Fingerprint liveness detection based on multiple image quality features

Authors:
Changlong Jin;Shengzhe Li;Hakil Kim;Ensoo Park
Affiliations:
School of Information and Communication Engineering, INHA University, Incheon, Korea;School of Information and Communication Engineering, INHA University, Incheon, Korea;School of Information and Communication Engineering, INHA University, Incheon, Korea;School of Information and Communication Engineering, INHA University, Incheon, Korea
Venue:
WISA'10 Proceedings of the 11th international conference on Information security applications
Year:
2010

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Abstract

Recent studies have shown that the conventional fingerprint recognition systems are vulnerable to fake attacks, and there are many existing systems that need to update their anti-spoofing capability inexpensively. This paper proposes an image quality-based fake detection method to address this problem. Three effective fake/live quality measures, spectral band energy, middle ridge line and middle valley line, are extracted firstly, and then, these features are fused and tested on a fake/live dataset using SVM and QDA classifiers. Experimental results demonstrate that the proposed method is promising in increasing the security of the existing fingerprint authentication system by only updating the software.