scholarly journals Detection of different chemical binders in coatings using hyperspectral imaging

2021 ◽  
Author(s):  
Bahman Raeissi ◽  
Muhammad Ahsan Bashir ◽  
Joseph L. Garrett ◽  
Milica Orlandic ◽  
Tor Arne Johansen ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Chemical Structure ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Diagnostic Information ◽  
Organic Coatings ◽  
Electromagnetic Spectrum ◽  
Metallic Structures ◽  
Analytical Technique ◽  
Applied Coating

AbstractOrganic coatings protect metallic structures of significant commercial value. Regular inspections of coatings are required to ensure their integrity and, therefore, to verify their stated performance. However, for metallic structures located in harsh places, coating inspection can pose significant safety and logistical challenges. Near-infrared (NIR) spectroscopy is a rapid, nondestructive and relatively inexpensive analytical technique. It is currently employed to analyze different chemicals in fields like agriculture, food, and pharmaceuticals. Similarly, hyperspectral imaging (HSI) creates a spatial map of spectral information by measuring light reflected from a material. In this work, hyperspectral imaging in the NIR portion of the electromagnetic spectrum (NIR-HSI) is used to accurately distinguish between the chemically different binders employed in commercial organic coatings. In addition, k-means clustering is explored as a tool to provide diagnostic information about the spatial inhomogeneities in the chemical structure of an applied coating, which, if undetected, can lead to coating defects during service life. The results of this work suggest that the NIR-HSI could be used for remote inspections of organic coatings.

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.

scholarly journals From the Laboratory to The Vineyard—Evolution of The Measurement of Grape Composition using NIR Spectroscopy towards High-Throughput Analysis

2019 ◽  
Vol 8 (4) ◽  
pp. 21
Author(s):  
Aoife Power ◽  
Vi Khanh Truong ◽  
James Chapman ◽  
Daniel Cozzolino
Keyword(s):  
Chemical Composition ◽  
Hyperspectral Imaging ◽  
High Throughput ◽  
Analytical Methods ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Chemical Compounds ◽  
Spectroscopic Techniques ◽  
High Throughput Analysis ◽  
Laboratory Methods

Compared to traditional laboratory methods, spectroscopic techniques (e.g., near infrared, hyperspectral imaging) provide analysts with an innovative and improved understanding of complex issues by determining several chemical compounds and metabolites at once, allowing for the collection of the sample “fingerprint”. These techniques have the potential to deliver high-throughput options for the analysis of the chemical composition of grapes in the laboratory, the vineyard and before or during harvest, to provide better insights of the chemistry, nutrition and physiology of grapes. Faster computers, the development of software and portable easy to use spectrophotometers and data analytical methods allow for the development of innovative applications of these techniques for the analyses of grape composition.

scholarly journals Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials

2014 ◽  
Vol 43 (24) ◽  
pp. 8200-8214 ◽  
Author(s):  
Marena Manley
Keyword(s):  
Infrared Spectroscopy ◽  
Hyperspectral Imaging ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Biological Materials ◽  
Destructive Analysis ◽  
Non Destructive

Principles, interpretation and applications of near-infrared (NIR) spectroscopy and NIR hyperspectral imaging are reviewed.

scholarly journals Hyperspectral and Multispectral Image Fusion Techniques

2020 ◽  
Vol 8 (5) ◽  
pp. 467-471
Keyword(s):  
Image Fusion ◽  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Spatial Information ◽  
Hyperspectral Image ◽  
Qualitative Comparative Analysis ◽  
Infrared Region ◽  
Multispectral Image ◽  
Electromagnetic Spectrum ◽  
Fusion Methods

The hyper spectral image covers a broad range of wavelengths in electromagnetic spectrum, spanning from visible to near-infrared region. The basic objective of hyperspectral imaging is to attain the spectrum for each pixel in the image of a scene, with the aim of identifying objects in the scene and its classification. The hyperspectral images give detailed spectral information but their spatial resolution is very poor. So to enhance the visual quality of the hyperspectral image, we can perform image fusion with high spatial information multispectral image. This paper provides a complete description of hyperspectral imaging and image fusion methods of hyperspectral and multispectral images. A quantitative and qualitative comparative analysis on performance of various hyperspectral and multispectral image fusion techniques are also done.

scholarly journals Use of infrared hyperspectral imaging as an aid for paint identification

2016 ◽  
Author(s):  
A. Polak ◽  
T. Kelman ◽  
P. Murray ◽  
S. Marshall ◽  
D. Stothard ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Imaging System ◽  
Classification Problem ◽  
Extensive Study ◽  
Electromagnetic Spectrum ◽  
New Techniques ◽  
Art Authentication ◽  
Infrared Spectral ◽  
Non Destructive

Art authentication is a complicated process that often requires the extensive study of high value objects. Although a series of non-destructive techniques is already available for art scientists, new techniques, extending current possibilities, are still required. In this paper, the use of a novel mid-infrared tunable imager is proposed as an active hyperspectral imaging system for art work analysis. The system provides access to a range of wavelengths in the electromagnetic spectrum (2500–3750 nm) which are otherwise difficult to access using conventional hyperspectral imaging (HSI) equipment. The use of such a tool could be beneficial if applied to the paint classification problem and could help analysts map the diversity of pigments within a given painting. The performance of this tool is demonstrated and compared with a conventional, off-the-shelf HSI system operating in the near infrared spectral region (900–1700 nm). Various challenges associated with laser-based imaging are demonstrated and solutions to these challenges as well as the results of applying classification algorithms to datasets captured using both HSI systems are presented. While the conventional HSI system provides data in which more pigments can be accurately classified, the result of applying the proposed laser-based imaging system demonstrates the validity of this technique for application in art authentication tasks.

Two-Dimensional Vibration Spectroscopy. V: Correlation of Mid- and near Infrared of Hard Red Winter and Spring Wheats

1996 ◽  
Vol 4 (1) ◽  
pp. 139-152 ◽  
Author(s):  
F.E. Barton ◽  
D.S. Himmelsbach ◽  
D.D. Archibald
Keyword(s):  
Raman Spectra ◽  
Spring Wheat ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Correlation Spectroscopy ◽  
Analytical Models ◽  
Electromagnetic Spectrum ◽  
Two Dimensional ◽  
Stretching Vibrations ◽  
Agricultural Materials

Two-dimensional correlation spectroscopy across the near infrared (NIR) and mid-infrared (MIR) regions have been used to explain the NIR spectra of hard red winter and spring wheat and provide additional confidence in analytical models developed with empirical data. Recent studies have shown that the major C–H stretching vibrations and some of the aromatic C–H and ring stretching vibrations and the minor vibrations in the “fingerprint” region are correlated also. The technique has been expanded to include Raman spectra. The Raman spectra were enhanced with Maximum Likelihood methods to improve signal-to-noise (S/N) while maintaining resolution. This was necessary to eliminate the effects of fluorescence which degrades S/N. The use of NIR lasers at 1.1 μm generally eliminates fluorescence as a problem, but it is still quite prevalent in agricultural materials. The original study did not show any significant correlations to aromatic functionality. However, the band at 1552 nm correlates to the Raman and not to the MIR. This band has shown up in NIR spectroscopy models for the determination of lignin, but is not readily observed in the MIR. Thus it correlates to a Raman active rather than a MIR active band. The same phenomena are observed for the amide I, II and III bands for wheat. The interesting features from NIR and MIR are that there are correlations that distinguish winter from spring wheat. These, and the Raman spectra of wheat, will be shown. These studies show that multiple regions of the electromagnetic spectrum can be, and in deed need to be, used to interpret adequately the spectral and statistical results we have traditionally obtained in the NIR.

Potential of Near-Infrared (NIR) Spectroscopy and Hyperspectral Imaging for Quality and Safety Assessment of Fruits: an Overview

2019 ◽  
Vol 12 (11) ◽  
pp. 2438-2458 ◽  
Author(s):  
Indurani Chandrasekaran ◽  
Shubham Subrot Panigrahi ◽  
Lankapalli Ravikanth ◽  
Chandra B. Singh
Keyword(s):  
Hyperspectral Imaging ◽  
Safety Assessment ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Quality And Safety

scholarly journals Assessment of pesticide coating on cereal seeds by near infrared hyperspectral imaging

2017 ◽  
Author(s):  
Ph. Vermeulen ◽  
P. Flémal ◽  
O. Pigeon ◽  
P. Dardenne ◽  
J. Fernández Pierna ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Seed Quality ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Ultra Performance Liquid Chromatography

Classical chromatographic methods, such as ultra performance liquid chromatography (UPLC), are used as reference methods to assess seed quality and homogeneous pesticide coating of seeds. These methods have some important drawbacks since they are time consuming, expensive, destructive and require a substantial amount of solvent, among others. Near infrared (NIR) spectroscopy seems to be an interesting alternative technique for the determination of the quality of seed treatment and avoids most of these drawbacks. The objective of this study was to assess the quality of pesticide coating treatment by near infrared hyperspectral imaging (NIR-HSI) by analysing, on a seed-by-seed basis, several seeds simultaneously in comparison to NIR spectroscopy and UPLC as the reference method. To achieve this goal, discrimination—partial least squares discriminant analysis (PLS-DA)—models and regression—partial least squares (PLS)—models were developed. The results obtained by NIR-HSI are compared to the results obtained with NIR spectroscopy and UPLC instruments. This study has shown the potential of NIR hyperspectral imaging to assess the quality/homogeneity of the pesticide coating on seeds.

scholarly journals Mapping nutrient concentration in pasture using hyperspectral imaging

2015 ◽  
Vol 77 ◽  
pp. 47-50 ◽  
Author(s):  
I. Yule ◽  
R. Pullanagari ◽  
M. Irwin ◽  
P. Mcveagh ◽  
G. Kereszturi ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Precision Agriculture ◽  
Nutrient Concentration ◽  
Large Scale ◽  
Near Infrared ◽  
Nutrient Content ◽  
Matter Content ◽  
Electromagnetic Spectrum ◽  
Dry Matter Content ◽  
Hyperspectral Sensing

Hyperspectral sensing using ground-based equipment has been demonstrated to be successful in determining pasture nutrient content (N, P, K, S) and parameters such as dry matter content and metabolisable energy. This technology needed to be up-scaled so that large areas could be rapidly covered with adequate spatial resolution. This paper describes work which demonstrates a progression from hyperspectral sensing to hyperspectral imaging which utilises the visible, near infrared and short wave infrared parts of the electromagnetic spectrum. Large scale calibration and validation field trials were conducted at the same time as hyperspectral imaging was completed. These trials demonstrate the feasibility of producing information, in detailed map form, on pasture nutrient concentration and other parameters to inform fertiliser placement decisions as well as other farm management tasks. The technique effectively produces a forage analysis for every square meter of any farm. Keywords: hyperspectral imaging, precision agriculture.

scholarly journals Application of the Non-Destructive NIR Technique for the Evaluation of Strawberry Fruits Quality Parameters

Foods ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 441 ◽  
Author(s):  
Manuela Mancini ◽  
Luca Mazzoni ◽  
Francesco Gagliardi ◽  
Francesca Balducci ◽  
Daniele Duca ◽  
...  
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Infrared Region ◽  
Quality Parameters ◽  
Soluble Solids ◽  
Electromagnetic Spectrum ◽  
Least Squares Regression ◽  
Solids Content ◽  
Non Destructive

The determination of strawberry fruit quality through the traditional destructive lab techniques has some limitations related to the amplitude of the samples, the timing and the applicability along all phases of the supply chain. The aim of this study was to determine the main qualitative characteristics through traditional lab destructive techniques and Near Infrared Spectroscopy (NIR) in fruits of five strawberry genotypes. Principal Component Analysis (PCA) was applied to search for spectral differences among all the collected samples. A Partial Least Squares regression (PLS) technique was computed in order to predict the quality parameters of interest. The PLS model for the soluble solids content prediction was the best performing—in fact, it is a robust and reliable model and the validation values suggested possibilities for its use in quality applications. A suitable PLS model is also obtained for the firmness prediction—the validation values tend to worsen slightly but can still be accepted in screening applications. NIR spectroscopy represents an important alternative to destructive techniques, using the infrared region of the electromagnetic spectrum to investigate in a non-destructive way the chemical–physical properties of the samples, finding remarkable applications in the agro-food market.

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