Fingerprint liveness detection based on multiple image quality features

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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. © 2011 Springer-Verlag.

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APA

Jin, C., Li, S., Kim, H., & Park, E. (2011). Fingerprint liveness detection based on multiple image quality features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6513 LNCS, pp. 281–291). Springer Verlag. https://doi.org/10.1007/978-3-642-17955-6_21

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