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Palmprint and Palm Vein Multimodal Fusion Biometrics Based on MMNBP

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Biometric Recognition (CCBR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9967))

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Abstract

This paper presents a multi-biometrics recognition method based on the fusion of palmprint and palm vein. Firstly, the traditional LBP method is improved, a novel algorithm called neighbor based binary pattern (NBP) is presented, which uses the relationship of gray value between adjacent pixels in the local area to encode the image. Secondly, the images of palm vein and palmprint are subdivided into several uniform size blocks, the gray mean value of each block is calculated. Furtherly, the multi-block mean image is encoded by the NBP method, which is called multi-block mean neighbor based binary pattern (MMNBP), and the feature fusion operation is implemented. Finally, the Hamming distance is used for matching. The comparison experiments are carried out with the current typical and popular approaches in the PolyU contact public database and self-built non-contact database. The experimental results indicate the superiority and effectiveness of the approach, which has good application prospect.

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Acknowledgement

This work is supported by (1) General Scientific Research Project of Liaoning Provincial Committee of Education (L2014132); (2) Natural Science Foundation of Liaoning Province of China (2015020100).

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Authors and Affiliations

  1. School of Electronic and Information Engineering, Liaoning Technical University, Huludao, 125105, Liaoning, China

    Sen Lin, Ying Wang & Tianyang Xu

  2. Computer Vision Group, Shenyang University of Technology, Shenyang, 110870, Liaoning, China

    Yonghua Tang

Authors
  1. Sen Lin
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  2. Ying Wang
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  3. Tianyang Xu
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  4. Yonghua Tang
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Corresponding author

Correspondence to Sen Lin .

Editor information

Editors and Affiliations

  1. Sichuan University , Chengdu, China

    Zhisheng You

  2. Tsinghua University , Beijing, China

    Jie Zhou

  3. Beihang University , Beijing, China

    Yunhong Wang

  4. Chinese Academy of Sciences , Beijing, China

    Zhenan Sun

  5. Chinese Academy of Sciences , Beijing, China

    Shiguang Shan

  6. Sun Yat-sen University , Guangzhou, China

    Weishi Zheng

  7. Tsinghua University , Beijing, China

    Jianjiang Feng

  8. Sichuan University , Chengdu, China

    Qijun Zhao

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© 2016 Springer International Publishing AG

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Lin, S., Wang, Y., Xu, T., Tang, Y. (2016). Palmprint and Palm Vein Multimodal Fusion Biometrics Based on MMNBP. In: You, Z., et al. Biometric Recognition. CCBR 2016. Lecture Notes in Computer Science(), vol 9967. Springer, Cham. https://doi.org/10.1007/978-3-319-46654-5_36

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  • DOI: https://doi.org/10.1007/978-3-319-46654-5_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46653-8

  • Online ISBN: 978-3-319-46654-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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