A new approach to fake finger detection based on skin elasticity analysis

Authors:
Jia Jia;Lianhong Cai;Kaifu Zhang;Dawei Chen
Affiliations:
Key Laboratory of Pervasive Computing, Tsinghua University, Ministry of Education, Beijing, P. R. China;Key Laboratory of Pervasive Computing, Tsinghua University, Ministry of Education, Beijing, P. R. China;Key Laboratory of Pervasive Computing, Tsinghua University, Ministry of Education, Beijing, P. R. China;Key Laboratory of Pervasive Computing, Tsinghua University, Ministry of Education, Beijing, P. R. China
Venue:
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Year:
2007

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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.