Research Funds for the Central Universities” (No.2042014kf0057) and “the Postdoctoral Science Foundation of China” (No.2012M511261). The authors would like to thank the support of the National Engineering Research Center for Multimedia Software.

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Authors and Affiliations

  1. School of Computer, Wuhan University, Wuhan, China

    Wei Yu, Lin Gan, Sha Yang, Yonggang Ding, Jun Wang & Shijun Li

  2. Department of Computer Science and Technology, Hankou University, Wuhan, China

    Sha Yang

  3. Faculty of Education, Hubei University, Wuhan, China

    Yonggang Ding

  4. School of Energy and Power Engineering, Wuhan University of Technology, Wuhan, China

    Pan Jiang

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  1. Wei Yu
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  2. Lin Gan
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  3. Sha Yang
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  4. Yonggang Ding
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  5. Pan Jiang
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  6. Jun Wang
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  7. Shijun Li
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Correspondence to Shijun Li.

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Yu, W., Gan, L., Yang, S. et al. An improved LBP algorithm for texture and face classification. SIViP 8 (Suppl 1), 155–161 (2014). https://doi.org/10.1007/s11760-014-0652-5

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