標題: Face Liveness Detection Based on Skin Blood Flow Analysis
作者: Wang, Shun-Yi
Yang, Shih-Hung
Chen, Yon-Ping
Huang, Jyun-We
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
關鍵字: spoof detection;skin blood flow;block-based color moment;public domain database
公開日期: 1-Dec-2017
摘要: 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.
URI: http://dx.doi.org/10.3390/sym9120305
http://hdl.handle.net/11536/144323
ISSN: 2073-8994
DOI: 10.3390/sym9120305
期刊: SYMMETRY-BASEL
Volume: 9
Issue: 12
起始頁: 0
結束頁: 0
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