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Proceedings Paper

Simulation of atmospheric turbulence effects and mitigation algorithms on stand-off automatic facial recognition
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Paper Abstract

Stand-off base and force protection surveillance measures primarily rely on electro-optic and thermal imaging technology. Atmospheric turbulence causes blur, distortion and intensity fluctuations that can severely degrade the image quality of these systems. This work explores the effects of turbulence image degradation on the performance of automatic facial recognition software and also looks at the potential benefit of turbulence mitigation algorithms. The goal of this work is to understand the feasibility of long-range facial recognition in degraded imaging conditions. In order to create a large enough database to match against, simulated imagery of different ranges and turbulence conditions were created using a horizontal view turbulence simulator and a subset of the Facial Recognition Technology (FERET) database. The simulated turbulence degraded imagery was then processed with facial recognition software and the results are compared against those from the pristine image set. Finally, the performance of the facial recognition software with turbulence mitigated imagery is also presented.

Paper Details

Date Published: 30 October 2012
PDF: 17 pages
Proc. SPIE 8546, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII, 85460O (30 October 2012); doi: 10.1117/12.979480
Show Author Affiliations
Kevin R. Leonard, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Jonathan Howe, Defence Science and Technology Lab. (United Kingdom)
David E. Oxford, Defence Science and Technology Lab. (United Kingdom)
U.S. Army Night Vision & Electronic Sensors Directorate (United States)


Published in SPIE Proceedings Vol. 8546:
Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII
Colin Lewis; Douglas Burgess, Editor(s)

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