Recognising persons by their iris patterns
John G. Daugman · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
Iris recognition provides real-time, high confidence identification of persons by analysis of the random patterns that are visible within the iris of an eye from some distance. Because the iris is a protected, internal, organ whose random texture is epigenetic and stable over the lifespan, it can serve as a living password. Recognition decisions are made with confidence levels high enough to support rapid exhaustive searches through national-sized databases. The principle that underlies these algorithms is the failure of an efficient test of statistical independence involving more than 200 degrees-of-freedom, based on phase sequencing each iris pattern with quadrature 2D wavelets. Different persons always pass this test of statistical independence, but images from the same iris almost always fail this test of independence. Database search speeds are around 1 million persons per second per CPU. Data from 200 billion cross-comparisons between different eyes will be presented in this talk, using a database consisting of 632,500 iris images acquired in the United Arab Emirates in a networked national border-crossing security system which performs, every day, about 9 billion iris comparisons using these algorithms. Current research efforts with this technology aim to make it more tolerant of difficult conditions of iris capture, such as "iris on the move," at a distance, and off-axis.