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Proceedings Paper

Quantitative laser speckle contrast imaging for presentation attack detection in biometric authentication systems
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Paper Abstract

We present an analysis and demonstration of using laser-speckle contrast imaging (LSCI) as a sensing modality for presentation attack detection in biometric authentication systems. We provide the design of an experimental testbed for the quantitative characterization of LSCI and measurement results for optimization of the parameters of the active imaging testbed. LSCI has traditionally been used as a qualitative tool for identification of blood flow in dermal micro-vasculature for diagnosis of tissue health. We have built a laboratory phantom model, simulating blood flow beneath diffuse tissue to enable quantitative characterization of the performance of LSCI as a function of both target and imaging system parameters. Our first testbed configuration was an objective LSCI setup, detecting unfocused light on a focal plane array. In objective configuration, we characterized speckle size and speckle contrast as a function of the testbed parameters. In the second testbed configuration, we evaluated the performance of objective LSCI for complex fluid flow scenes. Finally, we report on the quantitative measurement of speckle contrast as a function of fluid flow rate, thereby demonstrating the use of optimized LSCI as an important sensing modality for the detection of presentation attacks in biometric authentication systems.

Paper Details

Date Published: 2 May 2019
PDF: 9 pages
Proc. SPIE 11020, Smart Biomedical and Physiological Sensor Technology XVI, 1102008 (2 May 2019); doi: 10.1117/12.2518268
Show Author Affiliations
Claire Sun, USC Information Sciences Institute (United States)
Arun Jagannathan, USC Information Sciences Institute (United States)
Jonathan L. Habif, USC Information Sciences Institute (United States)
Mohamed Hussein, USC Information Sciences Institute (United States)
Leonidas Spinoulas, USC Information Sciences Institute (United States)
Wael Abd-Almageed, USC Information Sciences Institute (United States)


Published in SPIE Proceedings Vol. 11020:
Smart Biomedical and Physiological Sensor Technology XVI
Brian M. Cullum; Douglas Kiehl; Eric S. McLamore, Editor(s)

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