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Chinese Conference on Biometric Recognition

CCBR 2014: Biometric Recognition pp 260–265Cite as

Finger-Vein Recognition by Using Spatial Feature Interdependence Matrix Weighted by Probability and Direction

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8833))

Abstract

The spatial feature interdependence matrix (SFIM) has been proposed for face representation, which encodes feature interdependences between local patches. However, not all patches are equally important for classification purposes. For finger-vein identification, patches that contain vein lines contribute more to classification. Inspired by this, we propose a weighted SFIM based on probability and direction (PDSFIM). Both the probability and direction of vein lines in a patch are integrated into the SFIM. The experimental results demonstrate the superiority of the proposed method after comparison with various state-of-the-art methods.

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References

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Author information

Authors and Affiliations

  1. Shenzhen Key Lab. of Information Sci&Tech/Shenzhen Engineering Lab. of IS&DRM ,Department of EE/Graduate School at Shenzhen, Tsinghua University, China

    Wenming Yang, Yichao Li, Chuan Qin & Qingmin Liao

Authors
  1. Wenming Yang
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  2. Yichao Li
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  3. Chuan Qin
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  4. Qingmin Liao
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Editor information

Editors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, 100190, Beijing, China

    Zhenan Sun

  2. Institute of Computing Technology, Chinese Academy of Sciences, No.6 Kexueyuan South Road, P.O. Box 2704, 100190, HaiDian, Beijing, China

    Shiguang Shan

  3. School of Information Science and Engineering, Shenyang University of Technology, No.111, Shenliao West Road, Economic and Technological Development Zone, 110870, Shenyang, China

    Haifeng Sang  & Weiqi Yuan  & 

  4. Software Engineering Institute, Tsinghua University, No. 1 Tsinghua Yuan, Haidian District, 100084, Beijing, China

    Jie Zhou

  5. School of Computer Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, 100191, Beijing, China

    Yunhong Wang

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© 2014 Springer International Publishing Switzerland

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Cite this paper

Yang, W., Li, Y., Qin, C., Liao, Q. (2014). Finger-Vein Recognition by Using Spatial Feature Interdependence Matrix Weighted by Probability and Direction. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_29

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  • DOI: https://doi.org/10.1007/978-3-319-12484-1_29

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12483-4

  • Online ISBN: 978-3-319-12484-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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