Direct Least Square Fitting of Ellipses
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris Individuality: A Partial Iris Model
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
IEEE Transactions on Circuits and Systems for Video Technology
GESLIC: genetic and evolutionary-based short-length iris codes
Proceedings of the 49th Annual Southeast Regional Conference
Genetic and evolutionary methods for biometric feature reduction
International Journal of Biometrics
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There have been claims of very high information content in iris texture, higher even than in fingerprints. This makes iris attractive for large scale identification systems with possibly millions of people. However, some systems operate by performing N 1:1 matches of the probe against the database. This can get prohibitively expensive in terms of computation as N grows large. Note that for identification systems the per-match time dominants system performance, unlike verification where feature extraction time is the primary component. In this paper we show how to use a short-length iris code to pre-screen a large database and thereby reduce the number of full comparisons needed to a fraction of the total. Since the screening code is much smaller than the full iris code, the time to process the whole database is greatly reduced. As an added benefit, we show that we can use the alignment inferred from the short code to greatly restrict the range of alignments searched for the full code, which further speeds up the system. As we demonstrate in experiments, the two stage approach can reduce the cost and/or time needed by an order of magnitude with very little impact on identification performance.