Machine Vision and Applications

, Volume 21, Issue 5, pp 695–711

On design and optimization of face verification systems that are smart-card based


    • Centre for Vision Speech and Signal ProcessingUniversity of Surrey
  • Josef Kittler
    • Centre for Vision Speech and Signal ProcessingUniversity of Surrey
  • Kieron Messer
    • Centre for Vision Speech and Signal ProcessingUniversity of Surrey
Original Paper

DOI: 10.1007/s00138-009-0187-x

Cite this article as:
Bourlai, T., Kittler, J. & Messer, K. Machine Vision and Applications (2010) 21: 695. doi:10.1007/s00138-009-0187-x


The optimization of a smart card face verification system is a very complex process with many key factors to consider. It involves the investigation of the effect the system parameters have on the system performance measured in terms of accuracy and speed. As the parameters involved are not independent, the search space is of exponential complexity. In practice only partial optimization is feasible with many parameters forced to take default values. We argue that the key options to optimize are image resolution or/and image pre-processing. In addition the main design issue is the degree of compression that can be applied to the probe image before it is transmitted to the smart card. In this work we investigate different optimization strategies by considering both image compression and image resolution, and demonstrate that both the system performance and speed of access can be improved by the jointly optimized parameter setting and the level of probe compression. The experimental results obtained on the XM2VTS database suggest that the choice of one strategy over another is a matter of the time available for the system design, system performance, and response time.


Face verificationSmart cardSystem designOptimization
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Copyright information

© Springer-Verlag 2009