Skip to main content

Palmprint Based Verification System Using SURF Features

  • Conference paper
Contemporary Computing (IC3 2009)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 40))

Included in the following conference series:

Abstract

This paper describes the design and development of a prototype of robust biometric system for verification. The system uses features extracted using Speeded Up Robust Features (SURF) operator of human hand. The hand image for features is acquired using a low cost scanner. The palmprint region extracted is robust to hand translation and rotation on the scanner. The system is tested on IITK database of 200 images and PolyU database of 7751 images. The system is found to be robust with respect to translation and rotation. It has FAR 0.02%, FRR 0.01% and accuracy of 99.98% and can be a suitable system for civilian applications and high-security environments.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ribaric, S., Fratric, I.: A biometric identification system based on Eigenpalm and Eigenfinger features. IEEE Trans. on Pattern Analysis Machine Intelligence 27(11), 1698–1709 (2005)

    Article  Google Scholar 

  2. Zhang, D., Kong, W.-K., You, J., Wong, M.: Online palmprint identification. IEEE Transaction on Pattern Analysis and Machine Intelligence 25(9), 1041–1050 (2003)

    Article  Google Scholar 

  3. Kumar, A., Zhang, A.: Personal recognition using hand shape and texture. IEEE Transaction on Image Processing 15(8), 2454–2461 (2006)

    Article  Google Scholar 

  4. Zhang, L., Zhang, D.: Characterization of Palmprints by Wavelet Signatures via Directional Context Modeling. IEEE Transaction on Systems, Man, and Cybernetics 34(3), 1335–11347 (2004)

    Article  Google Scholar 

  5. The SURF source code, http://www.vision.ee.ethz.ch/~surf/

  6. Zhang, D., Shu, W.: Two novel characteristics in palmprint verification: Datum point invariance and line feature matching. Pattern Recognition 32(4), 691–702 (1999)

    Article  Google Scholar 

  7. Han, C.-C., Cheng, H.-L., Lin, C.-L., Fan, K.-C.: Personal authentication using palmprint features. Pattern Recognition 36, 371–381 (2003)

    Article  Google Scholar 

  8. International Committee for Information Technology Standards. Technical Committee M1-Biometrics (2005), http://www.incits.org/tc_home/m1.htm

  9. The PolyU palmprint database, http://www.comp.polyu.edu.hk/~biometrics

  10. Wenxin, L., Zhang, D., Xu, Z.: Palmprint Identification by Fourier Transform. Intl. Journal of Pattern Recognition and Artificial Intelligence 16(4), 417–432 (2002)

    Article  Google Scholar 

  11. Badrinath, G.S., Gupta, P.: An Efficient Multi-algorithmic Fusion System based on Palmprint for Personnel Identification. In: Intl. Conf. on Advanced Computing, pp. 759–764 (2007)

    Google Scholar 

  12. Ross, A., Jain, A.K.: Information fusion in biometrics. In: Pattern recognition letters, pp. 2115–2125 (2003)

    Google Scholar 

  13. Pavlidis, T.: Algorithms for graphics and image processing. Springer, Heidelberg (1982)

    Book  Google Scholar 

  14. Bay, H., Tuytelaars, T., Van Gool, L.: SURF: Speeded up robust features. In: Ninth European conference on computer vision, pp. 404–417 (2006)

    Google Scholar 

  15. Lu, G., Wang, K., Zhang, D.: Wavelet based independent component analysis for palmprint identification. In: Intl. conf. on Machine Learning and Cybernetics, pp. 3547–3550 (2004)

    Google Scholar 

  16. Wang, Y., Ruan, Q.: Kernel Fisher Discriminant Analysis for Palmprint Recognition. In: 18th Intl. Conf. on Pattern Recognition, pp. 457–460 (2006)

    Google Scholar 

  17. Bay, H., Fasel, B., Van, L.: Interactive museum guide: Fast and robust recognition of museum objects. In: First Intl. workshop on mobile vision (2006)

    Google Scholar 

  18. Murillo, A.C., Guerrero, J.J., Sagues, C.: SURF features for efficient robot localization with omnidirectional images. In: IEEE Intl. Conf. on Robotics and Automation, pp. 3901–3907 (2007)

    Google Scholar 

  19. Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: IEEE Conf. on Computer Vision and Pattern Recognition, pp. 511–518 (2001)

    Google Scholar 

  20. Shu, W., Zhang, D.: Automated Personal Identification by Palmprint. Optical Engineering 37(8), 2359–2362 (1998)

    Article  Google Scholar 

  21. Liu, X., Bowyer, K.W., Flynn, P.J.: Experiments with an Improved Iris Segmentation Algorithm. In: Fourth IEEE Workshop on Automatic Identification Advanced Technologies, pp. 118–123 (2005)

    Google Scholar 

  22. Independent Testing of Iris Recognition Technology Final Report. Int’l Biometric Group (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Srinivas, B.G., Gupta, P. (2009). Palmprint Based Verification System Using SURF Features. In: Ranka, S., et al. Contemporary Computing. IC3 2009. Communications in Computer and Information Science, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03547-0_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-03547-0_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03546-3

  • Online ISBN: 978-3-642-03547-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics