Fake Finger Detection Based on Thin-Plate Spline Distortion Model

  • Yangyang Zhang
  • Jie Tian
  • Xinjian Chen
  • Xin Yang
  • Peng Shi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)


This paper introduces a novel method based on the elasticity analysis of the finger skin to discriminate fake fingers from real ones. We match the fingerprints before and after special distortion and gained their corresponding minutiae pairs as landmarks. The thin-plate spline (TPS) model is used to globally describe the finger distortion. For an input finger, we compute the bending energy vector by the TPS model and calculate the similarity of the bending energy vector to the bending energy fuzzy feature set. The similarity score is in the range [0, 1], indicating how much the current finger is similar to the real finger. The method realizes fake finger detection based on the normal steps of fingerprint processing without special hardware, so it is easily implemented and efficient. The experimental results on a database of real and fake fingers show that the performance of the method is available.


fake finger distortion Thin-plate Spline model bending energy vector fuzzy feature set 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Yangyang Zhang
    • 1
  • Jie Tian
    • 1
  • Xinjian Chen
    • 1
  • Xin Yang
    • 1
  • Peng Shi
    • 1
  1. 1.Center for Biometrics and Security Research, Key Laboratory of Complex Systems, and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Graduate School of the Chinese Academy of Sciences, P.O. Box 2728 Beijing 100080, Email:tian@ieee.orgChina

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