未成年人虹膜生物识别图像质量评估

Norman Nelufule, A. Kock, G. Mabuza-Hocquet, Y. Moolla
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引用次数: 5

摘要

图像质量评估在提高模式识别系统(包括生物识别系统)的性能方面起着重要作用。虽然质量评估方法已被用于成人虹膜识别,但尚未对儿童虹膜识别进行研究。由于儿童的不合作性质,虹膜识别很困难,可能导致虹膜样本质量较低。在这项研究中,我们采用了四种现有的质量评估方法,光线变化、瞳孔扩张、偏离角度和像素计数,对我们从儿童和CASIA数据库收集的成人虹膜图像进行了分析。结果表明,一旦使用自动化过程去除没有任何可见虹膜区域的图像,则剩余的儿童图像产生与成人虹膜图像相似的质量评估分布。这项研究是为儿童创建虹膜识别系统的第一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Quality Assessment for Iris Biometrics for Minors
Image quality assessment plays an important role in enhancing the performance of pattern recognition systems, including biometric systems. Although, quality assessment methods have been utilized for iris recognition on adults they have not been investigated on iris recognition for children. Iris recognition on children is difficult because of their uncooperative nature and may result in lower quality iris samples. In this study, we applied four existing quality assessment methods, light variation, pupil dilation, off-angle, and pixel count to data we collected from children and the CASIA database with iris images from adults. The results indicate that once the image without any visible iris area are removed, using an automated process, then the remaining images for children produces similar quality assessment distributions as those of iris images from adults. This study is the first step in creating an iris recognition system for children.
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