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)

Abstract

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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  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), http://www.infotrends.com/public/Content/Press/2001/06.19.2001.html
  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), http://fingerprint.nist.gov/NFIS
  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

Personalised recommendations