Personal Recognition Using Single-Sensor Multimodal Hand Biometrics

  • Andreas Uhl
  • Peter Wild
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5099)


Single-sensor approaches to multimodal biometric authentication targeting the human hand in multiple-matcher scenarios provide higher security in terms of accuracy and resistance to biometric system attacks than unimodal systems. This paper introduces a novel multimodal hand biometric system using palmar images acquired by a commercially available flatbed scanner. Hence, the presented approach to personal recognition is independent of specific biometric sensors, such as fingerprint readers or palmprint scanners. Experimental results with a minimum half total error rate of 0.003% using a database of 443 hand images will illustrate the performance improvement when hand-geometry, fingerprint and palmprint-based features are combined.


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  1. 1.
    Jain, A.K., Pankanti, S., Prabhakar, S., Hong, L., Ross, A.: Biometrics: A grand challenge. In: Proceedings of the 17th International Conference on Pattern Recognition, pp. 935–942 (2004)Google Scholar
  2. 2.
    Kumar, A., Zhang, D.: Combining fingerprint, palmprint and hand-shape for user authentication. In: Proceedings of the 18th International Conference on Pattern Recognition, pp. 549–552 (2006)Google Scholar
  3. 3.
    Rowe, R.K., Uludag, U., Demirkus, M., Parthasaradhi, S., Jain, A.K.: A multispectral whole-hand biometric authentication system. In: Proceedings of Biometrics Symposium, pp. 1–6 (2007)Google Scholar
  4. 4.
    Ross, A.A., Jain, A.K.: Information fusion in biometrics. Pattern Recognition Letters 24, 2115–2125 (2003)CrossRefGoogle Scholar
  5. 5.
    InfoTrends, Inc.: Scanner market reaches maturity - penetration nearing one third of U.S. PC households (2001),
  6. 6.
    Liao, P.S., Chen, T.S., Chung, P.C.: A fast algorithm for multilevel thresholding. Journal of Information Science and Engineering 17(5), 713–727 (2001)Google Scholar
  7. 7.
    Sobottka, K., Pitas, I.: Extraction of facial regions and features using color and shape information. In: Proceedings of the 13th International Conference on Pattern Recognition, pp. 421–425 (1996)Google Scholar
  8. 8.
    Yörük, E., Dutagaci, H., Sankur, B.: Hand biometrics. Image and Vision Computing 24(5), 483–497 (2006)CrossRefGoogle Scholar
  9. 9.
    Kumar, A., Wong, D.C.M., Shen, H.C., Jain, A.K.: Personal verification using palmprint and hand geometry biometric. In: Proceedings of the 4th International Conference on Audio- and Video-Based Biometric Person Authentication, pp. 668–678 (2003)Google Scholar
  10. 10.
    Zhang, D.: Palmprint authentication. Kluwer Academic Publishers, Dordrecht (2004)Google Scholar
  11. 11.
    Yörük, E., Konukoglu, E., Sankur, B., Darbon, J.: Shape-based hand recognition. IEEE Transactions on Image Processing 15, 1803–1815 (2006)CrossRefGoogle Scholar
  12. 12.
    Uhl, A., Wild, P.: Personal identification using eigenfeet, ballprint and foot geometry biometrics. In: Proceedings of the IEEE First International Conference on Biometrics: Theory, Applications, and Systems, pp. 1–6 (2007)Google Scholar
  13. 13.
    NIST: Fingerprint Image Software 2 (2004),
  14. 14.
    Ribaric, S., Fratric, I.: A biometric identification system based on eigenpalm and eigenfinger features. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(11), 1698–1709 (2005)CrossRefGoogle Scholar
  15. 15.
    Zuiderveld, K.: Contrast limited adaptive histogram equalization. In: Graphics gems IV, San Diego, CA, USA, pp. 474–485. Academic Press Professional, Inc, London (1994)Google Scholar
  16. 16.
    Turk, M., Pentland, A.: Eigenfaces for Recognition. Journal of Cognitive Neuroscience 3(1), 71–86 (1991)CrossRefGoogle Scholar
  17. 17.
    Pierrot, J., Lindberg, J., Koolwaaij, J., Hutter, H.P., Genoud, D., Blomberg, M., Bimbot, F.: A comparison of a priori threshold setting procedures for speaker verification in the CAVE project. In: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, pp. 125–128 (1998)Google Scholar
  18. 18.
    Cheung, K.H., Kong, A., Zhang, D., Kamel, M., You, J.: Does eigenpalm work? a system and evaluation perspective. In: Proceedings of the 18th International Conference on Pattern Recognition, pp. 445–448 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Andreas Uhl
    • 1
  • Peter Wild
    • 1
  1. 1.Department of Computer SciencesUniversity of SalzburgSalzburgAustria

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