Ethnicity and Biometric Uniqueness: Iris Pattern Individuality in a West African Database

John Daugman;Cathryn Downing;Oluwatobi Noah Akande;Oluwakemi Christiana Abikoye
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Abstract

We conducted more than 1.3 million comparisons of iris patterns encoded from images collected at two Nigerian universities, which constitute the newly available African Human Iris (AFHIRIS) database. The purpose was to discover whether ethnic differences in iris structure and appearance such as the textural feature size, as contrasted with an all-Chinese image database or an American database in which only 1.53% were of African-American heritage, made a material difference for iris discrimination. We measured a reduction in entropy for the AFHIRIS database due to the coarser iris features created by the thick anterior layer of melanocytes, and we found stochastic parameters that accurately model the relevant empirical distributions. Quantile-Quantile analysis revealed that a very small change in operational decision thresholds for the African database would compensate for the reduced entropy and generate the same performance in terms of resistance to False Matches. We conclude that despite demographic difference, individuality can be robustly discerned by comparison of iris patterns in this West African population.
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种族和生物识别的独特性:西非数据库中的虹膜图案个体性
我们对尼日利亚两所大学收集的图像中编码的虹膜图案进行了 130 多万次比较,这些图像构成了最新的非洲人类虹膜(AFHIRIS)数据库。目的是发现虹膜结构和外观上的种族差异,如纹理特征大小,与全中文图像数据库或仅有 1.53% 非裔美国人血统的美国数据库相比,是否会对虹膜识别产生实质性影响。我们测得 AFHIRIS 数据库的熵值有所降低,这是因为黑色素细胞前层较厚,导致虹膜特征较粗糙,而且我们发现随机参数能准确模拟相关的经验分布。量纲-量纲分析显示,对非洲数据库的操作决策阈值进行很小的改动就能弥补熵的减少,并在抗假匹配方面产生相同的性能。我们的结论是,尽管存在人口统计学上的差异,但通过比较西非人群的虹膜模式,仍能稳健地辨别出个性。
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Table of Contents IEEE T-BIOM Editorial Board Changes IEEE Transactions on Biometrics, Behavior, and Identity Science Publication Information IEEE Transactions on Biometrics, Behavior, and Identity Science Information for Authors 2024 Index IEEE Transactions on Biometrics, Behavior, and Identity Science Vol. 6
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