Autofocus for SWIR facial imagery utilizing Haar wavelets

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 accuratel...

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Bibliographic Details
Published in2017 IEEE International Symposium on Technologies for Homeland Security (HST) pp. 1 - 10
Main Authors Leffel, Seth C., Bourlai, Thirimachos, Dawson, Jeremy M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2017
Subjects
Cameras
Face
Face recognition
Lighting
Measurement
Testing
Wavelet transforms
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Summary: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.
DOI:10.1109/THS.2017.7943491