Hyperspectral Imaging Based Corrosion Detection in Nuclear Packages
By: Jaime Zabalza, Paul Murray, Stuart Bennett, Andrew Campbell, Stephen Marshall, Jinchang Ren, Yijun Yan, Robert Bernard, Steve Hepworth, Simon Malone, Neil Cockbain, Douglas Offin, and Craig Holliday
Abstract
Storage packages for nuclear material are susceptible to corrosion, which can potentially undermine their structural integrity. Therefore, long-term monitoring is required. In this work, hyperspectral imaging (HSI) was evaluated as a nondestructive tool for detecting corrosion on stainless steel surfaces.
Hyperspectral Imaging for Cannabis Monitoring With Both Spatial & Spectral Information
By: John Margeson, Lynn Chandler Ph.D.
Abstract
Hyperspectral imaging is poised to make a significant impact on the cannabis industry because of its ability to simultaneously utilize the value of both spatial and spectral information. Current cannabis testing methods rely on spot sampling and do not capture enough data to measure the variability within a sample. Hyperspectral imaging is non-destructive and enables real-time test results, allowing rapid and complete product testing without the need to remove samples from product and prepare those samples for testing. Applications include determining cannabinoid concentration, moisture content testing, mold detection and monitoring, improved foreign-object detection in cultivation, enhanced testing for regulatory and law-enforcement reasons, and monitoring cannabis plant growth.
Hyperspectral imaging shines a light on food safety
By: Bob Whitby
Abstract
Just as detectives use ultraviolet light or dusting powder to find fingerprints, food producers have turned to hyperspectral imaging, or HSI, to examine fruit, vegetables, meat, and even crops still in the field. HSI works in spectrums beyond the capabilities of the human eye and at speeds that would be impossible for any worker to match.
Hyperspectral imaging technique to evaluate the firmness and the sweetness index of tomatoes
By: Anisur Rahman, Eunsoo Park, Bae Hyungjin, Byoung-Kwan Cho
Abstract
The objective of this study was to evaluate the firmness and the sweetness index (SI) of tomatoes with a hyperspectral imaging (HSI) technique within the wavelength range of 1000 – 1550 nm. The hyperspectral images of 95 tomatoes were acquired with a push-broom hyperspectral reflectance imaging system, from which the mean spectra of each tomato were extracted from the regions of interest.
Hyperspectral imaging technology for quality and safety evaluation of horticultural products
By: Yuzhen Lu, Wouter Saeys, Moon Kim, Yankun Peng, Renfu Lu
Abstract
In the past 20 years, hyperspectral imaging has been widely investigated as an emerging, promising technology for evaluating quality and safety of horticultural products. This technology has originated from remote sensing and joins the domains of machine vision and point spectroscopy to provide superior image segmentation for the detection of defects and contaminations, and to map the chemical composition.
Hyperspectral imaging through vacuum packaging for monitoring cheese biochemical transformation caused by Clostridium metabolism
By: Marlon M. Reis, Yash Dixit, Alistair Carr, Christine Tu, Faith Palevich, Tanushree Gupta, Mariza G. Reis
Abstract
Our results demonstrated the ability to use Hyperspectral Imaging combined with multivariate pattern recognition, to monitor the spatial and temporal biochemical processes associated with clostridial metabolism in cheese. Our maps of butyric acid concentration showed distinct patterns between control and Clostridium contaminated cheeses.
Hyperspectral Push-Broom Microscope Development and Characterization
By: Samuel Ortega, Raúl Guerr, María Díaz, Himar Fabelo, Sebastián López, Gustavo M. Callicó, Roberto Sarmiento
Abstract
Currently, the use of hyperspectral imaging (HSI) for the inspection of microscopic samples is an emerging trend in different fields. The use of push-broom hyperspectral (HS) cameras against other HSI technologies is motivated by their high spectral resolution and their capabilities to exploit spectral ranges beyond 1000 nm.
Hyperspectral Qualification of Aged Beef Sirloin
By: Ferenc Firtha, Anita Jasper, László Friedrich, József Felföldi
Abstract
Since the ageing process provides high added values that manifests in price, a quick, non-contact measurement method would be useful in industry to check ageing state. The objective of this study was to estimate the ageing time of beef sirloin samples by their reflected NIR spectra and hyperspectral datacube as well.`
Hyperspectral remote sensing for detecting geotechnical problems at Ray mine
By: Jingping He, Isabel Barton
Abstract
In this case study, we applied hyperspectral remote sensing for large-scale mapping and detection of minerals at a non-structure-related ground instability in the highwalls of the Ray mine near Tucson, Arizona. This combines drone- and tripod-mounted sensors, integrating hyperspectral with LiDAR and radar data, and using an iteratively refined spectral library based on site-specific sampling supported by ground truth.
Identification of Wheat Yellow Rust using Spectral and Texture Features of Hyperspectral Images
By: Anting Guo, Wenjiang Huang, Huichun Ye, Yingying Dong, Huiqin Ma, Yu Ren, Chao Ruan
Abstract
Wheat yellow rust is one of the most destructive diseases in wheat production and significantly affects wheat quality and yield. Accurate and non-destructive identification of yellow rust is critical to wheat production management. Hyperspectral imaging technology has proven to be effective in identifying plant diseases. We investigated the feasibility of identifying yellow rust on wheat leaves using spectral features and textural features (TFs) of hyperspectral images.
