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Symmetry 2017, 9(12), 305; doi:10.3390/sym9120305

Face Liveness Detection Based on Skin Blood Flow Analysis

1
Department of Electrical Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan
2
Department of Mechanical and Computer-Aided Engineering, Feng Chia University, Taichung 40724, Taiwan
*
Author to whom correspondence should be addressed.
Received: 6 November 2017 / Revised: 26 November 2017 / Accepted: 1 December 2017 / Published: 7 December 2017
(This article belongs to the Special Issue Information Technology and Its Applications)
View Full-Text   |   Download PDF [4801 KB, uploaded 7 December 2017]   |  

Abstract

Face recognition systems have been widely adopted for user authentication in security systems due to their simplicity and effectiveness. However, spoofing attacks, including printed photos, displayed photos, and replayed video attacks, are critical challenges to authentication, and these spoofing attacks allow malicious invaders to gain access to the system. This paper proposes two novel features for face liveness detection systems to protect against printed photo attacks and replayed attacks for biometric authentication systems. The first feature obtains the texture difference between red and green channels of face images inspired by the observation that skin blood flow in the face has properties that enable distinction between live and spoofing face images. The second feature estimates the color distribution in the local regions of face images, instead of whole images, because image quality might be more discriminative in small areas of face images. These two features are concatenated together, along with a multi-scale local binary pattern feature, and a support vector machine classifier is trained to discriminate between live and spoofing face images. The experimental results show that the performance of the proposed method for face spoof detection is promising when compared with that of previously published methods. Furthermore, the proposed system can be implemented in real time, which is valuable for mobile applications. View Full-Text
Keywords: spoof detection; skin blood flow; block-based color moment; public domain database spoof detection; skin blood flow; block-based color moment; public domain database
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, S.-Y.; Yang, S.-H.; Chen, Y.-P.; Huang, J.-W. Face Liveness Detection Based on Skin Blood Flow Analysis. Symmetry 2017, 9, 305.

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