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Chinese Intelligent Systems Conference

CISC 2016: Proceedings of 2016 Chinese Intelligent Systems Conference pp 19–27Cite as

Local Zernike Moment and Multiscale Patch-Based LPQ for Face Recognition

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 405))

Abstract

In this paper, a novel feature extraction method combining Zernike moment with multiscale patch-based local phase quantization is introduced, which can deal with the problem of uncontrolled image conditions in face recognition, such as expressions, blur, occlusion, and illumination changes (EBOI). First, the Zernike moments are computed around each pixel other than the whole image and then double moment images are, respectively, constructed from the real and imaginary parts. Subsequently, multiscale patch-based local phase quantization descriptor is utilized for the non-overlapping patches of moment images to obtain the texture information. Afterward, the support vector machine (SVM) is employed for classification. Experimental results performed on ORL, JAFFE, and AR databases clearly show that the LZM-MPLPQ method outperforms the state-of-the-art methods and achieves better robustness against severe conditions abovementioned.

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Author information

Authors and Affiliations

  1. College of Information and Engineering, Capital Normal University, Beijing, 100048, China

    Xiaoyu Sun, Xiaoyan Fu, Zhuhong Shao, Yuanyuan Shang & Hui Ding

  2. Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, 100048, China

    Xiaoyan Fu, Zhuhong Shao, Yuanyuan Shang & Hui Ding

  3. Beijing Key Laboratory of Electronic System Reliability Technology, Capital Normal University, Beijing, 100048, China

    Yuanyuan Shang & Hui Ding

Authors
  1. Xiaoyu Sun
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  2. Xiaoyan Fu
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  3. Zhuhong Shao
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  4. Yuanyuan Shang
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  5. Hui Ding
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Corresponding author

Correspondence to Xiaoyan Fu .

Editor information

Editors and Affiliations

  1. Beihang University , Beijing, China

    Yingmin Jia

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Junping Du

  3. University of Science and Technology Beijing, Beijing, China

    Weicun Zhang

  4. Tsinghua University , Beijing, China

    Hongbo Li

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© 2016 Springer Science+Business Media Singapore

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Cite this paper

Sun, X., Fu, X., Shao, Z., Shang, Y., Ding, H. (2016). Local Zernike Moment and Multiscale Patch-Based LPQ for Face Recognition. In: Jia, Y., Du, J., Zhang, W., Li, H. (eds) Proceedings of 2016 Chinese Intelligent Systems Conference. CISC 2016. Lecture Notes in Electrical Engineering, vol 405. Springer, Singapore. https://doi.org/10.1007/978-981-10-2335-4_3

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  • DOI: https://doi.org/10.1007/978-981-10-2335-4_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2334-7

  • Online ISBN: 978-981-10-2335-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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