Ms. Yuping Huang Profile

Yuping Huang

at Michigan State Univ

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Proceedings Article | 1 May 2017 Presentation + Paper

Development of a multichannel hyperspectral imaging probe for food property and quality assessment

Yuping Huang, Renfu Lu, Kunjie Chen

Proceedings Volume 10217, 102170L (2017) https://doi.org/10.1117/12.2262622

KEYWORDS: Absorption, Reflectivity, Transmittance, Optical testing, Imaging systems, Liquids, Hyperspectral imaging, Calibration, Optical properties, Spectral calibration, Light sources, Light, Scattering, Signal detection, Light scattering

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This paper reports on the development, calibration and evaluation of a new multipurpose, multichannel hyperspectral imaging probe for property and quality assessment of food products. The new multichannel probe consists of a 910 μm fiber as a point light source and 30 light receiving fibers of three sizes (i.e., 50 μm, 105 μm and 200 μm) arranged in a special pattern to enhance signal acquisitions over the spatial distances of up to 36 mm. The multichannel probe allows simultaneous acquisition of 30 spatially-resolved reflectance spectra of food samples with either flat or curved surface over the spectral region of 550-1,650 nm. The measured reflectance spectra can be used for estimating the optical scattering and absorption properties of food samples, as well as for assessing the tissues of the samples at different depths. Several calibration procedures that are unique to this probe were carried out; they included linearity calibrations for each channel of the hyperspectral imaging system to ensure consistent linear responses of individual channels, and spectral response calibrations of individual channels for each fiber size group and between the three groups of different size fibers. Finally, applications of this new multichannel probe were demonstrated through the optical property measurement of liquid model samples and tomatoes of different maturity levels. The multichannel probe offers new capabilities for optical property measurement and quality detection of food and agricultural products.

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