New algorithm for iris recognition based on video sequences

Salah Bourennane; Caroline Fossati; William Ketchantang

doi:10.1117/1.3478885

1 July 2010 New algorithm for iris recognition based on video sequences

Salah Bourennane, Caroline Fossati, William Ketchantang

Author Affiliations +

Journal of Electronic Imaging, Vol. 19, Issue 3, 033011 (July 2010). https://doi.org/10.1117/1.3478885

Abstract

Among existing biometrics, iris recognition systems are among the most accurate personal biometric identification systems. However, the acquisition of a workable iris image requires strict cooperation of the user; otherwise, the image will be rejected by a verification module because of its poor quality, inducing a high false reject rate (FRR). The FRR may also increase when iris localization fails or when the pupil is too dilated. To improve the existing methods, we propose to use video sequences acquired in real time by a camera. In order to keep the same computational load to identify the iris, we propose a new method to estimate the iris characteristics. First, we propose a new iris texture characterization based on Fourier-Mellin transform, which is less sensitive to pupil dilatations than previous methods. Then, we develop a new iris localization algorithm that is robust to variations of quality (partial occlusions due to eyelids and eyelashes, light reflects, etc.), and finally, we introduce a fast and new criterion of suitable image selection from an iris video sequence for an accurate recognition. The accuracy of each step of the algorithm in the whole proposed recognition process is tested and evaluated using our own iris video database and several public image databases, such as CASIA, UBIRIS, and BATH.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Salah Bourennane, Caroline Fossati, and William Ketchantang "New algorithm for iris recognition based on video sequences," Journal of Electronic Imaging 19(3), 033011 (1 July 2010). https://doi.org/10.1117/1.3478885

Published: 1 July 2010

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