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An Adaptive Contrast Enhancement Method for Palm Vein Image

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Biometric Recognition (CCBR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10568))

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Abstract

Contrast enhancement plays an important role in palm vein image processing applications. However, the over enhancement of noise the commonly used enhancement method produces in relatively homogeneous regions is still a challenging problem. This paper proposes a low-complexity gray-level transformation method for this contrast enhancement problem. Firstly, we calculate a grid size based on the image’s dimension and extract the high frequency from each patch as a weighting matrix. Then we construct a Gaussian model to express the expected contrast-stretching ratio based on the analysis of patch’s high-frequency distribution. Finally, we use the intensity of each pixel as an index to find its mapping at the four closest neighboring grid points and then interpolate among these values to get the gray scale transformation. Experimental results for some of the widely accepted criterions demonstrate its superiority to the conventional contrast enhancement techniques in enhancement performance and anti-noise capability.

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Acknowledgements

This work was supported by the Special Scientific Research Fund of Meteorological Public Welfare Profession of China (No. GYHY201106002-03), the Fundamental Research Funds for the Central Universities of China (No. JB140315), National Natural Science Foundation of China No. 31401285 and No. 61475163, the National Natural Science Foundation of Anhui No. 1508085QC65 and No. 1608085QF127.

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Authors and Affiliations

  1. Institute of Technology Innovation, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230088, Anhui, China

    Xiongwei Sun, Zede Zu, Shouguo Zheng & Xinhua Zeng

  2. Department of Computer Engineering, Anhui Sanlian University, Hefei, 230601, China

    Xiubo Ma

  3. Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, 230031, Anhui, China

    Xiongwei Sun & Chunyi Wang

Authors
  1. Xiongwei Sun
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  2. Xiubo Ma
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  3. Chunyi Wang
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  4. Zede Zu
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  5. Shouguo Zheng
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  6. Xinhua Zeng
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Corresponding author

Correspondence to Xiongwei Sun .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jie Zhou

  2. Beihang University, Beijing, China

    Yunhong Wang

  3. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  4. Computing and Technology, Chinese Academy of Sciences, Beijing, China

    Yong Xu

  5. Shenzhen University, Shenzhen, China

    Linlin Shen

  6. Tsinghua University, Beijing, China

    Jianjiang Feng

  7. Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

  8. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Yu Qiao

  9. Graduate School at Shenzhen, Tsinghua University, Shenzhen, China

    Zhenhua Guo

  10. Shenzhen University, Shenzhen, China

    Shiqi Yu

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Sun, X., Ma, X., Wang, C., Zu, Z., Zheng, S., Zeng, X. (2017). An Adaptive Contrast Enhancement Method for Palm Vein Image. In: Zhou, J., et al. Biometric Recognition. CCBR 2017. Lecture Notes in Computer Science(), vol 10568. Springer, Cham. https://doi.org/10.1007/978-3-319-69923-3_26

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  • DOI: https://doi.org/10.1007/978-3-319-69923-3_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69922-6

  • Online ISBN: 978-3-319-69923-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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