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An iris recognition approach through structural pattern analysis methods
Author(s) -
Proença Hugo
Publication year - 2010
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/j.1468-0394.2009.00534.x
Subject(s) - computer science , iris recognition , encode , artificial intelligence , robustness (evolution) , pattern recognition (psychology) , biometrics , iris (biosensor) , word error rate , computer vision , biochemistry , chemistry , gene
Continuous efforts have been made to improve the robustness of iris coding methods since Daugman's pioneering work on iris recognition was published. Iris recognition is at present used in several scenarios (airport check‐in, refugee control etc.) with very satisfactory results. However, in order to achieve acceptable error rates several imaging constraints are enforced, which reduce the fluidity of the iris recognition systems. The majority of the published iris recognition methods follow a statistical pattern recognition paradigm and encode the iris texture information through phase, zero‐crossing or texture‐analysis based methods. In this paper we propose a method that follows the structural (syntactic) pattern recognition paradigm. In addition to the intrinsic advantages of this type of approach (intuitive description and human perception of the system functioning), our experiments show that the proposed method behaves comparably to the statistical approach that constitutes the basis of nearly all deployed systems.