Ms. Fang Hua Profile

Fang Hua

at Clarkson Univ

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Proceedings Article | 5 May 2012 Paper

A study on quality-adjusted impact of time lapse on iris recognition

Nadezhda Sazonova, Fang Hua, Xuan Liu, Jeremiah Remus, Arun Ross, Lawrence Hornak, Stephanie Schuckers

Proceedings Volume 8371, 83711W (2012) https://doi.org/10.1117/12.919642

KEYWORDS: Iris recognition, Iris, Statistical analysis, Databases, Detection and tracking algorithms, Biometrics, Quality measurement, Eye models, Performance modeling, Image quality

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Although human iris pattern is widely accepted as a stable biometric feature, recent research has found some evidences on the aging effect of iris system. In order to investigate changes in iris recognition performance due to the elapsed time between probe and gallery iris images, we examine the effect of elapsed time on iris recognition utilizing 7,628 iris images from 46 subjects with an average of ten visits acquired over two years from a legacy database at Clarkson University. Taken into consideration the impact of quality factors such as local contrast, illumination, blur and noise on iris recognition performance, regression models are built with and without quality metrics to evaluate the degradation of iris recognition performance based on time lapse factors. Our experimental results demonstrate the decrease of iris recognition performance along with increased elapsed time based on two iris recognition system (the modified Masek algorithm and a commercial software VeriEye SDK). These results also reveal the significance of quality factors in iris recognition regression indicating the variability in match scores. According to the regression analysis, our study in this paper helps provide the quantified decrease on match scores with increased elapsed time, which indicates the possibility to implement the prediction scheme for iris recognition performance based on learning of impact on time lapse factors.

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