Abstract
Iris as a biometric identifier is assumed to be stable over a period of time. However, some researchers have observed that for long time lapse, the genuine match score distribution shifts towards the impostor score distribution and the performance of iris recognition reduces. The main purpose of this study is to determine if the shift in genuine scores can be attributed to aging or not. The experiments are performed on the two publicly available iris aging databases namely, ND-Iris-Template-Aging-2008–2010 and ND-TimeLapseIris-2012 using a commercial matcher, VeriEye. While existing results are correct about increase in false rejection over time, we observe that it is primarily due to the presence of other covariates such as blur, noise, occlusion, and pupil dilation. This claim is substantiated with quality score comparison of the gallery and probe pairs.
Highlights
Human growth or aging from newborn to toddler to adult to elderly is a natural phenomenon
There is no evident shift in the impostor scores whereas the genuine scores show a shift towards the impostor scores for long time lapse
The performance with long time lapse is slightly lower than the short time lapse
Summary
Human growth or aging from newborn to toddler to adult to elderly is a natural phenomenon This process leads to changes in different characteristics such as height, weight, face, gait, and voice. Daugman mentioned that iris is well protected from the environment and stable over time [1,2] This fact is supported with the case study of Sharbat Gula, the Afghan girl whose iris templates were matched after the age difference of 18 years [3]. Owing to these characteristics of iris recognition, it is used for authentication in several large scale government identification projects [4,5]. Fairhurst et al [14]
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