Global and local quality measures for NIR iris video

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI:10.1109/CVPRW.2009.5204310

Jinyu Zuo, N. Schmid

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引用次数: 31

Abstract

In the field of iris-based recognition, evaluation of quality of images has a number of important applications. These include image acquisition, enhancement, and data fusion. Iris image quality metrics designed for these applications are used as figures of merit to quantify degradations or improvements in iris images due to various image processing operations. This paper elaborates on the factors and introduces new global and local factors that can be used to evaluate iris video and image quality. The main contributions of the paper are as follows. (1) A fast global quality evaluation procedure for selecting the best frames from a video or an image sequence is introduced. (2) A number of new local quality measures for the iris biometrics are introduced. The performance of the individual quality measures is carefully analyzed. Since performance of iris recognition systems is evaluated in terms of the distributions of matching scores and recognition probability of error, from a good iris image quality metric it is also expected that its performance is linked to the recognition performance of the biometric recognition system.

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近红外虹膜视频的全球和本地质量措施

在基于虹膜的识别领域中，图像质量评价有着许多重要的应用。这包括图像采集、增强和数据融合。为这些应用设计的虹膜图像质量指标被用作价值指标，以量化由于各种图像处理操作而导致的虹膜图像的降级或改进。本文对这些因素进行了详细的阐述，并介绍了可以用来评价虹膜视频和图像质量的新的全局和局部因素。本文的主要贡献如下:(1)介绍了一种从视频或图像序列中选择最佳帧的快速全局质量评估程序。(2)介绍了虹膜生物识别的一些新的局部质量度量方法。仔细分析了各项质量措施的效果。由于虹膜识别系统的性能是根据匹配分数的分布和识别错误的概率来评估的，因此从一个好的虹膜图像质量指标来看，它的性能也被期望与生物特征识别系统的识别性能相关联。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

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