The Symbiotic Relationship of Parts and Monolithic Face Representations in Verification
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 5 - Volume 05
Journal of Cognitive Neuroscience
Robust features for frontal face authentication in difficult image conditions
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
A GMM parts based face representation for improved verification through relevance adaptation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Likelihood-ratio-based biometric verification
IEEE Transactions on Circuits and Systems for Video Technology
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Anti-spoofing protection of biometric systems is always a serious issue in real-life applications of an automatic personal verification system. Despite the fact that face image is the most common way of identifying persons and one of the most popular modalities in automatic biometric authentication, little attention has been given to the spoof resistance of face verification algorithms. In this paper, we discuss how a system based on DCT features with a likelihood-ratio-based classifier can be easily spoofed by adding white Gaussian noise to the test image. We propose a strategy to address this problem by measuring the quality of the test image and of the extracted features before making a verification decision.