Abstract: Plastic and microplastic pollution in human food chain is a big problem for human health that requires more elaborated techniques that can identify their presences in different kinds of food. Hyperspectral imaging technique is an optical technique than can detect the presence of different elements in an image and can be used to detect plastics and microplastics in a scene. To do this statistical techniques are required that need to be evaluated and compared in order to find the more efficient ones. In this work, two problems related to the presence of plastics are addressed, the first is to detect and identify pieces of plastic immersed in almond seeds, and the second problem is to detect and quantify microplastic in almond flour. To do this we make use of the analysis hyperspectral images taken in the range of 900 to 1700 nm using 4 unmixing techniques of hyperspectral imaging which are: least squares unmixing (LSU), non-negatively constrained least squares unmixing (NCLSU), fully constrained least squares unmixing (FCLSU), and scaled constrained least squares unmixing (SCLSU). NCLSU, FCLSU, SCLSU techniques manage to find the region where the plastic is found and also manage to quantify the amount of microplastic contained in the almond flour. The SCLSU technique estimated a 13.03% abundance of microplastics and 86.97% of almond flour compared to 16.66% of microplastics and 83.33% abundance of almond flour prepared for the experiment. Results show the feasibility of applying near-infrared hyperspectral image analysis for the detection of plastic contaminants in food.
Abstract: The article presents results from the AF3 project “Advanced Forest Fire Fighting” focused on Unmanned Aircraft Systems (UAS)-based 3D surveillance and 3D area mapping using high-resolution photogrammetric methods from multispectral imaging, also taking advantage of the 3D scanning techniques from the SCAN4RECO project. We also present a proprietary embedded sensor system used for the detection of fire ignitions in the forest using near-infrared based scanner with weight and form factors allowing it to be easily deployed on standard commercial micro-UAVs, such as DJI Inspire or Mavic. Results from real-life pilot trials in Greece, Spain, and Israel demonstrated added-value in the use of UAS for precise and reliable detection of forest fires, as well as high-resolution 3D aerial modeling for accurate quantification of human resources and equipment required for firefighting.
Abstract: Wood decay is addressed continuously within the wood industry through use and development of wood preservatives. The increasing awareness on the negative effects of many chemicals towards the environment is causing political restrictions in their use and creating more urgent need for research on green alternatives. This paper discusses some of the possible natural extracts for wood preserving applications and compares the analytical methods available for testing their behavior and efficiency against decay fungi. The results indicate that natural extracts have interesting chemical constituents that delay fungal growth but vary in efficiency depending on the chemical concentration and substrate used. Results also suggest that presence and redistribution of preservatives in wood during exposure trials can be assessed by spectral imaging methods although standardized methods are not available. This study concludes that, in addition to the many standard methods available, there is a need to develop new faster methods for screening potential preservative formulation while maintaining the comparability and relevance of results.
Abstract: Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no information about the given data cube. Sparsity is one of the recent approaches used in the source recovery or unmixing techniques. The l1-norm optimization problem “basis pursuit” could be used as a sparsity-based approach to solve this unmixing problem where the endmembers is assumed to be sparse in an appropriate domain known as dictionary. This optimization problem is solved using proximal method “iterative thresholding”. The l1-norm basis pursuit optimization problem as a sparsity-based unmixing technique was used to unmix real and synthetic hyperspectral data cubes.
Abstract: Hard seeds will not grow and can cause mold in sprouting process. Thus, the hard seeds need to be separated from the normal seeds. Near infrared hyperspectral imaging in a range of 900 to 1700 nm was implemented to develop a model by partial least squares discriminant analysis to discriminate the hard seeds from the normal seeds. The orientation of the seeds was also studied to compare the performance of the models. The model based on hilum-up orientation achieved the best result giving the coefficient of determination of 0.98, and root mean square error of prediction of 0.07 with classification accuracy was equal to 100%.
Abstract: Mineral mapping on the Moon surface provides the clue to understand the origin, evolution, stratigraphy and geological history of the Moon. Recently, reflectance imaging spectroscopy plays a significant role in identifying minerals on the planetary surface in the Visible to NIR region of the electromagnetic spectrum. The Moon Mineralogy Mapper (M3) onboard Chandrayaan-1 provides unprecedented spectral data of lunar surface to study about the Moon surface. Here we used the M3 sensor data (hyperspectral imaging spectroscopy) for analysing mineralogy of Orientale basin region on the Moon surface. Reflectance spectrums were sampled from different locations of the basin and continuum was removed using ENvironment for Visualizing Images (ENVI) software. Reflectance spectra of unknown mineral composition were compared with known Reflectance Experiment Laboratory (RELAB) spectra for discriminating mineralogy. Minerals like olivine, Low-Ca Pyroxene (LCP), High-Ca Pyroxene (HCP) and plagioclase were identified. In addition to these minerals, an unusual type of spectral signature was identified, which indicates the probable Fe-Mg-spinel lithology in the basin region.
Abstract: Nowadays, food safety is a great public concern;
therefore, robust and effective techniques are required for detecting
the safety situation of goods. Hyperspectral Imaging (HSI) is an
attractive material for researchers to inspect food quality and safety
estimation such as meat quality assessment, automated poultry
carcass inspection, quality evaluation of fish, bruise detection of
apples, quality analysis and grading of citrus fruits, bruise detection
of strawberry, visualization of sugar distribution of melons,
measuring ripening of tomatoes, defect detection of pickling
cucumber, and classification of wheat kernels. HSI can be used to
concurrently collect large amounts of spatial and spectral data on the
objects being observed. This technique yields with exceptional
detection skills, which otherwise cannot be achieved with either
imaging or spectroscopy alone. This paper presents a nonlinear
technique based on kernel Fukunaga-Koontz transform (KFKT) for
detection of fat content in ground meat using HSI. The KFKT which
is the nonlinear version of FKT is one of the most effective
techniques for solving problems involving two-pattern nature. The
conventional FKT method has been improved with kernel machines
for increasing the nonlinear discrimination ability and capturing
higher order of statistics of data. The proposed approach in this paper
aims to segment the fat content of the ground meat by regarding the
fat as target class which is tried to be separated from the remaining
classes (as clutter). We have applied the KFKT on visible and nearinfrared
(VNIR) hyperspectral images of ground meat to determine
fat percentage. The experimental studies indicate that the proposed
technique produces high detection performance for fat ratio in ground
meat.
Abstract: The increasing demand of gallium, indium and
rare-earth elements for the production of electronics, e.g. solid
state-lighting, photovoltaics, integrated circuits, and liquid crystal
displays, will exceed the world-wide supply according to current
forecasts. Recycling systems to reclaim these materials are not yet in
place, which challenges the sustainability of these technologies. This
paper proposes a multispectral imaging system as a basis for a vision
based recognition system for valuable components of electronics
waste. Multispectral images intend to enhance the contrast of images
of printed circuit boards (single components, as well as labels) for
further analysis, such as optical character recognition and entire
printed circuit board recognition. The results show, that a higher
contrast is achieved in the near infrared compared to ultraviolett and
visible light.
Abstract: Unwanted side effects because of spectral aliasing and spectral imaging during signal processing would be the major concern over the sampling rate alteration. Multirate-multistage implementation of digital filter could come about a large computational saving than single rate filter suitable for sample rate conversion. This implementation can further improve through high-level architectural transformation in circuit level. Reallocating registers and relocating flip-flops across logic gates through retiming certainly a prominent sequential transformation technology, that optimize hardware circuits to achieve faster clocking speed without affecting the functionality. In this paper, we proposed an efficient compensated cascade Integrator comb (CIC) decimation filter structure that analyze the consequence of filter order variation which has a retimed FIR filter being compensator while using the cutset retiming technique and achieved an improvement in the passband droop by 14% to 39%, in computation time by 38.04%, 25.78%, 12.21%, 6.69% and 4.44% and reduction in path delay by 62.27%, 72%, 86.63%, 91.56% and 94.42% of 3, 6, 8, 12 and 24 order filter respectively than the non-retimed CIC compensation filter.
Abstract: Any digital processing performed on a signal with larger nyquist interval requires more computation than signal processing performed on smaller nyquist interval. The sampling rate alteration generates the unwanted effects in the system such as spectral aliasing and spectral imaging during signal processing. Multirate-multistage implementation of digital filter can result a significant computational saving than single rate filter designed for sample rate conversion. In this paper, we presented an efficient cascaded integrator comb (CIC) decimation filter that perform fast down sampling using signed digit adder algorithm with compensated frequency droop that arises due to aliasing effect during the decimation process. This proposed compensated CIC decimation filter structure with a hybrid signed digit (HSD) fast adder provide an improved performance in terms of down sampling speed by 65.15% than ripple carry adder (RCA) and reduced area and power by 57.5% and 0.01 % than signed digit (SD) adder algorithms respectively.
Abstract: Near-infrared (NIR) spectroscopy is a widely used
method for material identification for laboratory and industrial applications.
While standard spectrometers only allow measurements at
one sampling point at a time, NIR Spectral Imaging techniques can
measure, in real-time, both the size and shape of an object as well as
identify the material the object is made of. The online classification
and sorting of recovered paper with NIR Spectral Imaging (SI)
is used with success in the paper recycling industry throughout
Europe. Recently, the globalisation of the recycling material streams
caused that water-based flexographic-printed newspapers mainly from
UK and Italy appear also in central Europe. These flexo-printed
newspapers are not sufficiently de-inkable with the standard de-inking
process originally developed for offset-printed paper. This de-inking
process removes the ink from recovered paper and is the fundamental
processing step to produce high-quality paper from recovered paper.
Thus, the flexo-printed newspapers are a growing problem for the
recycling industry as they reduce the quality of the produced paper
if their amount exceeds a certain limit within the recovered paper
material.
This paper presents the results of a research project for the
development of an automated entry inspection system for recovered
paper that was jointly conducted by CTR AG (Austria) and PTS
Papiertechnische Stiftung (Germany). Within the project an NIR
SI prototype for the identification of flexo-printed newspaper has
been developed. The prototype can identify and sort out flexoprinted
newspapers in real-time and achieves a detection accuracy
for flexo-printed newspaper of over 95%. NIR SI, the technology the
prototype is based on, allows the development of inspection systems
for incoming goods in a paper production facility as well as industrial
sorting systems for recovered paper in the recycling industry in the
near future.
Abstract: Lanthanide-doped upconversion nanoparticles which can convert near-infrared lights to visible lights have attracted growing interest because of their great potentials in fluorescence imaging. Upconversion fluorescence imaging technique with excitation in the near-infrared (NIR) region has been used for imaging of biological cells and tissues. However, improving the detection sensitivity and decreasing the absorption and scattering in biological tissues are as yet unresolved problems. In this present study, a novel NIR-reflected multispectral imaging system was developed for upconversion fluorescent imaging in small animals. Based on this system, we have obtained the high contrast images without the autofluorescence when biocompatible UCPs were injected near the body surface or deeply into the tissue. Furthermore, we have extracted respective spectra of the upconversion fluorescence and relatively quantify the fluorescence intensity with the multispectral analysis. To our knowledge, this is the first time to analyze and quantify the upconversion fluorescence in the small animal imaging.
Abstract: Breast carcinoma is the most common form of cancer
in women. Multicolour fluorescent in-situ hybridisation (m-FISH) is
a common method for staging breast carcinoma. The interpretation
of m-FISH images is complicated due to two effects: (i) Spectral
overlap in the emission spectra of fluorochrome marked DNA probes
and (ii) tissue autofluorescence. In this paper hyper-spectral images of
m-FISH samples are used and spectral unmixing is applied to produce
false colour images with higher contrast and better information
content than standard RGB images. The spectral unmixing is realised
by combinations of: Orthogonal Projection Analysis (OPA), Alterating
Least Squares (ALS), Simple-to-use Interactive Self-Modeling
Mixture Analysis (SIMPLISMA) and VARIMAX. These are applied
on the data to reduce tissue autofluorescence and resolve the spectral
overlap in the emission spectra. The results show that spectral unmixing
methods reduce the intensity caused by tissue autofluorescence by
up to 78% and enhance image contrast by algorithmically reducing
the overlap of the emission spectra.