Skip to main content

Introduction to the Handbook of Iris Recognition

  • Chapter
  • First Online:

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

Abstract

Iris recognition is both a technology already in successful use in ambitious nation-scale applications and also a vibrant, active research area with many difficult and exciting problems yet to be solved. This chapter gives a brief introduction to iris recognition and an overview of the chapters in the Second Edition of the Handbook of Iris Recognition.

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

Buying options

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 EPUB and 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

Learn about institutional subscriptions

References

  1. S.E. Baker, K.W. Bowyer, P.J.J. Flynn, Empirical evidence for correct iris match score degradation with increased time-lapse between gallery and probe matches, in Advances in Biometrics. Lecture Notes in Computer Science, vol. 5558 (2009), pp. 1170–1179

    Google Scholar 

  2. S.E. Baker et al., Degradation of iris recognition performance due to non-cosmetic prescription contact lenses. Comput. Vis. Image Underst. 114(9), 1030–1044 (2010)

    Article  Google Scholar 

  3. K. Bowyer, K. Hollingsworth, P.J. Flynn, Image understanding for iris biometrics: a survey. Comput. Vis. Image Underst. 110(2), 281–307 (2008)

    Article  Google Scholar 

  4. K. Bowyer, E. Ortiz, A. Sgroi, Trial Somaliland voting register de-duplication using iris recognition, in IEEE Automatic Face and Gesture Recognition Conference Workshops (2015)

    Google Scholar 

  5. A. Czajka, Influence of iris template ageing on recognition reliability. Commun. Comput. Inf. Sci. 452, 284–299 (2014)

    Article  Google Scholar 

  6. J. Daugman, Demodulation by complex-valued wavelets for stochastic pattern recognition. Int. J. Wavelets Multiresol. Inf. Process. 1(1), 1–17 (2003)

    Article  MATH  Google Scholar 

  7. J. Daugman, New methods in iris recognition. IEEE Trans. Syst. Man Cybern. Part B: Cybern. 37(5), 1167–1175 (2007)

    Article  Google Scholar 

  8. J. Daugman, I. Malhas, Iris recognition border-crossing system in the UAE. Biometrics, 49053 (2004)

    Google Scholar 

  9. J. Doyle, K. Bowyer, Robust detection of texured contact lenses in iris recognition using BSIF. IEEE Access 3, 1672–1683 (2015)

    Article  Google Scholar 

  10. S.P. Fenker, Experimental evidence of a template aging effect in iris biometrics (2011)

    Google Scholar 

  11. FotoNation, Iris Recognition

    Google Scholar 

  12. J. Galbally et al., Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms. Comput. Vis. Image Underst. 117, 1512–1525 (2013)

    Article  Google Scholar 

  13. P. Grother et al., IREX I: performance of iris recognition algorithms on standard images (NIST Interagency Report 7629, in PoLAR (2009)

    Google Scholar 

  14. K. Hollingsworth, K. Bowyer, P.J. Flynn, Pupil dilation degrades iris biometric performance. Comput. Vis. Image Underst. 113(1), 150–157 (2009)

    Article  Google Scholar 

  15. G. of India, Unique Identification Authority of India

    Google Scholar 

  16. A.W.K. Kong, D. Zhang, M.S. Kamel, An analysis of IrisCode. IEEE Trans. Image Process. 19(2), 522–532 (2010)

    Article  MathSciNet  Google Scholar 

  17. A.J. Mansfield, J.L. Wayman, Best practices in testing and reporting performance of biometric devices ver 2.01. Natl. Phys. Lab. 14(02), 1–36 (2002)

    Google Scholar 

  18. J.R. Matey et al., Iris on the move: acquisition of images for iris recognition in less constrained environments. Proc. IEEE 94(11), 1936–1947 (2006)

    Article  Google Scholar 

  19. D. Mathieson, R. Wager, Somaliland national election commission: report on the preparation of the voting register (2010)

    Google Scholar 

  20. NeuroTechnology, VeriEye SDK

    Google Scholar 

  21. G.P. et al., IREX VI: Temporal stability of iris recognition accuracy (NIST Interagency Report 7948), in PoLAR (2013)

    Google Scholar 

  22. P.J. Phillips et al., FRVT 2006 and ICE 2006 large-scale experimental results. IEEE Trans. Pattern Anal. Mach. Intell. 32(5), 831–846 (2010)

    Article  Google Scholar 

  23. A.N. Al-Raisi, A.M. Al-Khouri, Iris recognition and the challenge of homeland and border control security in UAE. Telemat. Inform. 25(2), 117–132 (2008)

    Article  Google Scholar 

  24. C. Rathgeb, A. Uhl, P. Wild, USIT—University of Salzburg Iris-Toolkit

    Google Scholar 

  25. N. Sazonova et al., A study on quality-adjusted impact of time lapse on iris recognition, in SPIE 8371B: Biometric Technology for Human Identification (2012)

    Google Scholar 

  26. J.A. Scallan, S. Weimer, Overview of the multiple biometrics grand challenge, in Advances in Biometrics, ed. by M. Tistarelli, M. Nixon, vol. 5558 (Springer, Berlin/Heidelberg, 2009), pp. 705–714

    Google Scholar 

  27. N. I. of Standards and T. (NIST), IREX: IRis EXchange

    Google Scholar 

  28. G. Sutra et al., A biometric reference system for iris: OSIRIS version 4.1

    Google Scholar 

  29. Technavio, Global Iris Recognition Market: 2015–2019 (2015)

    Google Scholar 

  30. S. Venugopalan, M. Savvides, How to generate spoofed irises from an iris code template. IEEE Trans. Inf. Forensics Secur. 6, 385–394 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kevin W. Bowyer .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer-Verlag London

About this chapter

Cite this chapter

Bowyer, K.W., Burge, M.J. (2016). Introduction to the Handbook of Iris Recognition. In: Bowyer, K., Burge, M. (eds) Handbook of Iris Recognition. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-6784-6_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-6784-6_1

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-6782-2

  • Online ISBN: 978-1-4471-6784-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics