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Quantum cascade laser based active hyperspectral imaging for standoff detection of chemicals on surfaces

 
: Hugger, Stefan; Fuchs, Frank; Jarvis, J.P.; Yang, Q.K.; Rattunde, M.; Ostendorf, R.; Schilling, C.; Draid, R.; Bronner, W.; Aidam, R.; Wagner, J.; Tybussek, Thorsten; Rieblinger, Klaus

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Fulltext urn:nbn:de:0011-n-4105162 (1.1 MByte PDF)
MD5 Fingerprint: 9ca165e0fbaf464e5709c14843cc7073
Copyright Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Created on: 10.6.2017


Razeghi, M. (Ed.) ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Quantum Sensing and Nano Electronics and Photonics XIII : San Francisco, California, United States, February 13, 2016
Bellingham, WA: SPIE, 2016 (Proceedings of SPIE 9755)
ISBN: 9781628419900
Paper 97550A, 11 pp.
Conference "Quantum Sensing and Nano Electronics and Photonics" <13, 2016, San Francisco/Calif.>
European Commission EC
H2020; 645535; CHEQUERS
Compact High pErformance QUantum cascadE laseR Sensors
English
Conference Paper, Electronic Publication
Fraunhofer IAF ()
Fraunhofer IVV ()

Abstract
We employ active hyperspectral imaging using tunable mid-infrared (MIR) quantum cascade lasers for contactless identification of solid and liquid contaminations on surfaces. By collecting the backscattered laser radiation with a camera, a hyperspectral data cube, containing the spatially resolved spectral information of the scene is obtained. Data is analyzed using appropriate algorithms to find the target substances even on substrates with a priori unknown spectra. Eye-save standoff detection of residues of explosives and precursors over extended distances is demonstrated and the main purpose of our system. However, it can be applied to any substance with characteristic reflectance / absorbance spectrum. As an example, we present first results of monitoring food quality by distinguishing fresh and mold contaminated peanuts by their MIR backscattering spectrum.

: http://publica.fraunhofer.de/documents/N-410516.html