CONF Chingovska_IEEEBIOSIG2012_2012/IDIAP On the Effectiveness of Local Binary Patterns in Face Anti-spoofing Chingovska, Ivana Anjos, André Marcel, Sébastien EXTERNAL https://publications.idiap.ch/attachments/papers/2012/Chingovska_IEEEBIOSIG2012_2012.pdf PUBLIC https://publications.idiap.ch/index.php/publications/showcite/Chingovska_Idiap-RR-19-2012 Related documents Proceedings of the 11th International Conference of the Biometrics Special Interes Group 2012 Spoofing attacks are one of the security traits that biometric recognition systems are proven to be vulnerable to. When spoofed, a biometric recognition system is bypassed by presenting a copy of the biometric evidence of a valid user. Among all biometric modalities, spoofing a face recognition system is particularly easy to perform: all that is needed is a simple photograph of the user. In this paper, we address the problem of detecting face spoofing attacks. In particular, we inspect the potential of texture features based on Local Binary Patterns (LBP) and their variations on three types of attacks: printed photographs, and photos and videos displayed on electronic screens of different sizes. For this purpose, we introduce REPLAY-ATTACK, a novel publicly available face spoofing database which contains all the mentioned types of attacks. We conclude that LBP, with 15% Half Total Error Rate, show moderate discriminability when confronted with a wide set of attack types. REPORT Chingovska_Idiap-RR-19-2012/IDIAP On the Effectiveness of Local Binary Patterns in Face Anti-spoofing Chingovska, Ivana Anjos, André Marcel, Sébastien Biometrics Counter-Measures Local Binary Patterns Spoofing Attacks EXTERNAL https://publications.idiap.ch/attachments/reports/2012/Chingovska_Idiap-RR-19-2012.pdf PUBLIC Idiap-RR-19-2012 2012 Idiap July 2012 Spoofing attacks are one of the security traits that biometric recognition systems are proven to be vulnerable to. When spoofed, a biometric recognition system is bypassed by presenting a copy of the biometric evidence of a valid user. Among all biometric modalities, spoofing a face recognition system is particularly easy to perform: all that is needed is a simple photograph of the user. In this paper, we address the problem of detecting face spoofing attacks. In particular, we inspect the potential of texture features based on Local Binary Patterns (LBP) and their variations on three types of attacks: printed photographs, and photos and videos displayed on electronic screens of different sizes. For this purpose, we introduce REPLAY-ATTACK, a novel publicly available face spoofing database which contains all the mentioned types of attacks. We conclude that LBP, with ~15% Half Total Error Rate, show moderate discriminability when confronted with a wide set of attack types.