Computer Laboratory

Technical reports

Results from 200 billion iris cross-comparisons

John Daugman

June 2005, 8 pages

Abstract

Statistical results are presented for biometric recognition of persons by their iris patterns, based on 200 billion cross-comparisons between different eyes. The database consisted of 632,500 iris images acquired in the Middle East, in a national border-crossing protection programme that uses the Daugman algorithms for iris recognition. A total of 152 different nationalities were represented in this database. The set of exhaustive cross-comparisons between all possible pairings of irises in the database shows that with reasonable acceptance thresholds, the False Match rate is less than 1 in 200 billion. Recommendations are given for the numerical decision threshold policy that would enable reliable identification performance on a national scale in the UK.

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BibTeX record

@TechReport{UCAM-CL-TR-635,
  author =	 {Daugman, John},
  title = 	 {{Results from 200 billion iris cross-comparisons}},
  year = 	 2005,
  month = 	 jun,
  url = 	 {http://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-635.pdf},
  institution =  {University of Cambridge, Computer Laboratory},
  number = 	 {UCAM-CL-TR-635}
}