Premium cocoa beans are important for fine chocolate manufacturing. However, cocoa beans may suffer from improper management practices that reduce their final quality. The objective of this study was to establish a non-invasive and high throughput grading system for cocoa bean (whole seeds) using hyperspectral imaging technique, in combination with advanced machine learning methods. Six hundred cocoa beans were collected and scanned using a HySpex Classic SWIR camera covering the spectral range from 970 to 2500 nm, with a spatial resolution of 250 μm, and a spectral sampling of 5.45 nm. Each bean was then graded using cut test methodology, the internationally recognized standard procedure in the market for cocoa trade. A maximum entropy multiclass classification model was built based on the hyperspectral cube and results from the cut test. Cocoa beans were identified into different classes: good beans, under-fermented beans, slaty beans, and other low-quality beans. For the most critical classes (good, under-fermented and slaty), a classification accuracy close to 80% was achieved without having to cut the beans open. The classification model can also distinguish other defects such as germination, over-fermentation, mold, and white beans. The proposed hyperspectral solution can significantly increase the onsite evaluation capabilities for large number of samples, potentially applicable to full batches of cocoa beans. The analysis of all beans in a batch can provide a more reliable assessment of the overall quality, compared to the results traditionally obtained from cut tests using small sample sets from batches of several tons.
HySpex is presenting an integrated solution for hyperspectral drill core imaging. The system’s mineral mapping capabilities are presented in close cooperation with renowned academic and industrial partners through the Center to Advance the Science of Exploration to Reclamation in Mining (CASERM) led by the Colorado School of Mines and Virginia Tech. Utilizing HySpex cameras covering the spectral range between 400 and 2500 nm, the system is capable of scanning full core boxes in seconds. Using Prediktera’s new Breeze-GEO Software, real-time mineral mapping of the highest quality is achieved. Apart from different interactive qualitative and quantitative data analysis tools offered by Breeze, the platform includes the publicly available USGS Material Identification and Classification Algorithm (MICA) for mineral identification, as well as the Minimum Wavelength Mapping (MWL) algorithm. The scanner’s capabilities are demonstrated using drill cores from the LaRonde-Penna deposit. The deposit is located within the Archean Abitibi greenstone belt of Ontario and Quebec, Canada, which is home to numerous Volcanogenic Massive Sulfide (VMS) deposits. LaRonde-Penna contains an endowment of 71 Mt of ore grading on average 3.9 g/t Au and economic grades of Zn, Cu and Pd. Because the deposits have been studied extensively over the past decades, cores from the deposit open up a unique opportunity for research and development.
The HySpex Mjolnir-1024 hyperspectral camera provides a unique combination of small form factor and low mass combined with high performance and scientific grade data quality. The camera has spatial resolution of 1024 pixels, spectral resolution of 200 bands within 400 nm to 1000 nm wavelength range and F1.8 optics that ensures high light throughput. Rugged design with good thermal and mechanical stability makes Mjolnir-1024 an excellent option for a wide range of scientific applications for airborne UAV operations and field applications. The optical architecture is based on the high-end ODIN-1024 system and features a total FOV of 20 degrees with approximately 0.1 pixel residual keystone effect and even smaller residual smile effect after resampling. With a total mass of less than 4 kg including hyperspectral camera, data acquisition unit, IMU and GPS, the system is suitable for even relatively small UAVs. The system is generic and can be deployed on a wide range of UAVs with various downlink capabilities. The ground station software enables full control of the sensor settings and has the capability to show in real time the location of the UAV, plot the flight path of the UAV and display a georeferenced waterfall preview image in order to give instant feedback on spatial coverage. The system can be triggered automatically by the UAV’s flight management system, but can also be controlled manually. Mjolnir-1024 housing contains both the camera hardware and a high performance onboard computer. The computer enables advanced processing capabilities such as real-time georeferencing based on the data streams from the camera and INS. The system is also capable of performing real-time image analysis such as anomaly detection, NDVI and SAM. The data products can be overlaid on top of various background maps and images in real time. The real-time processing results can also be downlinked and displayed directly on the monitor of the ground station.
The healing process of chronic wounds is complex, and the complete pathogenesis is not known. Diagnosis is currently based on visual inspection, biopsies and collection of samples from the wound surface. This is often time consuming, expensive and to some extent subjective procedures. Hyperspectral imaging has been shown to be a promising modality for optical diagnostics. The main objective of this study was to identify a suitable technique for reproducible classification of hyperspectral data from a wound and the surrounding tissue. Two statistical classification methods have been tested and compared to the performance of a dermatologist. Hyperspectral images (400-1000 nm) were collected from patients with venous leg ulcers using a pushbroom-scanning camera (VNIR 1600, Norsk Elektro Optikk AS).Wounds were examined regularly over 4 - 6 weeks. The patients were evaluated by a dermatologist at every appointment. One patient has been selected for presentation in this paper (female, age 53 years). The oxygen saturation of the wound area was determined by wavelength ratio metrics. Spectral angle mapping (SAM) and k-means clustering were used for classification. Automatic extraction of endmember spectra was employed to minimize human interaction. A comparison of the methods shows that k-means clustering is the most stable method over time, and shows the best overlap with the dermatologist’s assessment of the wound border. The results are assumed to be affected by the data preprocessing and chosen endmember extraction algorithm. Results indicate that it is possible to develop an automated method for reliable classification of wounds based on hyperspectral data.
KEYWORDS: Sensors, Cameras, Signal to noise ratio, Signal detection, Luminescence, Electron multiplying charge coupled devices, Biomedical optics, Skin, Spectrometers, Electromyography
Hyperspectral imaging provides means for characterizing large biological samples with microscopic spatial
resolution and a narrow spectral sampling interval. However, this approach requires having a measurable light
signal in each spectral band. Overcoming the limitations imposed by working with biological samples requires
the use of a highly sensitive sensor to detect weak signals. For this study we have built and compared the
performance of two imaging spectrometers using optimized for low light environments: an electron-multiplying
CCD (EMCCD) and a scientific CMOS (sCMOS). Both systems have been designed to lower the risk of
damaging photosensitive samples, delay the bleaching of fluorophores and detect weak fluorescence signals. The
cameras work within the VNIR spectral region (400 nm - 900 nm) with a spectral sampling lower than 4 nm. The
produced images have scene pixel sizes smaller than 25 μm and a field of view larger than 25 mm. The systems
have been tested side to side measuring the diffusion front of a fluorescent tag in samples of porcine skin in
challenging light conditions. The study aimed to show the advantages and limitations of each approach.
Preliminary results show good performance of the EMCCD for fluorescence applications, whereas more
experimental results are needed to be able to conclude on the performance of the sCMOS sensor. However, the
sCMOS appears promising for imaging scenes with high dynamics in low light settings.
Optical diagnostics of bruised skin might provide important information for characterization and age determination
of such injuries. Hyperspectral imaging is one of the optical techniques that have been employed for bruise
characterization. This technique combines high spatial and spectral resolution and makes it possible to study
both chromophore signatures and -distributions in an injury. Imaging and spectroscopy in the visible spectral
range have resulted in increased knowledge about skin bruises. So far the SWIR region has not been explored for
this application. The main objective of the current study was to characterize bruises in the SWIR wavelength
range. Hyperspectral images in the SWIR (950-2500nm ) and VNIR (400-850nm) spectral range were collected
from 3 adult volunteers with bruises of known age. Data were collected over a period of 8 days. The data were
analyzed using spectroscopic techniques and statistical image analysis. Preliminary results from the pilot study
indicate that SWIR hyperspectral imaging might be an important supplement to imaging in the visible part of
the spectrum. The technique emphasizes local edema and gives a possibility to visualize features that cannot
easily be seen in the visible part of the spectrum.
Hyperspectral fluorescence imaging is a modality combining high spatial and spectral resolution with increased
sensitivity for low photon counts. The main objective of the current study was to investigate if this technique is a suitable
tool for characterization of diffusion properties in human skin. This was done by imaging fluorescence from Alexa 488
in ex vivo human skin samples using an sCMOS based hyperspectral camera. Pre-treatment with acetone, DMSO and
mechanical micro-needling of the stratum corneum created variation in epidermal permeability between the measured
samples. Selected samples were also stained using fluorescence labelled biopolymers. The effect of fluorescence
enhancers on transdermal diffusion could be documented from the collected data. Acetone was found to have an
enhancing effect on the transport, and the results indicate that the biopolymers might have a similar effect, The
enhancement from these compounds were not as prominent as the effect of mechanical penetration of the sample using a
micro-needling device. Hyperspectral fluorescence imaging has thus been proven to be an interesting tool for
characterization of fluorophore diffusion in ex vivo skin samples. Further work will include repetition of the
measurements in a shorter time scale and mathematical modeling of the diffusion process to determine the diffusivity in
skin for the compounds in question.
The new "scientific CMOS" (sCMOS) sensor technology has been tested for use in hyperspectral imaging. The sCMOS
offers extremely low readout noise combined with high resolution and high speed, making it attractive for hyperspectral
imaging applications. A commercial HySpex hyperspectral camera has been modified to be used in low light conditions
integrating an sCMOS sensor array. Initial tests of fluorescence imaging in challenging light settings have been
performed. The imaged objects are layered phantoms labelled with controlled location and concentration of fluorophore.
The camera has been compared to a state of the art spectral imager based on CCD technology. The image quality of the
sCMOS-based camera suffers from artifacts due to a high density of pixels with excessive noise, attributed to the high
operating temperature of the array. Image processing results illustrate some of the benefits and challenges of the new
sCMOS technology.
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