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Keywords

Active Contour Iris Image Equal Error Rate Active Contour Model False Reject Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. J. G. Daugman. US Patent 5,291,560. Biometric Personal Identification System Based on Iris Analysis, 1994.Google Scholar
  2. J. G. Daugman. Probing the uniqueness and randomness of iriscodes: Results from 200 billion iris pair comparisons. Proc. IEEE, 94(11):1927–1935, 2006.Google Scholar
  3. UK Government Home Ofice, Project IRIS website. http://iris.gov.uk.Google Scholar
  4. J. Matey, K. Hanna, R. Kolcyznski, D. LoIacono, S. Mangru, O. Naroditsky, M. Tinker, T. Zappia, and W-Y. Zhao. Iris on the Move: Acquisition of images for iris recognition in less constrained environments. Proc. IEEE, 94(11):1936–1947, 2006.Google Scholar
  5. K. Bowyer and K. Hollingsworth and P. Flynn. Image understanding for iris biometrics: a survey. Technical Report CSE, Univ. Notre Dame, 2007.Google Scholar
  6. A. Bertillon. La couleur de l’iris. Revue Scientifique, 1885.Google Scholar
  7. J. H. Doggart. Ocular Signs in Slit-lamp Microscopy. Kimpton, London, 1949.Google Scholar
  8. L. Flom and A. Safir. US Patent 4,641,349. Iris Recognition System, 1987.Google Scholar
  9. National Institute of Standards and Technology. Iris Challenge Evaluation. http://iris.nist.gov/ice/.Google Scholar
  10. ISO/IEC Standard 19794-6. Information Technology – Biometric Data Interchange Formats, Part 6: Iris Image Data, 2005.Google Scholar
  11. J. G. Daugman. High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. Pattern Analysis and Machine Intelligence, 15(11):1148–1161, 1993.CrossRefGoogle Scholar
  12. A. Blake and M. Isard. Active Contours. Springer, Heidelberg, Germany, 1998.Google Scholar
  13. M. Kass, A. Witkin, and D. Terzopoulos. Snakes: active contour models. International Journal of Computer Vision, 1:321–331, 1988.CrossRefGoogle Scholar
  14. V. Dorairaj, N. Schmid, and G. Fahmy. Performance evaluation of non-ideal iris based recognition system implementing global ICA encoding. In Proc. IEEE Int’l Conference on Image Processing (ICIP), volume 3, pages 285–288, 2005.Google Scholar
  15. J. G. Daugman. How iris recognition works. IEEE Trans. Circuits and Systems for Video Technology, 14(1):21–30, 2004.CrossRefGoogle Scholar
  16. F. Hao, J. G. Daugman, and P. Zielinski. A fast search algorithm for a large fuzzy database. Submitted: IEEE Trans. Information Forensics & Security, 2007.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • John Daugman
    • 1
  1. 1.The Computer LaboratoryUniversity of CambridgeCambridge CB3 0FDUnited Kingdom

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