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Pattern Recognition and Image Analysis

, Volume 21, Issue 4, pp 754–758 | Cite as

Multimodal biometrics: Empirical study of performance-throughput trade-off

  • O. UshmaevEmail author
  • I. Sinitsyn
Application Problems

Abstract

The paper briefly describes results of empirical study on performance (as measured by ROC) and throughput (as measured by number of matches per sec) of multimodal biometrics. We use cascaded multimodal biometric identification. Experiments show that cascaded multimodal biometric fusion improves both throughput and performance.

Key words

multimodal biometrics 

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References

  1. 1.
    A. Ross and N. Poh, “Multibiometric: Overview, Case Studies, and Open Issues,” in Handbook of Remote Biometrics, Ed. by M. Tistarelli, et al. (Springer, 2009), pp. 273–292.Google Scholar
  2. 2.
    P. Griffin, “Optimal Biometric Fusion for Identy Verification,” Identix Research Tech. Rep. No. RDNJ-03-0064 (2004).Google Scholar
  3. 3.
    K. Nandakumar, Y. Chen, S. C. Dass, and A. K. Jain, “Likelihood Ratio Based Biometric Score Fusion,” IEEE Trans. Pattern Anal. Mach. Intell. 30(2), 342–347 (2008).CrossRefGoogle Scholar
  4. 4.
    S. O. Novikov and O. S. Ushmaev, “Biometric Fusion: Robust Approach,” in Proc. 2nd Workshop on Multimodal User Authentication (Toulouse, 2006), Available from: http//mmua.cs.ucsb.edu/MMUA2006/Papers/127.pdf
  5. 5.
    L. I. Kuncheva, Combining Pattern Classifiers-Methods and Algorithms (Wiley, New York, 2004).CrossRefzbMATHGoogle Scholar
  6. 6.
    E. S. Bigun, J. Bigun, B. Duc, and S. Fischer, “Expert Conciliation for Multimodal Person Authentication Systems Using Bayesian Statistics,” in Proc. 1st Int. Conf. on Audio- and Video-Based Biometric Person Authentication (AVBPA) (Crans-Montana, 1997), 291–300.Google Scholar
  7. 7.
    A. K. Jain, K. Nandakumar, and A. Ross, “Score Normalization in Multimodal Biometric Systems,” Pattern Recogn. 8(12), 2270–2285 (2005).CrossRefGoogle Scholar
  8. 8.
    J. Kittler, N. Poh, O. Fatukasi, K. Messer, K. Kryszczuk, J. Richiardi, and A. Drygajlo, “Quality Dependent Fusion of Intramodal and Multimodal Biometric Experts,” in Proc. SPIE Defense and Security Symp., Workshop on Biometric Technology for Human Identification (Orlando, 2007), Vol. 6539.Google Scholar
  9. 9.
    J. Neyman and E. S. Pearson, “On the Problem of the Most Efficient Tests of Statistical Hypotheses,” Phil. Trans. Roy. Soc. L. Ser. A 231, 289–337 (1933).CrossRefGoogle Scholar
  10. 10.
  11. 11.
    NIST Biometric Scores Set, Release 1, Available from: http://www.itl.nist.gov/iad/894.03/biometricscores/

Copyright information

© Pleiades Publishing, Ltd. 2011

Authors and Affiliations

  1. 1.Institute of Informatics Problem, RASMoscowRussia

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