Iris Quality Metrics for Adaptive Authentication
Iris Quality Metrics for Adaptive Authentication
复制标题
用于自适应身份验证的虹膜质量指标
DOI：
10.1007/978-1-4471-4402-1_4
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发表时间：
2013
期刊：
影响因子：
10.7
通讯作者：
H. Wechsler
中科院分区：
文献类型：
--
作者：
N. Schmid;Jinyu Zuo;Francesco Nicolo;H. Wechsler
虹膜样本质量有许多重要的应用。它可以用于虹膜识别系统中的各种处理级别，例如，在采集阶段，在图像增强阶段，或在匹配和融合阶段。设计用于评估虹膜样本质量的参数被用作品质因数，以量化由于环境条件、个体的不受约束的呈现或由于可以减少数据中的虹膜信息的后处理而导致的虹膜图像的退化。本章简要总结了虹膜识别系统中传统使用的质量因素。它进一步介绍了新的指标，可用于评估虹膜图像质量。的个人质量措施的性能进行了分析，并证明他们的自适应列入虹膜识别系统。介绍了三种基于质量度量向量的生物特征匹配器的性能改进方法。对于所有这三种方法，所报道的实验结果表明，显着的性能改善时，应用于虹膜生物特征识别。这证实了新提出的质量措施是信息的意义上说，他们的参与结果在提高虹膜识别性能。
Iris sample quality has a number of important applications. It can be used at a variety of processing levels in iris recognition systems, for example, at the acquisition stage, at image enhancement stage, or at matching and fusion stage. Metrics designed to evaluate iris sample quality are used as figures of merit to quantify degradations in iris images due to environmental conditions, unconstrained presentation of individuals or due to postprocessing that can reduce iris information in the data. This chapter presents a short summary of quality factors traditionally used in iris recognition systems. It further introduces new metrics that can be used to evaluate iris image quality. The performance of the individual quality measures is analyzed, and their adaptive inclusion into iris recognition systems is demonstrated. Three methods to improve the performance of biometric matchers based on vectors of quality measures are described. For all the three methods, the reported experimental results show significant performance improvement when applied to iris biometrics. This confirms that the newly proposed quality measures are informative in the sense that their involvement results in improved iris recognition performance.