Purpose: This work was conducted determine whether iris recognition accuracy decreases with the time lapsed between collection of initial enrollment and recognition images. More specifically, it seeks to quantify accuracy changes associated with any permanent changes to the iris and its proximal anatomy. This study is intended to quantify natural ageing effects in a healthy population; medical conditions and injuries can rapidly and severely affect recognition, so these are out of scope.Background: Stability is a required definitional property for a biometric to be useful. Quantitative statements of stability are operationally important as they dictate re-enrollment schedules e.g. of a face on a passport. The ophthalmologists who filed initial patents on iris recognition posited the iris to be "extremely stable" over "many years" but that "features which do develop" do so "rather slowly" [31]. A further patent held that irises have "texture of high complexity, that prove to be immutable over a person's life" [21]. This view held until several recent empirical studies suggested otherwise. Those studies, and ours, were motivated to check the veracity of the 1994 patent's assertion that an enrolled iris can be viable over decades. Two studies, using separate iris image collections from the University of Notre Dame, reported a large increase in false rejection rates [8,29]. The studies made attempts to account for several possible causes of the observed ageing, but could not conclude that the iris texture itself was changing. Their results, however, were widely reported [59,24, 3] with statements such as "irises, rather than being stable over a lifetime, are susceptible to ageing effects that steadily change the appearance over time" [33]. A further study, however, identified pupil-dilation[27] as the primary causal variable. Operational iris systems have identified individuals over periods up to 10 years[5] and 7 years [6].Conclusions: Using two large operational datasets, we find no evidence of a widespread iris ageing effect. Specifically, the population statistics (mean and variance) are constant over periods of up to nine years. This is consistent with the ability to enroll most individuals and see no degradation in overall recognition accuracy. Furthermore, we compute an ageing rate for how quickly recognition degrades with changes in the iris anatomy; this estimate suggests that iris recognition of average individuals will remain viable over decades. However, given the large population sizes, we identify a small percentage of individuals whose recognition scores do degrade consistent with disease or an ageing effect. These results are confined to adult populations. Additionally, we show that the template ageing reported in the Notre Dame studies is largely due to systematic dilation change over the collection period. Pupil dilation varies under environmental and several biological influences, with variations occuring on timescales ranging from below one second up to several decades. Our data suggests that the...

The historical NEXUS iris kiosks log dataset collected by the Canada Border Services Agency from 2003 to 2014 has become the focus of scientific attention due to its involvement in the iris ageing debate between the National Institute of Standard and Technology and the University of Notre Dame researchers. To facilitate this debate, this study provides additional details on how this dataset was collected, its various properties and irregularities, and presents new results related to the effect of ageing, age, and other factors on the system performance obtained using the portions of the dataset that have not been previously analysed. In doing that, the importance of conducting subject-based performance analysis, as opposed to the traditionally done transaction-based analysis, is emphasised. The significance of factor effects is examined. Recommendations on further improvement of the technology are made.