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Optimal Generation of Iris Codes for Iris Recognition

Hu, Yang, Sirlantzis, Konstantinos, Howells, Gareth (2016) Optimal Generation of Iris Codes for Iris Recognition. IEEE Transactions on Information Forensics and Security, . ISSN 1556-6013. (doi:10.1109/TIFS.2016.2606083)

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http://doi.org/10.1109/TIFS.2016.2606083

Abstract

The calculation of binary iris codes from feature values (e.g. the result of Gabor transform) is a key step in iris recognition systems. Traditional binarization method based on the sign of feature values has achieved very promising performance. However, currently, little research focuses on a deeper insight into this binarization method to produce iris codes. In this paper, we illustrate the iris code calculation from the perspective of optimization. We demonstrate that the traditional iris code is the solution of an optimization problem which minimizes the distance between the feature values and iris codes. Furthermore, we show that more effective iris codes can be obtained by adding terms to the objective function of this optimization problem. We investigate two additional objective terms. The first objective term exploits the spatial relationships of the bits in different positions of an iris code. The second objective term mitigates the influence of less reliable bits in iris codes. The two objective terms can be applied to the optimization problem individually, or in a combined scheme. We conduct experiments on four benchmark datasets with varying image quality. The experimental results demonstrate that the iris code produced by solving the optimization problem with the two additional objective terms achieves a generally improved performance in comparison to the traditional iris code calculated by binarizing feature values based on their signs.

Item Type: Article
DOI/Identification number: 10.1109/TIFS.2016.2606083
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Tina Thompson
Date Deposited: 31 Oct 2016 11:33 UTC
Last Modified: 09 Jul 2019 11:48 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/58277 (The current URI for this page, for reference purposes)
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