Special Issue "Application of Hyperspectral Imaging for Nondestructive Measurement"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: 31 August 2019

Special Issue Editor

Guest Editor
Prof. Dr. Byoung-Kwan Cho

Nondestructive Bio-Sensing Laboratory, Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon, 34134, Korea
Website | E-Mail
Phone: +82-42-821-6715
Interests: hyperspectral imaging; spectral analysis; chemometrics; nondestructive sensing

Special Issue Information

Dear Colleagues,

Hyperspectral imaging technology has recently emerged as a powerful analytical technique that uses vibrational spectroscopy for nondestructive quality measurement of various materials. The previously described spectroscopic analytical methods (Vis/NIR, MIR, Fluorescence, Raman spectroscopies, etc.) are well-established, non-invasive analytical techniques for the analysis of materials. However, these techniques are point-based scanning techniques and only examine a relatively small area of a specimen; thus, these techniques are unable to provide spatial information that is important for many material inspection applications. Sample analysis is also more convenient and fast compared with the hyperspectral imaging technique because a large number of samples are analyzed at the same time, instead of the single sampling technique used by the other spectroscopic methods. Furthermore, HSI has instrumental flexibility and can be used to collect hyperspectral data for specimens with different sizes and shapes. In addition, the spectral region collected, spatial resolution, and field of view (FOV) can be adjusted depending on the application. With these advantages and flexibility, hyperspectral imaging has been successfully adopted in a variety of research and industry environments.

This Special Issue focuses on the latest research and development of hyperspectral imaging in nondestructive measurement applications. Accordingly, papers that demonstrate novel hyperspectral imaging technology concepts for nondestructive measurement are sought. These include papers dealing with theoretical analyses, and laboratory and field studies in various industries, such as agriculture, foods, pharmaceutics, natural science, etc.

We would like to invite you to submit original research papers for the “Application of Hyperspectral Imaging for Nondestructive Measurement” Special Issue.

Prof. Dr. Byoung-Kwan Cho
Guest Editor

Manuscript Submission Information

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Keywords

  • Hyperspectral imaging
  • Multispectral imaging
  • Chemical imaging
  • Spectral imaging
  • Nondestructive measurement
  • Quality evaluation
  • Sorting technique

Published Papers (2 papers)

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Research

Open AccessArticle Development of a Low-Cost Multi-Waveband LED Illumination Imaging Technique for Rapid Evaluation of Fresh Meat Quality
Appl. Sci. 2019, 9(5), 912; https://doi.org/10.3390/app9050912
Received: 21 January 2019 / Revised: 27 February 2019 / Accepted: 28 February 2019 / Published: 4 March 2019
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Abstract
Determining the quality of meat has always been essential for the food industry because consumers prefer superior quality meat. Therefore, the food industry requires the development of a rapid and non-destructive method for meat-quality determination. Over the past few years, a number of [...] Read more.
Determining the quality of meat has always been essential for the food industry because consumers prefer superior quality meat. Therefore, the food industry requires the development of a rapid and non-destructive method for meat-quality determination. Over the past few years, a number of techniques have been presented for monitoring meat–chemical attributes. However, most previous techniques are quite expensive, destructive, and require complex hardware to operate. Thus, in this work, we demonstrate a low-cost sensing technique (eliminating the expensive equipment and complicated design) for meat–chemical quality detection. The newly developed system was integrated with a low-cost monochrome camera and ordinary light-emitting diode (LED) light sources, with fifteen different wavebands ranging from 458 to 950 nm. The monochrome camera captures images of the meat sample across a spectral range from 458 to 950 nm using a single snapshot method. The chemical values (e.g., moisture, fat, and protein) were also determined using conventional methods. The collected images were combined to produce a multispectral data cube and to extract spectral data. Partial least squares (PLS) and support vector regression (SVR) modeling were used on the extracted spectra and chemical values. The developed models for meat samples displayed accurate chemical-component prediction ( R 2 > 0.80). Our model, based on a monochrome sensor using only fifteen wavebands, provided reasonable results compared with the previously developed expensive spectroscopic techniques. Therefore, this complementary metal-oxide semiconductor (CMOS) based multispectral sensing technique may have the potential to detect meat quality, thereby facilitating a simple, fast, and cost-effective method applicable to small-scale meat-processing industries. Full article
(This article belongs to the Special Issue Application of Hyperspectral Imaging for Nondestructive Measurement)
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Open AccessArticle Prediction of Douglas-Fir Lumber Properties: Comparison between a Benchtop Near-Infrared Spectrometer and Hyperspectral Imaging System
Appl. Sci. 2018, 8(12), 2602; https://doi.org/10.3390/app8122602
Received: 16 November 2018 / Revised: 5 December 2018 / Accepted: 10 December 2018 / Published: 13 December 2018
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Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Application of Hyperspectral Imaging for Nondestructive Measurement)
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