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Biometric bits extraction through phase quantization based on feature level fusion

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Abstract

Biometric bits extraction has emerged as an essential technique for the study of biometric template protection as well as biometric cryptosystems. In this paper, we present a non-invertible but revocable bits extraction technique by means of quantizing the facial data from two feature extractors in the phase domain, which we coin as aligned feature-level fusion phase quantization (AFPQ). In this technique, we utilize helper data to achieve the revocability requirement of bits extraction. The feature averaging and remainder normalization technique are integrated with the helper data to reduce feature variance within the same individual and increase the distinctiveness of bit strings of different individuals to achieve good recognition performance. A scenario in which the system is compromised by an adversary is also considered. As a generic technique, AFPQ can be easily extended to multiple different biometric modalities.

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References

  1. Bartlett, M. S., Movellan, J. R., & Sejnowski, T. J. (2002). Face recognition by independent component analysis. IEEE Transactions on Neural Networks, 13(6), 1450–1464.

    Article  Google Scholar 

  2. Buciu, I., & Pitas, I. (2008). Understanding complex systems. In Organic computing (pp. 303–320). Berlin: Springer. ISBN 978-3-540-77656-7.

    Chapter  Google Scholar 

  3. Burton, A. M., Jenkins, R., Hancock, P. J. B., & White, D. (2005). Robust representations for face recognition: the power of averages. Cognitive Psychology, 51(3), 256–284.

    Article  Google Scholar 

  4. Chang, Y.-J., Zhang, W., & Chen, T. (2004). Biometrics-based cryptographic key generation. In IEEE international conference on multimedia and expo, 2004. ICME 2004 (Vol. 3, pp. 2203–2206).

  5. Chen, C., Veldhuis, R. N. J., Kevenaar, T. A. M., & Akkermans, A. H. M. (2007). Multi-bits biometric string generation based on the likelihood ratio. In First IEEE international conference on biometrics: theory, applications, and systems, BTAS.

  6. Chen, B., & Wornell, G. W. (2001). Quantization index modulation: a class of provably good methods for digital watermarking and information embedding. IEEE Transactions on Information Theory, 47(4), 1423–1443.

    Article  Google Scholar 

  7. Daugman, J. (2006). Probing the uniqueness and randomness of IrisCodes: results from 200 billion Iris pair comparisons. Proceedings of the IEEE, 94(11), 1927–1935.

    Article  Google Scholar 

  8. Georghiades, A. S., Belhumeur, P. N., & Kriegman, D. J. (2001). From few to many: illumination cone models for face recognition under variable lighting and pose. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(6), 643–660. http://vision.ucsd.edu/~leekc/ExtYaleDatabase/ExtYaleB.html.

    Article  Google Scholar 

  9. Golic, J. D., & Baltatu, M. (2008). Entropy analysis and new constructions of biometric key generation systems. IEEE Transactions on Information Theory, 54(5), 2026–2040.

    Article  Google Scholar 

  10. Han, Q., Wang, Z., & Xiamu, N. (2006). A non-uniform quantizing approach to protect biometric templates. In International conference on intelligent information hiding and multimedia signal processing, IIH-MSP ’06 (pp. 693–698).

  11. Jenkins, R., & Burton, A. M. (2008). 100% accuracy in automatic face recognition. Science, 319(5862), 435.

    Article  Google Scholar 

  12. Kong, B., Cheung, K., Zhang, D., Kamel, M., & You, J. (2006). An analysis of biohashing and its variants. Pattern Recognition, 39(7), 1359–1368.

    Article  Google Scholar 

  13. Lee, K. C., Ho, J., & Kriegman, D. (2005). Acquiring linear subspaces for face recognition under variable lighting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(5), 684–698.

    Article  Google Scholar 

  14. Lee, D. D., & Seung, H. S. (1999). Learning the parts of objects by non-negative matrix factorization. Nature, 401, 788–791.

    Article  Google Scholar 

  15. Linnartz, J.-P., & Tuyls, P. (2003). New shielding functions to enhance privacy and prevent misuse of biometric templates. In AVBPA (pp. 393–402).

  16. Lumini, A., & Nanni, L. (2007). An improved BioHashing for human authentication. Pattern Recognition, 40(3), 1057–1065.

    Article  Google Scholar 

  17. Maio, D., & Nanni, L. (2004). Multihashing, human authentication featuring biometrics data and tokenized random number: A case study. In FVC2004.

  18. Nanni, L., & Lumini, A. (2008). Local binary patterns for a hybrid fingerprint matcher. Pattern Recognition, 41(11), 3461–3466.

    Article  Google Scholar 

  19. Ratha, N., Connell, J., & Bolle, R. (2001). Enhancing security and privacy in biometrics-based authentication systems. IBM Systems Journal, 40(3), 614–634.

    Article  Google Scholar 

  20. Schneier, B. (1999). Inside risks: the uses and abuses of biometrics. Communications of the ACM, 42(8), 136.

    Article  Google Scholar 

  21. Sim, T., Baker, S., & Bsat, M. (2003). The CMU pose, illumination, and expression database. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(12), 1615–1618.

    Article  Google Scholar 

  22. Teoh, A. B. J., Connie, T., Ngo, D., & Ling, C. (2006). Remarks on BioHash and its mathematical foundation. Information Processing Letters, 100(4), 145–150.

    Article  Google Scholar 

  23. Teoh, A. B. J., Goh, A., Ngo, D.. & Ling, C.. (2006). Random multispace quantisation as an analytic mechanism for biohashing of biometric and random identity inputs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(12), 1892–1901.

    Article  Google Scholar 

  24. Teoh, A. B. J., Kuan, Y. W., & Lee, S. (2008). Cancellable biometrics and annotations on BioHash. Pattern Recognition, 41(6), 2034–2044.

    Article  Google Scholar 

  25. Teoh, A., Ngo, D., & Goh, A. (2004). Biohashing: two factor authentication featuring fingerprint data and tokenised random number. Pattern Recognition, 37(11), 2245–2255.

    Article  Google Scholar 

  26. Teoh, A. B. J., & Toh, K.-A. (2008). Secure biometric-key generation with biometric helper. In The 3rd IEEE conference on industrial electronics and applications (ICIEA 2008) (pp. 2145–2150).

  27. Turk, M. A., & Pentland, A. P. (1991). Eigenfaces for recognition. Cognitive Neuroscience, 3(1), 71–86.

    Article  Google Scholar 

  28. Tuyls, P., Akkermans, A. H. M., Kevenaar, T. A. M., Schrijen, G. J., Bazen, A. M., & Veldhuis, R. N. J. (2005). Practical biometric authentication with template protection. In International conference on audio- and video-based biometric person authentication, AVBPA (Vol. 3546, pp. 436–446).

  29. Uludag, U., Pankanti, S., Prabhakar, S., & Jain, A. K. (2004). Biometric cryptosystems: issues and challenges. Proceedings of the IEEE, 92(6), 948–960.

    Article  Google Scholar 

  30. Vielhauer, C., & Steinmetz, R. (2004). Handwriting: feature correlation analysis for biometric hashes. EURASIP Journal on Applied Signal Processing, 2004(4), 542–558. Special issue on Biometric Signal Processing.

    Article  Google Scholar 

  31. Yip, W. K., Teoh, A. B. J., & Ngo, D. C. L. (2007). Secure hashing of dynamic hand signatures using wavelet-Fourier compression with BioPhasor mixing and 2N discretization. EURASIP Journal on Advances in Signal Processing, 2007, 59125. 8 pages.

    Google Scholar 

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Biometrics Engineering Research Center (BERC), Yonsei University, Seoul, Republic of Korea

    Hyunggu Lee, Andrew Beng Jin Teoh & Jaihie Kim

Authors
  1. Hyunggu Lee
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  2. Andrew Beng Jin Teoh
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  3. Jaihie Kim
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Correspondence to Jaihie Kim.

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Lee, H., Teoh, A.B.J. & Kim, J. Biometric bits extraction through phase quantization based on feature level fusion. Telecommun Syst 47, 255–273 (2011). https://doi.org/10.1007/s11235-010-9317-z

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