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A New Approach to Fake Finger Detection Based on Skin Elasticity Analysis

  • Jia Jia
  • Lianhong Cai
  • Kaifu Zhang
  • Dawei Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)

Abstract

This work introduces a new approach to fake finger detection, based on the analysis of human skin elasticity. When a user puts a finger on the scanner surface, a sequence of fingerprint images which describes the finger deformation process is captured. Then two features which represent the skin elasticity are extracted from the image sequence: 1) the correlation coefficient of the fingerprint area and the signal intensity; 2) the standard deviation of the fingerprint area extension in x and y axes. Finally the Fisher Linear Discriminant is used to discriminate the finger skin from other materials such as gelatin. The experiments carried out on a dataset of real and fake fingers show that the proposed approach and features are effective in fake finger detection.

Keywords

Fingerprint Image Average Signal Intensity Skin Elasticity Fisher Linear Discriminant Extra Hardware 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Jia Jia
    • 1
  • Lianhong Cai
    • 1
  • Kaifu Zhang
    • 1
  • Dawei Chen
    • 1
  1. 1.Key Laboratory of Pervasive Computing (Tsinghua University), Ministry of Education, Beijing 100084P.R. China

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