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Face Quality Measure for Face Authentication

机译:用于面部认证的面部质量度量

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摘要

In a face authentication system, face image quality can significantly influence system performance. Designing an effective image quality measure is necessary to reduce the number of poor quality face images acquired during enrollment and authentication, thereby improving system performance. Furthermore, image quality scores can be used as weights in multimodal system based on weighted score level fusion. In this paper, the authors examined image quality factors, such as contrast, brightness, focus and illumination, and defined quality measure for these factors. The quality measure used template image's, or registration image's, quality as reference quality. Thus, the quality measure does not rely on any reference good quality and criteria to evaluate how good a face image is. The quality measure reflects difference in quality between a template image and a query image. Then, we proposed a face quality measure by combining these factors. Finally, we conducted experiments to evaluate the relationship between face authentication performance and individual image quality factors as well as the combined face quality measure.
机译:在人脸认证系统中,人脸图像质量会严重影响系统性能。设计有效的图像质量度量对于减少在注册和身份验证期间获取的劣质人脸图像的数量是必要的,从而提高了系统性能。此外,基于加权得分水平融合,图像质量得分可以用作多峰系统中的权重。在本文中,作者检查了图像质量因素,例如对比度,亮度,焦点和照明,并为这些因素定义了质量度量。质量度量使用模板图像或注册图像的质量作为参考质量。因此,质量度量不依赖于任何参考良好的质量和标准来评估面部图像的良好程度。质量度量反映了模板图像和查询图像之间的质量差异。然后,我们结合这些因素提出了一种面部质量测量方法。最后,我们进行了实验,以评估人脸认证性能与单个图像质量因素之间的关系以及组合的人脸质量度量。

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