Skip to main content
SpringerLink
Log in

Iris Recognition – Beyond One Meter

  • Chapter
Handbook of Remote Biometrics

Part of the book series: Advances in Pattern Recognition ((ACVPR))

Abstract

Iris recognition Iris recognition is, arguably, the most robust form of biometric Biometrics identification. It has been deployed in large-scale systems that have been very effective. The systems deployed to date make use of iris Remote Biometric cameras that require significant user cooperation; that in turn imposes significant constraints on the deployment scenarios that are practical.

There are many applications in which it would be useful to undertake iris recognition at distances greater than those provided by conventional iris recognition systems. This chapter reviews iris recognition methods and provides a framework for understanding the issues involved in capturing images for iris recognition at distances of a meter or more. This chapter is intended to be a self-contained tutorial, but the reader will be referred to recent reviews and papers for additional detail. A small set of exercises is provided at the end of the chapter.

This chapter is based on the tutorial originally presented by Matey at the International Summer School on Biometrics held in Alghero in 2007[1].

Mention of any product in this chapter is for illustrative and tutorial purposes only and does not constitute an endorsement of the product by the authors, the US Naval Academy Databases U.S. Naval Academy or the US Government.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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. 4th Summer School for Advanced Studies on Biometrics for Secure Authentication. http://biometrics.uniss.it/

  2. Chaterjee, S. and Yilmaz, M., “Chaos, Fractals and Statistics” Statistical Science. 1992, 7: 49–121.

    Article  MathSciNet  Google Scholar 

  3. Mansfield, T., Kelly, G., Chandler, D., and Kane, J., “Biometric Product Testing Final Report”, CESG Contract X92A/4009309, Centre for Mathematics & Scientific Computing, National Physical Laboratory, Queen’s Road, Teddington, Middlesex TW11 0LW.

    Google Scholar 

  4. Daugman, J., “Recognizing Persons by Their Iris Patterns” in Biometrics: Personal Identification in Networked Society, A. Jain, R. Bolle, & S. Pankanti, eds. Springer, New York, 2006 ISBN 0-387-28539-3.

    Google Scholar 

  5. Newman, C., “A Life Revealed” in National Geographic Magazine, April 2002.

    Google Scholar 

  6. Daugman, J., http://www.cl.cam.ac.uk/jgd1000/afghan.html.

  7. http://www.genetests.org

  8. Jensen, B., Iridology Simplified 5th ed. Bernard Jensen International, Escondido, CA, 1980 ISBN 096083608-X

    Google Scholar 

  9. Simon, A., Worthen, D.M., and Mitas, J.A., 2nd. “An Evaluation of Iridology”. JAMA. 1979, September 8;242(13):1385–1389.

    Article  Google Scholar 

  10. Bertillon, A., “La couleur de L’Iris”. Annales de Demographie Internationale. 1886, 7: 226–246.

    Google Scholar 

  11. Daugman, J., “Biometric Personal Identification System Based on Iris Analysis.” U.S. Patent No. 5,291,560 issued 1 March 1994.

    Google Scholar 

  12. Bowyer, K.W., Hollingsworth, K., and Flynn, P.J., “Image understanding for iris biometrics: A survey”, Computer Vision and Image Understanding. 2008, 110:281–307.

    Article  Google Scholar 

  13. Vatsa, M., Singh, R., and Gupta, P., “Comparison of iris recognition algorithms,” Intelligent Sensing and Information Processing, 2004. Proceedings of International Conference on, pp. 354–358, 2004.

    Google Scholar 

  14. Thornton, J., Savvides, M., and Kumar, B.V.K., “An Evaluation of Iris Pattern Representations,” Biometrics: Theory, Applications, and Systems, 2007. BTAS 2007. First IEEE International Conference on, pp. 1–6, 27–29 September 2007.

    Google Scholar 

  15. “How the Afghan Girl was Identified by Her Iris Patterns”, http://www.cl.cam.ac.uk/jgd1000/afghan.html

  16. IrisCodeTM is the name for the iris template generated by a particular group of Daugman algorithm variants.

    Google Scholar 

  17. Daugman, J. “Probing the Uniqueness and Randomness of IrisCodes: Results from 200 billion iris pair comparisons.” Proceedings of the IEEE, vol. 94, no. 11, 2006, pp. 1927–1935.

    Google Scholar 

  18. ISO/IEC JTC 1/SC 37 N 504, “Biometric Data Interchange Formats – Part 6: Iris Image Data”.

    Google Scholar 

  19. American Conference of Governmental Industrial Hygienists.

    Google Scholar 

  20. ACGIH, 2008 TLVs and BEIs, ISBN 978-1-882417-79-7. Available at www.acgih.org.

  21. Diemer, S., “Safety Aspects for Light Emitting Diodes (LEDs) and Laser Pointers: Current Positions of the ICNIRP”, Proceedings of the International Laser Safety Conference, 1999.

    Google Scholar 

  22. International Light, 10 Technology Drive, · Peabody, MA 01960. www.intl-lighttech.com.

  23. Grother, P., Iris Exchange Evaluation (IREX) Evaluation 2008, Published online at http://iris.nist.gov/irex/index.html

  24. Sun, Z., Tan, T., and Wang, Y., “Robust encoding of local ordinal measures: A general framework of iris recognition”, in: Proc. BioAW Workshop, 2004, pp. 270–282.

    Google Scholar 

  25. Daugman, J., “How Iris Recognition Works”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 1, January 2004.

    Google Scholar 

  26. Daugman, J., “New Methods in Iris Recognition,” Systems, Man, and Cybernetics, Part B, IEEE Transactions on , vol. 37, no. 5, pp. 1167–1175, October 2007.

    Google Scholar 

  27. ZEMAX Development Corporation, 3001 112th Avenue NE, Suite 202, Bellevue, WA 98004-8017. www.zemax.com

  28. Imatest LLC, 3478 16th Circle, Boulder, CO 80304. www.imatest.com

  29. Roggemann, M.C. and Welsh, B.M., Imaging Through Turbulence (CRC Press, Boca Raton, 1996), ISBN 0-8493-3787-9.

    Google Scholar 

  30. Kennell, L., Broussard, R.P., Ives, R.W., and Matey, J.R. “Preprocessing of Off-Axis Iris Images for Recognition”, SPIE Europe Security & Defense Conference, Cardiff, Wales, UK, September 2008.

    Google Scholar 

  31. Sung, E., Chen, X., Zhu, J., and Yang, J., “Towards Non-cooperative Iris Recognition Systems,” Proceedings of the 2002 Seventh IEEE International Conference on Control, Automation, Robotics, and Vision, pp. 990–995, December 2002.

    Google Scholar 

  32. Zuo, J., Kalka, N.D., and Schmid, N.A., “A Robust Iris Segmentation Procedure for Unconstrained Subject Presentation,” Special Session on Research at the Biometric Consortium Conference, 2006 Biometrics Symposium.

    Google Scholar 

  33. Ross, A. and Shah, S., “Segmenting Non-ideal Irises Using Geodesic Active Contours,” Special Session on Research at the Biometric Consortium Conference, 2006 Biometrics Symposium.

    Google Scholar 

  34. Schuckers, S., Schmid, N.A., Abhyankar, A., Dorairaj, V., Boyce, C.K., and Hornak, L.A., “On Techniques for Angle Compensation in Non-ideal Iris Recognition,” IEEE Transactions on Systems, Man, and Cybernetics, Part B, vol. 37, no. 5, October 2007.

    Google Scholar 

  35. Price, J.R., Gee, T.F., Paquit, V., and Tobin, K.W., Jr., “On the Efficacy of Correcting for Refractive Effects in Iris Recognition,” IEEE Conference on Computer Vision and Pattern Recognition, June 2007.

    Google Scholar 

  36. Fancourt, C., Bogoni, L., Hanna, K., Guo, Y., Wildes, R., Takahashi, N., and Jain, U. “Iris Recognition at a Distance”, Proc. 5th Int. Conf. on Audio and Video-Based Biometric Person Authentication, 2005.

    Google Scholar 

  37. Matey, J.R., Naroditsky, O., Hanna, K., Kolczynski, R., LoIacono, D., Mangru, S., Tinker M., Zappia, T., and Zhao, W.Y., “Iris on the MoveTM: Acquisition of Images for Iris Recognition in Less Constrained Environments”. Proc. IEEE. 94(11), pp. 1936–1947, November 2006.

    Article  Google Scholar 

  38. Matey, J.R., Ackerman, D., Bergen, J., and Tinker, M., “Iris Recognition in Less Constrained Environments”, in Advances in Biometrics, Sensors, Algorithms & Systems, N. Ratha and V. Govindaraju, eds. Springer-Verlag, London, 2008 ISBN 978-1-84628-920-0.

    Google Scholar 

  39. Dr. Jonathon Phillips, MBGC Program Manager, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Stop 8940, Gaithersburg, MD 20899-8940. mbgc@nist.gov.

    Google Scholar 

  40. Northcott, M.J. and Graves, J.E. “Iris Imaging Using Reflection from the Eye” US Patent Application 20080002863, January 3, 2008.

    Google Scholar 

  41. Geterman, G., Jacobsen, V., Jelinek, J., Phinney, T., Jamza, R., Ahrens, T., Kilgore, G., Whillock, R., and Bedros, S. “Combined Face and Iris Recognition System”, US Patent Application 20080075334, March 27, 2008.

    Google Scholar 

  42. Global Rainmakers, affiliate of Hoyos Group, 10 E 53rd St, 33rd Floor, New York, NY 10022. www.hoyosgroup.com

  43. Retica Systems, Inc., 201 Jones Road, Third Floor, West Waltham, MA 02451. www.retica.com.

  44. Bashir, F., Casaverde, P., Usher, D., and Friedman, M., “Eagle-Eye: A System for Iris Recognition at a Distance,” 2008 IEEE Conference on Technologies for Homeland Security, pp. 426–431, 12–13 May 2008.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical & Computer Engineering Department US Naval Academy–Maury Hall, Biometric Signal Processing Laboratory, Annapolis, MD 21402-5025, USA

    James R. Matey & Lauren R. Kennell

Authors
  1. James R. Matey
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lauren R. Kennell
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to James R. Matey .

Editor information

Editors and Affiliations

  1. Universitá of Sassari, Dipto. Architettura e Pianificazione, Piazza Duomo, 6, 07041 Alghero SS, Italy

    Massimo Tistarelli (Prof.) (Prof.)

  2. Chinese Academy of Science Institute of Automation, Center Biometrics Research & Security, Room 1227, Zhongguancun 95, 100080 Beijing, China

    Stan Z. Li

  3. University of Maryland, Center for Automation Research, College Park, MD 20742-3275, USA

    Rama Chellappa

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag London Limited

About this chapter

Cite this chapter

Matey, J.R., Kennell, L.R. (2009). Iris Recognition – Beyond One Meter. In: Tistarelli, M., Li, S.Z., Chellappa, R. (eds) Handbook of Remote Biometrics. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84882-385-3_2

Download citation

  • DOI: https://doi.org/10.1007/978-1-84882-385-3_2

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84882-384-6

  • Online ISBN: 978-1-84882-385-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation