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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Goh, A., Ngo, D.: Computation of Cryptographic Keys from Face Biometrics. Communications and Multimedia Security, 1–13 (2003)
Teh, C.H., Chin, R.T.: On Image Analysis by the Methods of Moments. IEEE Trans. Pattern Analysis Machine Intell 10, 496–512 (1998)
Mukundan, R., Ramakrishnan, K.R.: Moment Functions in Image Analysis – Theory and Applications. World Scientific Publishing, Singapore (1998)
Fukunaga, K.: Introduction to Statistical Pattern Recognition, 2nd edn. Academic, New York (1991)
Swets, D.L., Weng, J.: Using Discriminant Eigenfeatures for Image Retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence 18, 831–836 (1996)
Pang, Y.H., Andrew, T.B.J., David, N.C.L.: A Hybrid Moments and Fisher’s Linear Discriminant in face Recognition. In: International Conference on Robotics, Vision, Information and Signal Processing, pp. 581–585 (2005) ISBN:983-3391-15-X
OVL face database, http://www.uk.research.att.com/facedatabase.html
PF01 face database, http://nova.postech.ac.kr/archives/imdb.html
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
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
eBook Packages: Computer ScienceComputer Science (R0)