The use of a non-contact Fourier interferometric, hyperspectral imaging system to quantify the absorption and reduced scattering coefficients of tissue-like turbid media over a broad spectral range

2002 ◽  
Author(s):  
T.H. Pham ◽  
F. Bevilacqua ◽  
T. Spott ◽  
J.S. Dam ◽  
B.J. Tromberg ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Spectral Range ◽  
Imaging System ◽  
Turbid Media ◽  
Scattering Coefficients ◽  
Broad Spectral Range

scholarly journals Measurement of Early Disease Blueberries Based on Vis/NIR Hyperspectral Imaging System

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5783
Author(s):  
Yuping Huang ◽  
Dezhen Wang ◽  
Ying Liu ◽  
Haiyan Zhou ◽  
Ye Sun
Keyword(s):  
Hyperspectral Imaging ◽  
Spectral Range ◽  
Imaging System ◽  
Early Stage ◽  
Partial Least Square ◽  
Least Square ◽  
Early Disease ◽  
Spectral Correlation ◽  
Fungal Damage ◽  
Optimal Classification

Blueberries, which are rich in nutrition, are susceptible to fungal infection during postharvest or storage. However, early detection of diseases in blueberry is challenging because of their opaque appearance and the inconspicuousness of spots in the early stage of disease. The goal of this study was to investigate the potential of hyperspectral imaging over the spectral range of 400–1000 nm to discriminate early disease in blueberries. Scanning electron microscope observation verified that fungal damage to the cellular structure takes place during the early stages. A total of 400 hyperspectral images, 200 samples each of healthy and early disease groups, were collected to obtain mean spectra of each blueberry samples. Spectral correlation analysis was performed to select an effective spectral range. Partial least square discrimination analysis (PLSDA) models were developed using two types of spectral range (i.e., full wavelength range of 400–1000 nm and effective spectral range of 685–1000 nm). The results showed that the effective spectral range made it possible to provide better classification results due to the elimination of the influence of irrelevant variables. Moreover, the effective spectral range combined with an autoscale preprocessing method was able to obtain optimal classification accuracies, with recognition rates of 100% and 99% for healthy and early disease blueberries. This study demonstrated that it is feasible to use hyperspectral imaging to measure early disease blueberries.

scholarly journals Identification of Apple Varieties Using a Multichannel Hyperspectral Imaging System

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5120 ◽  
Author(s):  
Yuping Huang ◽  
Yutu Yang ◽  
Ye Sun ◽  
Haiyan Zhou ◽  
Kunjie Chen
Keyword(s):  
Hyperspectral Imaging ◽  
Spectral Range ◽  
Near Infrared ◽  
Imaging System ◽  
Visible Region ◽  
Infrared Region ◽  
Apple Variety ◽  
Apple Varieties ◽  
Spatially Resolved ◽  
Variety Classification

This paper reports the nondestructive detection of apple varieties using a multichannel hyperspectral imaging system consisting of an illumination fiber and 30 detection fibers arranged at source–detector distances of 1.5–36 mm over the spectral range of 550–1650 nm. Spatially resolved (SR) spectra were obtained for 1500 apples, 500 each of three varieties from the same orchard to avoid environmental and geographical influences. Partial least squares discriminant analysis (PLSDA) models were developed for single SR spectra and spectral combinations to compare their performance of variety detection. To evaluate the effect of spectral range on variety detection, three types of spectra (i.e., visible region: 550–780 nm, near-infrared region: 780–1650 nm, full region: 550–1650 nm) were analyzed and compared. The results showed that the single SR spectra presented a different accuracy for apple variety classification, and the optimal SR spectra varied with spectral types. Spectral combinations had better accuracies for variety detection with best overall classifications of 99.4% for both spectral ranges in the NIR and full regions; however, the spectral combination could not improve the results over the optimal single SR spectra in the visible region. Moreover, the recognition of golden delicious (GD) was better than those of the other two varieties, with the best classification accuracy of 100% for three types of spectra. Overall, the multichannel hyperspectral imaging system provides more spatial-spectral information for the apples, and the results demonstrate that the technique gave excellent classifications, which suggests that the multichannel hyperspectral imaging system has potential for apple variety detection.

Mapping of fatty acids composition in shelled almonds analysed in bulk using a Hyperspectral Imaging system

LWT ◽  
2021 ◽  
Vol 138 ◽  
pp. 110678
Author(s):  
Irina Torres ◽  
Dolores Pérez-Marín ◽  
Miguel Vega-Castellote ◽  
María-Teresa Sánchez
Keyword(s):  
Fatty Acids ◽  
Hyperspectral Imaging ◽  
Imaging System ◽  
Fatty Acids Composition

scholarly journals Nondestructive and rapid determination of lignocellulose components of biofuel pellet using online hyperspectral imaging system

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Xuping Feng ◽  
Chenliang Yu ◽  
Xiaodan Liu ◽  
Yunfeng Chen ◽  
Hong Zhen ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging System ◽  
Rapid Determination

Design of a Cooperative Chemical Agent (CA) Detection Algorithm with the Hyperspectral Imaging System

2021 ◽  
Author(s):  
Hyeong-Geun Yu ◽  
Whimin Kim ◽  
Dong-Jo Park ◽  
Dong Eui Chang ◽  
Hyunwoo Nam
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging System ◽  
Detection Algorithm ◽  
Chemical Agent
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