Towards contactless palmprint authentication

Towards contactless palmprint authentication

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Computer Vision — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This study examines the issues related to two of the most palmprint promising approaches applied to the contactless biometric authentication and presents a performance evaluation on three different scenarios. The presence of significant scale, rotation, occlusion and translation variations in the contactless palmprint images requires the feature extraction approaches that can accommodate such within class image variations. Therefore the usage and performance of traditional palmprint feature extraction methods on contactless imaging schemes remain questionable and hence all/popular palmprint feature extraction methods may not be effective in contactless frameworks. The experimental results on more than 6000 images from three contactless databases acquired in different environments suggest that the scale invariant feature transform (SIFT) features perform significantly better for the contactless palmprint images than the promising orthogonal line ordinal features (OLOF) approach employed earlier on the more conventional touch-based palmprint imaging. The experimental results further suggest that the combination of robust SIFT matching scores along with those from OLOF can be employed to achieve more reliable performance improvement. The use of publicly available databases ensures repeatability in the experiments. Therefore this study provides a new/challenging contactless hand database acquired in uncontrolled environments for further research efforts.


    1. 1)
      • Jain, A.K., Ross, A., Pankanti, S.: `A prototype hand geometry-based verification system', Proc. 2nd Int. Conf. on Audio- and Video-Based Biometric Person Authentication, March 1999, p. 166–171.
    2. 2)
    3. 3)
    4. 4)
      • Hao, Y., Sun, Z., Tan, T., Ren, C.: `Multi-spectral palm image fusion for accurate contact-free palmprint recognition', Proc. IEEE Int. Conf. on Image Processing, ICIP 2008, 2008, p. 281–284.
    5. 5)
      • Morales, A., Ferrer, M.A., Alonso, J.B., Travieso, C.M.: `Comparing infrared and visible illumination for contactless hand based biometric scheme', Proc. 42nd Annual IEEE Int. Carnahan Conf. on Security Technology, ICCST 2008, 2008, p. 191–197.
    6. 6)
    7. 7)
      • Morales, A., Ferrer, M.A., Kumar, A.: `Improved palmprint authentication using contactless imaging', Proc. Fourth IEEE Int. Conf. on Biometrics Theory, Applications and Systems, BTAS 2010, September 2010, Washington.
    8. 8)
      • Sun, Z., Tan, T., Wang, Y., Li, S.Z.: `Ordinal palmprint representation for personal identification', Proc. IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, 2005, 1, p. 279–284.
    9. 9)
      • IITD Touchless Palmprint Database, version 1.0,
    10. 10)
      • GPDS-CL1 Database,
    11. 11)
      • Ferrer, M.A., Morales, A., Travieso, C.M., Alonso, J.B.: `Low cost multimodal biometric identification system based on hand geometry, palm and finger print texture', Proc. 41st Annual IEEE Int. Carnahan Conf. on Security Technology, 2007, p. 52–58.
    12. 12)
    13. 13)
      • Badrinath, G.S., Gupta, P.: `Palmprint verification using sift features', Proc. First Workshops on Image Processing Theory, Tools and Application, IPTA 2008, 2008, p. 1–8.
    14. 14)
      • K. Zuiderveld . (1994) Contrast limited adaptive histogram equalization.
    15. 15)
    16. 16)
    17. 17)
      • Kong, W.K., Zhang, D.: `Competitive coding scheme for palmprint verification', Proc. 17th Int. Conf. on Pattern Recognition, 2004, 1, p. 520–523.
    18. 18)
    19. 19)
    20. 20)
      • Kumar, A.: `Incorporating cohort information for reliable palmprint authentication', Proc. Sixth Indian Conf. on Computer Vision, Graphics & Image Processing, Bhubaneswar (India), December 2008, p. 112–119.
    21. 21)
    22. 22)
      • Methani, C., Namboodiri, A.M.: `Pose invariant palmprint recognition', Proc. Third Int. Conf. on Biometrics, ICB 2009, June 2009, p. 577–586.

Related content

This is a required field
Please enter a valid email address