A liquid crystal tunable filter based shortwave infrared spectral imaging system: Design and integration |
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| Affiliation: | 1. Biological and Agricultural Engineering, University of Georgia, 2360 Rainwater Road, Tifton, GA 31793, USA;2. Biological and Agricultural Engineering, Driftmier Engineering Center, The University of Georgia, Athens, GA 30602, USA;3. Plant Pathology Department, University of Georgia, Plant Science Bldg., 115 Coastal Way, Tifton, GA 31793, USA;1. Department of Physics, Azarbaijan Shahid Madani University, Tabriz, Iran;2. Department of Physics, Ahar Branch, Islamic Azad University, Ahar, Iran;1. U.S. Army Research Laboratory, Adelphi, MD 20783, USA;2. University of Maryland, College Park, MD 20742, USA;1. Department of Chemistry, University of Connecticut, Storrs, CT 06269-3060, USA;2. Photosynthetic Antenna Research Center, Washington University in St. Louis, MO 63130, USA;3. Department of Chemistry, School of Science and Technology, Kwansei Gakuin University, Gakuen, Sanda, Hyogo 669-1337, Japan;4. Graduate School of Science, Osaka City University, 3-3-138 Sugimoto, Sumiyoshi-ku, Osaka 558-8585, Japan;5. Osaka City University Advanced Research Institute for Natural Science and Technology, 3-3-138 Sugimoto, Sumiyoshi-ku, Osaka 558-8585, Japan;1. Department of Optical Engineering, School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;2. Shanghai Aerospace Control Technology Research Institute, Shanghai 200233, China |
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| Abstract: | This paper presents the methodology to design and integrate a liquid crystal tunable filter (LCTF) based shortwave infrared (SWIR) spectral imaging system. The system consisted of an LCTF-based SWIR spectral imager, an illumination unit, a frame grabber, and a computer with the data acquisition software. The spectral imager included an InGaAs camera (320 × 256 pixels), an SWIR lens (50 mm, F/1.4), and an LCTF (20 mm aperture). Four multifaceted reflector halogen lamps (35 W, 12 VDC) were used to build the illumination unit. The system was integrated by a LabVIEW program for data acquisition. It can capture hyperspectral or multispectral images of the test object in the spectral range of 900–1700 nm. The system was validated by differentiating sugar from wheat flour, and water from 95% ethanol. The results showed that the system can distinguish these materials in both spectral and spatial domains. This SWIR spectral imaging system could be a potential useful tool for nondestructive inspection of food quality and safety. |
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