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Poor-quality facial images pose challenges in biometric authentication, especially in passport photo acquisition and recognition. This study proposes a novel and open-source solution to address these issues by introducing a real-time facial image quality analysis utilizing computer vision technology on a low-power single-board computer. We present an open-source complete hardware solution that consists of a Jetson processor, a 16 MP autofocus RGB camera, a custom enclosure, and a touch sensor LCD for user interaction. To ensure the integrity and confidentiality of captured facial data, Advanced Encryption Standard (AES) is used for secure image storage. Using the pilot data collection, the system demonstrated its ability to capture high-quality images, achieving 98.98% accuracy in storing images of acceptable quality. This open-source, readily deployable, secure system offers promising potential for diverse real-time applications such as passport verification, security systems, etc.
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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 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 in 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 system.
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- PAR ID:
- 10053530
- Date Published:
- Journal Name:
- IEEE International Symposium on Technologies for Homeland Security (HST)
- Page Range / eLocation ID:
- 1 to 10
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/THS.2017.7943491
