Autofocus for SWIR facial imagery utilizing Haar wavelets
Autofocus for SWIR facial imagery utilizing Haar wavelets
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DOI：
10.1109/ths.2017.7943491
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发表时间：
2017-04
期刊：
影响因子：
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通讯作者：
S. C. Leffel;T. Bourlai;J. Dawson
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文献类型：
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作者：
S. C. Leffel;T. Bourlai;J. Dawson
当使用任何特定波段相机传感器捕获面部图像时，自动评估和调整图像质量的任务可以通过消除各种采集参数（例如照明）来实现。与图像质量相关的一个这样的参数是锐度。如果在数据采集过程中估计不准确，可能会影响整个人脸图像数据集的质量，从而影响人脸识别的准确性。虽然手动地将每个相机聚焦在目标（人脸）上可以产生看起来清晰的面部图像，但是该过程对于操作者和受试者来说可能是麻烦的，并且因此增加了数据收集获取时间。在这项工作中，我们开发了一个基于机电的系统，自动评估人脸图像的清晰度，之前捕获，而不是必要的后处理方案。在确定我们所提出的系统的算法步骤之前，已经根据经验评估了各种模糊质量因素和约束。本文讨论了该系统在一个实时操作环境中的实现。
The task of automatically assessing and adjusting image quality, when capturing face images using any band-specific camera sensor, can be achieved by eliminating a variety of acquisition parameters such as illumination. One such parameter related to image quality is sharpness. If it is not accurately estimated during data collection, it may affect the quality of the overall face image dataset and thus face recognition accuracy. While manually focusing each camera on the target (human face) can result is sharp looking face images, the process can be cumbersome for the operators and the subjects and, thus, it increases data collection acquisition time. In this work, we developed an electromechanical based system that automatically assesses face image sharpness, prior to capture rather than necessitating post-processing schemes. Various blur quality factors and constraints have been empirically evaluated, before determining the algorithmic steps of our proposed system. This paper discusses the implementation of this system in a live operating environment.