Machine Vision and Applications

, Volume 20, Issue 4, pp 225–242 | Cite as

Designing a smart-card-based face verification system: empirical investigation

  • Thirimachos BourlaiEmail author
  • Josef Kittler
  • Kieron Messer
Original Paper


To design a smart card face verification system many key factors have to be considered. In this study we discuss the implementation of such a system and investigate the trade-off between performance and computational complexity. Two optimisation strategies are considered. The studies are performed on the XM2VTS, BANCA and FERET databases demonstrating that the judicial choice of spatial and grey level resolution as well as JPEG compression settings for face representation can optimise verification error. We show that the use of a fixed precision data type does not affect system performance very much but can speed up the verification process. Since the optimisation framework of such a system is very complicated, the search space is simplified by applying some heuristics to the problem. In the adopted suboptimal search strategy one or two parameters are optimised at a time. The system was evaluated using half total error rate (HTER) as the performance criterion. The conclusions reached on different databases indicate that the selection of the optimum parameters may call for different optimum operating points.


Face verification Smart card System design Optimisation 


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  1. 1.
    Bailly-Baillire, E., Bengio, S., Bimbot, F., Hamouz, M., Kittler, J., Mariethoz, J., Matas, J., Messer, K., Popovici, V., Poree, F., Ruiz, B., Thiran, J.-Ph.: The banca database and evaluation protocol. AVBRA (2003)Google Scholar
  2. 2.
    Bourlai, T., Kittler, J., Messer, K.: Jpeg compression effects on a smart card face verification system. In: IAPR Conference on Machine Vision Applications, 16–18 May 2005Google Scholar
  3. 3.
    Bourlai, T., Kittler, J., Messer, K.: On optimisation of smart card face verification systems. AVSS (Nov 2006)Google Scholar
  4. 4.
    Bourlai, T., Messer, K., Kittler, J.: Face verification system architecture using smart cards. In: Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, vol. 1, pp. 793–796, (23–26 August 2004)Google Scholar
  5. 5.
    Bourlai, T., Messer, K., Kittler, J.: Performance versus computational complexity trade-off in face verification. In: Proceedings of the International Conference on Biometric Authentication, ICBA 2004, pp. 169–177, 15–17 July 2004Google Scholar
  6. 6.
    Bourlai, T., Messer, K., Kittler, J.: Scenario based performance optimisation in face verification using smart cards. AVBPA 2005, 22–25 July 2005Google Scholar
  7. 7.
    Czyz, J., Vandendorpe, L.: Evaluation of lda-based face verification with respects to available computational resources. In: PRIS April 2002Google Scholar
  8. 8.
    Dugelay, J.L., Junqua, J.C., Kotropoulos, C., Kuhn, R., Perronnin, F., Pitas, I.: Recent advances in biometric person authentication. ICASSP (special session on biometrics), Orlando, Florida, May, (2002)Google Scholar
  9. 9.
    Copyright Smart Card Alliance Inc.: Smart card and biometrics in privacy-sensitive secure personal identification systems. A Smart Card Alliance white paper,, May 2002
  10. 10.
    Li, Y.P., Kittler, J., Matas, J.: Analysis of the lda-based matching schemes for face verification. In: Proceedings of British Machine Vision Conference 2000 (2000)Google Scholar
  11. 11.
    Li, Y.P., Kittler, J., Matas, J.: Face verification using client specific fisher faces. In: Kent, J.T., Aykroyd, R.G. (eds.) Proceedings of the International conference on The Statistics of Directions, Shapes and Images, pp. 63–66, September 2000Google Scholar
  12. 12.
    Messer, K., Matas, J., Kittler, J., Luettin, J., Maitre, G.: Xm2vtsdb: the extended m2vts database. AVBRA, pp. 72–77, March 1999Google Scholar
  13. 13.
    Osborne, M., Ratha, N.K.: A jc-bioapi compliant smart card with biometrics for secure access control. AVBRA pp. 903–910 June 2003Google Scholar
  14. 14.
    Phillips, P.J., McCabe, M., Chellappa, R.: Biometric image processing and recognition. EUSIPCO (1998)Google Scholar
  15. 15.
    Phillips, P.J., Moon, H.J., Rizvi, S.A., Rauss, P.J.: The feret evaluation methodology for face-recognition algorithms. IEEE Trans. Pattern Anal. Machine Intell. (PAMI) 22(10), 1090–1104, October 2000Google Scholar
  16. 16.
    Rankl W., Effing W.: Smart card handbook.. Wiley, New York (2000)Google Scholar
  17. 17.
    Sanchez-Reillo, R.: Including biometric authentication in a smart card operating system. AVBPA, pp. 342–347, June 2001Google Scholar
  18. 18.
    Sanchez-Reillo, R., Mengibar-Pozo, L., Sanchez-Avila, C.: Microprocessor smart cards with fingerprint used authentication. IEEE AESM, pp. 22–24, March 2003Google Scholar
  19. 19.
    Sanchez-Reillo R., Sanchez-Avila C.: Fingerprint verification using smart cards for access control systems. IEEE AESM 17(9), 12–15 (2002)Google Scholar
  20. 20.
    Turk M., Pentland A.: Eigenfaces for recognition. Cogn. Neurosci. IEEE PAMI 3(1), 71–86 (1991)CrossRefGoogle Scholar
  21. 21.
    Zhao, W., Chellappa, R., Rosenfeld, A., Phillips, P.: Face recognition: a literature survey. UMD CfAR Technical Report CAR-TR-948 (2000)Google Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Thirimachos Bourlai
    • 1
    Email author
  • Josef Kittler
    • 1
  • Kieron Messer
    • 1
  1. 1.Centre for Vision Speech and Signal ProcessingUniversity of SurreyGuildford, SurreyUK

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