Abstract
This paper proposes a robust face recognition system, by providing a strong discrimination power and cancelable mechanism to biometrics data. Fisher’s Linear Discriminant uses pseudo Zernike moments to derive an enhanced feature subset. On the other hand, the revocation capability is formed by the combination of a tokenized pseudo-random data and the enhanced template. The inner product of these factors generates a user-specific binary code, face-Hash. This two-factor basis offers an extra protection layer against biometrics fabrication since face-Hash authenticator is replaceable via token replacement.
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© 2005 Springer-Verlag Berlin Heidelberg
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Pang, YH., Jin, A.T.B., Ling, D.N.C. (2005). A Robust Face Recognition System. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_173
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DOI: https://doi.org/10.1007/11589990_173
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30462-3
Online ISBN: 978-3-540-31652-7
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