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Fake finger detection based on thin-plate spline distortion model

  • Yangyang Zhang*
  • , Jie Tian
  • , Xinjian Chen
  • , Xin Yang
  • , Peng Shi
  • *Corresponding author for this work
  • University of Chinese Academy of Sciences

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationAdvances in Biometrics - International Conference, ICB 2007, Proceedings
PublisherSpringer Verlag
Pages742-749
Number of pages8
ISBN (Print)9783540745488
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 International Conference on Advances in Biometrics, ICB 2007 - Seoul, Korea, Republic of
Duration: 27 Aug 200729 Aug 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4642 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2007 International Conference on Advances in Biometrics, ICB 2007
Country/TerritoryKorea, Republic of
CitySeoul
Period27/08/0729/08/07

Keywords

  • Bending energy vector
  • Distortion
  • Fake finger
  • Fuzzy feature set
  • Thin-plate Spline model

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