scholarly journals DMD-based hyperspectral imaging system with tunable spatial and spectral resolution

2019 ◽  
Vol 27 (12) ◽  
pp. 16995 ◽  
Author(s):  
Xue Dong ◽  
Xingchen Xiao ◽  
Yining Pan ◽  
Guangyao Wang ◽  
Yiting Yu
Keyword(s):  
Hyperspectral Imaging ◽  
Spectral Resolution ◽  
Imaging System

scholarly journals Study of the best decocting time of sun dried ginseng by using the hyperspectral imaging technology

2016 ◽  
Vol 09 (06) ◽  
pp. 1650006
Author(s):  
Qing He ◽  
Lan Liang ◽  
Zhenqiang Chen ◽  
Qichang Pang ◽  
Jing Zhao
Keyword(s):  
Fluorescence Imaging ◽  
Hyperspectral Imaging ◽  
Spectral Resolution ◽  
Equilibrium Condition ◽  
Imaging System ◽  
Test Sample ◽  
Tissue Fluid ◽  
Active Ingredients ◽  
Spectral Curves ◽  
Fluorescence Imaging System

In this research, a new method based on the hyperspectral imaging for searching the best decocting time of sun dried ginseng is reported. The spectral images at different decocting time of test sample have been taken by the staring hyperspectral fluorescence imaging system and the solubility of active ingredients have been discussed by analyzing the changes on the spectral curves. The spectral range of the system is 400–720[Formula: see text]nm and the spectral resolution is 5[Formula: see text]nm. In the decocting process, the active ingredients of nonsoaked ginseng was dissolved in the tissue fluid at first, and reached equilibrium condition at last after the precipitation–dissolution reciprocating process of boiling. At last, the experimental results show that the best decoction time of sun dried ginseng is about 60[Formula: see text]min after boiling.

scholarly journals Development of a Novel Embedded Relay Lens Microscopic Hyperspectral Imaging System for Cancer Diagnosis: Use of the Mice with Oral Cancer to Be the Example

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Yao-Fang Hsieh ◽  
Mang Ou-Yang ◽  
Jeng-Ren Duann ◽  
Jin-Chern Chiou ◽  
Nai-Wen Chang ◽  
...  
Keyword(s):  
Oral Cancer ◽  
Hyperspectral Imaging ◽  
Cancer Diagnosis ◽  
Spectral Resolution ◽  
Imaging System ◽  
Early Stage ◽  
High Spectral Resolution ◽  
Normal Cells ◽  
M 10

This paper develops a novel embedded relay lens microscopic hyperspectral imaging system (ERL-MHSI) with high spectral resolution (nominal spectral resolution of 2.8 nm) and spatial resolution (30 μm × 10 μm) for cancer diagnosis. The ERL-MHSI system has transmittance and fluorescence mode. The transmittance can provide the morphological information for pathological diagnosis, and the fluorescence of cells or tissue can provide the characteristic signature for identification of normal and abnormal. In this work, the development of the ERL-MHSI system is discussed and the capability of the system is demonstrated by diagnosing early stage oral cancer of twenty mice in vitro. The best sensitivity for identifying normal cells and squamous cell carcinoma (SCC) was 100%. The best specificity for identifying normal cells and SCC was 99%. The best sensitivity for identifying normal cells and dysplasia was 99%. The best specificity for identifying normal cells and dysplasia was 97%. This work also utilizes fractal dimension to analyze the morphological information and find the significant different values between normal and SCC.

scholarly journals Hyperspectral system trade-offs for illumination, hardware and analysis methods: a case study of seed mix ingredient discrimination

2020 ◽  
Author(s):  
Carolina Blanch-Pérez del Notario ◽  
Carlos López-Molina ◽  
Andy Lambrechts ◽  
Wouter Saeys
Keyword(s):  
Hyperspectral Imaging ◽  
Spectral Resolution ◽  
Food Industry ◽  
Near Infrared ◽  
Imaging System ◽  
Infrared Range ◽  
Analysis Methods ◽  
Trade Offs ◽  
The Impact

The discrimination power of a hyperspectral imaging system for image segmentation or object detection is determined by the illumination, the camera spatial–spectral resolution, and both the pre-processing and analysis methods used for image processing. In this study, we methodically reviewed the alternatives for each of those factors for a case study from the food industry to provide guidance in the construction and configuration of hyperspectral imaging systems in the visible near infrared range for food quality inspection. We investigated both halogen- and LED-based illuminations and considered cameras with different spatial–spectral resolution trade-offs. At the level of the data analysis, we evaluated the impact of binning, median filtering and bilateral filtering as pre- or post-processing and compared pixel-based classifiers with convolutional neural networks for a challenging application in the food industry, namely ingredient identification in a flour–seed mix. Starting from a basic configuration and by modifying the combination of system aspects we were able to increase the mean accuracy by at least 25 %. In addition, different trade-offs in performance-complexity were identified for different combinations of system parameters, allowing adaptation to diverse application requirements.

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

scholarly journals Prediction of Douglas-Fir Lumber Properties: Comparison between a Benchtop Near-Infrared Spectrometer and Hyperspectral Imaging System

2018 ◽  
Vol 8 (12) ◽  
pp. 2602 ◽  
Author(s):  
Laurence Schimleck ◽  
Joseph Dahlen ◽  
Seung-Chul Yoon ◽  
Kurt Lawrence ◽  
Paul Jones
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Imaging System ◽  
Nir Spectroscopy ◽  
Physical And Mechanical Properties ◽  
Douglas Fir ◽  
Modulus Of Rupture ◽  
Visual Grade ◽  
Fit Statistics ◽  
Infrared Spectrometer

Near-infrared (NIR) spectroscopy and NIR hyperspectral imaging (NIR-HSI) were compared for the rapid estimation of physical and mechanical properties of No. 2 visual grade 2 × 4 (38.1 mm by 88.9 mm) Douglas-fir structural lumber. In total, 390 lumber samples were acquired from four mills in North America and destructively tested through bending. From each piece of lumber, a 25-mm length block was cut to collect diffuse reflectance NIR spectra and hyperspectral images. Calibrations for the specific gravity (SG) of both the lumber (SGlumber) and 25-mm block (SGblock) and the lumber modulus of elasticity (MOE) and modulus of rupture (MOR) were created using partial least squares (PLS) regression and their performance checked with a prediction set. The strongest calibrations were based on NIR spectra; however, the NIR-HSI data provided stronger predictions for all properties. In terms of fit statistics, SGblock gave the best results, followed by SGlumber, MOE, and MOR. The NIR-HSI SGlumber, MOE, and MOR calibrations were used to predict these properties for each pixel across the transverse surface of the scanned samples, allowing SG, MOE, and MOR variation within and among rings to be observed.

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