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3D Fingerprint Reconstruction and Registration Based on Binocular Structured Light

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Biometric Recognition (CCBR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14463))

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Abstract

Fingerprint recognition is assuming an increasingly pivotal role in our modern information society. Its applications span across civil domains such as door locks and mobile phone security, to more critical realms like public security and legal identification. However, traditional contact-based fingerprint recognition methods bear the drawbacks of compromising the fingerprint’s intrinsic 3D structure and being susceptible to contamination. In contrast, prevailing non-contact 3D fingerprint collection methods encounter challenges related to limited coverage area and the complexity of capturing an absolute height 3D representation. In light of these issues, we present a novel approach: a 3D fingerprint reconstruction and registration technique rooted in high-precision binocular structured light. This innovative method promises to deliver comprehensive and remarkably precise 3D fingerprint representations, addressing the limitations of current methodologies.

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Authors and Affiliations

  1. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China

    Jingjing Wang, Yuping Ye, Wei Cao, Juan Zhao & Zhan Song

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Jingjing Wang, Yuping Ye, Wei Cao, Juan Zhao & Zhan Song

Authors
  1. Jingjing Wang
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  2. Yuping Ye
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  3. Wei Cao
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  4. Juan Zhao
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  5. Zhan Song
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Corresponding author

Correspondence to Zhan Song .

Editor information

Editors and Affiliations

  1. Hefei University of Technology, Hefei, China

    Wei Jia

  2. South China University of Technology, Guangzhou, China

    Wenxiong Kang

  3. China University of Mining and Technology, Xuzhou, China

    Zaiyu Pan

  4. Shandong University, Jinan, China

    Xianye Ben

  5. China University of Mining and Technology, Xuzhou, China

    Zhengfu Bian

  6. Southern University of Science and Technology, Shenzhen, China

    Shiqi Yu

  7. Chinese Academy of Sciences, Beijing, China

    Zhaofeng He

  8. China University of Mining and Technology, Xuzhou, China

    Jun Wang

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Wang, J., Ye, Y., Cao, W., Zhao, J., Song, Z. (2023). 3D Fingerprint Reconstruction and Registration Based on Binocular Structured Light. In: Jia, W., et al. Biometric Recognition. CCBR 2023. Lecture Notes in Computer Science, vol 14463. Springer, Singapore. https://doi.org/10.1007/978-981-99-8565-4_8

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  • DOI: https://doi.org/10.1007/978-981-99-8565-4_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8564-7

  • Online ISBN: 978-981-99-8565-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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