Abstract
Continuous efforts have been made in searching for robust and effective iris coding methods, since Daugman’s pioneering work on iris recognition was published. Proposed algorithms follow the statistical pattern recognition paradigm and encode the iris texture information through phase, zero-crossing or texture-analysis based methods. In this paper we propose an iris recognition algorithm that follows the structural (syntactic) pattern recognition paradigm, which can be advantageous essentially for the purposes of description and of the human-perception of the system’s functioning. Our experiments, that were performed on two widely used iris image databases (CASIA.v3 and ICE), show that the proposed iris structure provides enough discriminating information to enable accurate biometric recognition, while maintains the advantages intrinsic to structural pattern recognition systems.
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Proença, H. (2007). A Structural Pattern Analysis Approach to Iris Recognition. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_90
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DOI: https://doi.org/10.1007/978-3-540-75175-5_90
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75174-8
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