Completing the picture of field-grown cereal crops: a new method for detailed leaf surface models in wheat.

BACKGROUND: The leaf angle distribution (LAD) is an important structural parameter of agricultural crops that influences light interception, radiation fluxes and consequently plant performance. Therefore, LAD and its parametrized form, the Beta distribution, is used in many photosynthesis models. However, in field cultivations, these parameters are difficult to assess and cereal crops in particular pose challenges since their leaves are thin, flexible, and often bent and twisted around their own axis. To our knowledge, there is only a very limited set of methods currently available to calculate LADs of field-grown cereal crops that explicitly takes these special morphological properties into account. RESULTS: In this study, a new processing pipeline is introduced that allows for the generation of realistic leaf surface models and the analysis of LADs of field-grown cereal crops from 3D point clouds. The data acquisition is based on a convenient stereo imaging setup. The approach was validated with different artificial targets and results on the accuracy of the 3D reconstruction, leaf surface modeling and calculated LAD are given. The mean error of the 3D reconstruction was below 1 mm for an inclination angle range between 0° and 75° and the leaf surface could be quantified with an average accuracy of 90%. The concordance correlation coefficient (CCC) of 99.6% (p-value = [Formula: see text]) indicated a high correlation between the reconstructed inclination angle and the identity line. The LADs for bent leaves were reconstructed with a mean error of 0.21° and a standard deviation of 1.55°. As an additional parameter, the insertion angle was reconstructed for the artificial leaf model with an average error < 5°. Finally, the method was tested with images of field-grown cereal crops and Beta functions were approximated from the calculated LADs. The mean CCC between reconstructed LAD and calculated Beta function was 0.66. According to Cohen, this indicates a high correlation. CONCLUSION: This study shows that our image processing pipeline can reconstruct the complex leaf shape of cereal crops from stereo images. The high accuracy of the approach was demonstrated with several validation experiments including artificial leaf targets. The derived leaf models were used to calculate LADs for artificial leaves and naturally grown cereal crops. This helps to better understand the influence of the canopy structure on light absorption and plant performance and allows for a more precise parametrization of photosynthesis models via the derived Beta distributions.

Seaweed Growth Monitoring with a Low-Cost Vision-Based System.

In this paper, we introduce a method for automated seaweed growth monitoring by combining a low-cost RGB and stereo vision camera. While current vision-based seaweed growth monitoring techniques focus on laboratory measurements or above-ground seaweed, we investigate the feasibility of the underwater imaging of a vertical seaweed farm. We use deep learning-based image segmentation (DeeplabV3+) to determine the size of the seaweed in pixels from recorded RGB images. We convert this pixel size to meters squared by using the distance information from the stereo camera. We demonstrate the performance of our monitoring system using measurements in a seaweed farm in the River Scheldt estuary (in The Netherlands). Notwithstanding the poor visibility of the seaweed in the images, we are able to segment the seaweed with an intersection of the union (IoU) of 0.9, and we reach a repeatability of 6% and a precision of the seaweed size of 18%.

Realization of NIR-II 3D whole-body contour and tumor blood vessels imaging in small animals using rotational stereo vision technique.

Significance: Optical imaging in the second near-infrared (NIR-II, 1000 to 1700 nm) region is capable of deep tumor vascular imaging due to low light scattering and low autofluorescence. Non-invasive real-time NIR-II fluorescence imaging is instrumental in monitoring tumor status. Aim: Our aim is to develop an NIR-II fluorescence rotational stereo imaging system for 360-deg three-dimensional (3D) imaging of whole-body blood vessels, tumor vessels, and 3D contour of mice. Approach: Our study combined an NIR-II camera with a 360-deg rotational stereovision technique for tumor vascular imaging and 3D surface contour for mice. Moreover, self-made NIR-II fluorescent polymer dots were applied in high-contrast NIR-II vascular imaging, along with a 3D blood vessel enhancement algorithm for acquiring high-resolution 3D blood vessel images. The system was validated with a custom-made 3D printing phantom and in vivo experiments of 4T1 tumor-bearing mice. Results: The results showed that the NIR-II 3D 360-deg tumor blood vessels and mice contour could be reconstructed with 0.15 mm spatial resolution, 0.3 mm depth resolution, and 5 mm imaging depth in an ex vivo experiment. Conclusions: The pioneering development of an NIR-II 3D 360-deg rotational stereo imaging system was first applied in small animal tumor blood vessel imaging and 3D surface contour imaging, demonstrating its capability of reconstructing tumor blood vessels and mice contour. Therefore, the 3D imaging system can be instrumental in monitoring tumor therapy effects.

Full-field strain mapping of healthy and pathological mouse aortas using stereo digital image correlation.

The murine aorta is a complex, heterogeneous structure that undergoes large and sometimes asymmetrical deformations under loading. For analytical convenience, mechanical behavior is predominantly described using global quantities that fail to capture critical local information essential to elucidating aortopathic processes. Here, in our methodological study, we used stereo digital image correlation (StereoDIC) to measure the strain profiles of speckle-patterned healthy and elastase-infused, pathological mouse aortas submerged in a temperature-controlled liquid medium. Our unique device rotates two 15-degree stereo-angle cameras that gather sequential digital images while simultaneously performing conventional biaxial pressure-diameter and force-length testing. A StereoDIC Variable Ray Origin (VRO) camera system model is employed to correct for high-magnification image refraction through hydrating physiological media. The resultant Green-Lagrange surface strain tensor was quantified at different blood vessel inflation pressures, axial extension ratios, and after aneurysm-initiating elastase exposure. Quantified results capture large, heterogeneous, inflation-related, circumferential strains that are drastically reduced in elastase-infused tissues. Shear strains, however, were very small on the tissue's surface. Spatially averaged StereoDIC-based strains were generally more detailed than those determined using conventional edge detection techniques.

Development of Stereo NIR-II Fluorescence Imaging System for 3D Tumor Vasculature in Small Animals.

Near-infrared-II (NIR-II, 1000-1700 nm) fluorescence imaging boasts high spatial resolution and deep tissue penetration due to low light scattering, reduced photon absorption, and low tissue autofluorescence. NIR-II biological imaging is applied mainly in the noninvasive visualization of blood vessels and tumors in deep tissue. In the study, a stereo NIR-II fluorescence imaging system was developed for acquiring three-dimension (3D) images on tumor vasculature in real-time, on top of the development of fluorescent semiconducting polymer dots (IR-TPE Pdots) with ultra-bright NIR-II fluorescence (1000-1400 nm) and high stability to perform long-term fluorescence imaging. The NIR-II imaging system only consists of one InGaAs camera and a moving stage to simulate left-eye view and right-eye view for the construction of 3D in-depth blood vessel images. The system was validated with blood vessel phantom of tumor-bearing mice and was applied successfully in obtaining 3D blood vessel images with 0.6 mm- and 5 mm-depth resolution and 0.15 mm spatial resolution. The NIR-II stereo vision provides precise 3D information on the tumor microenvironment and blood vessel path.

High Speed Crop and Weed Identification in Lettuce Fields for Precision Weeding.

Precision weeding can significantly reduce or even eliminate the use of herbicides in farming. To achieve high-precision, individual targeting of weeds, high-speed, low-cost plant identification is essential. Our system using the red, green, and near-infrared reflectance, combined with a size differentiation method, is used to identify crops and weeds in lettuce fields. Illumination is provided by LED arrays at 525, 650, and 850 nm, and images are captured in a single-shot using a modified RGB camera. A kinematic stereo method is utilised to compensate for parallax error in images and provide accurate location data of plants. The system was verified in field trials across three lettuce fields at varying growth stages from 0.5 to 10 km/h. In-field results showed weed and crop identification rates of 56% and 69%, respectively. Post-trial processing resulted in average weed and crop identifications of 81% and 88%, respectively.

Simultaneous measurements of three-dimensional trajectories and wingbeat frequencies of birds in the field.

Tracking the movements of birds in three dimensions is integral to a wide range of problems in animal ecology, behaviour and cognition. Multi-camera stereo-imaging has been used to track the three-dimensional (3D) motion of birds in dense flocks, but precise localization of birds remains a challenge due to imaging resolution in the depth direction and optical occlusion. This paper introduces a portable stereo-imaging system with improved accuracy and a simple stereo-matching algorithm that can resolve optical occlusion. This system allows us to decouple body and wing motion, and thus measure not only velocities and accelerations but also wingbeat frequencies along the 3D trajectories of birds. We demonstrate these new methods by analysing six flocking events consisting of 50 to 360 jackdaws (Corvus monedula) and rooks (Corvus frugilegus) as well as 32 jackdaws and 6 rooks flying in isolated pairs or alone. Our method allows us to (i) measure flight speed and wingbeat frequency in different flying modes; (ii) characterize the U-shaped flight performance curve of birds in the wild, showing that wingbeat frequency reaches its minimum at moderate flight speeds; (iii) examine group effects on individual flight performance, showing that birds have a higher wingbeat frequency when flying in a group than when flying alone and when flying in dense regions than when flying in sparse regions; and (iv) provide a potential avenue for automated discrimination of bird species. We argue that the experimental method developed in this paper opens new opportunities for understanding flight kinematics and collective behaviour in natural environments.

3D reconstruction of the spatial distribution of dislocation loops using an automated stereo-imaging approach.

We propose an automated stereoscopic imaging approach for reconstructing the 3D spatial distribution of small dislocation loops (DLs) from 2D TEM micrographs. This method is demonstrated for small DLs in tungsten, formed by low-dose ion-implantation, that appear as circular spots in diffraction contrast TEM images. To extract the 3D position of specific DLs, their 2D position in multiple weak-beam dark-field TEM micrographs, recorded at different tilt angles, is fitted. From this fit the geometric centre and size of each DL in each micrograph can be extracted. To identify each specific DL in all the 2D projections, an automated forward prediction approach is used. A system of linear equations can then be setup, linking the 3D position of each DL to its 2D position in each projection, and solved using least-squares fitting. This approach is initially tested on synthetic data. For low projected loop densities (<20 â€¯×  1015 m-2) only 3 projections are required for perfect recovery of the defect microstructure. More projections are required when the projected number density increases or realistic errors are included. 3D reconstruction of experimental data from the low-dose self-ion implanted tungsten sample reveals a damage microstructure in good agreement with the depth-dependent damage profile predicted by SRIM. A comparison with weighed back-projection shows that the stereo-imaging-approach requires fewer projections, is less sensitive to the angular range spanned, and is more resilient to spurious variations in local contrast. It also allows a more straightforward retrieval of quantitative information such as size and position of each loop.

Three-dimensional scanning transmission electron microscopy of dislocation loops in tungsten.

Scanning transmission electron microscopy (STEM) imaging using diffraction contrast is a powerful technique to assess crystal defects. In this work it is used to assess the spatial distribution of radiation induced defect in tungsten. In effect, its irradiation leads to the formation of nanometric dislocation loops that under certain conditions may form intriguing 3-D rafts. In this study, we have irradiated thin tungsten samples in situ in a TEM with 1.2 MeV W ions to 0.017 dpa at room temperature (RT) and at 700 °C. Besides the Burgers vector analysis, the number density and size of the dislocation loops with their spatial arrangement were quantitatively characterized by stereo imaging in STEM mode. Most of the loops have a Burgers vector ½ a0 〈111〉, with some a0 〈100〉 at room temperature. Loops are located mainly in the simulated damage profile but there is also a significant portion in deeper regions of the sample, indicating that loops in W diffuse easily, even at RT. At 700 °C, loops form elongated rafts that contain dislocation segments having a Burgers vector ½ a0 〈111〉. The rafts are narrow and reside on {111} planes; they are elongated along 〈110〉 directions, which correspond, when combined to the rafts' Burgers vector, to the lines of edge dislocations. Compared to conventional TEM, 3-D analysis in STEM appears thus as a powerful technique for quantitative analyses of defects in tungsten, as it allows reducing the background diffraction contrast and reaching thicker areas of the electron transparent foil, here 0.5 µm of tungsten at 200 kV.

A Low-Rate Video Approach to Hyperspectral Imaging of Dynamic Scenes.

The increased sensitivity of modern hyperspectral line-scanning systems has led to the development of imaging systems that can acquire each line of hyperspectral pixels at very high data rates (in the 200-400 Hz range). These data acquisition rates present an opportunity to acquire full hyperspectral scenes at rapid rates, enabling the use of traditional push-broom imaging systems as low-rate video hyperspectral imaging systems. This paper provides an overview of the design of an integrated system that produces low-rate video hyperspectral image sequences by merging a hyperspectral line scanner, operating in the visible and near infra-red, with a high-speed pan-tilt system and an integrated IMU-GPS that provides system pointing. The integrated unit is operated from atop a telescopic mast, which also allows imaging of the same surface area or objects from multiple view zenith directions, useful for bi-directional reflectance data acquisition and analysis. The telescopic mast platform also enables stereo hyperspectral image acquisition, and therefore, the ability to construct a digital elevation model of the surface. Imaging near the shoreline in a coastal setting, we provide an example of hyperspectral imagery time series acquired during a field experiment in July 2017 with our integrated system, which produced hyperspectral image sequences with 371 spectral bands, spatial dimensions of 1600 × 212, and 16 bits per pixel, every 0.67 s. A second example times series acquired during a rooftop experiment conducted on the Rochester Institute of Technology campus in August 2017 illustrates a second application, moving vehicle imaging, with 371 spectral bands, 16 bit dynamic range, and 1600 × 300 spatial dimensions every second.

FieldSAFE: Dataset for Obstacle Detection in Agriculture.

In this paper, we present a multi-modal dataset for obstacle detection in agriculture. The dataset comprises approximately 2 h of raw sensor data from a tractor-mounted sensor system in a grass mowing scenario in Denmark, October 2016. Sensing modalities include stereo camera, thermal camera, web camera, 360 ∘ camera, LiDAR and radar, while precise localization is available from fused IMU and GNSS. Both static and moving obstacles are present, including humans, mannequin dolls, rocks, barrels, buildings, vehicles and vegetation. All obstacles have ground truth object labels and geographic coordinates.

A high-throughput stereo-imaging system for quantifying rape leaf traits during the seedling stage.

BACKGROUND: The fitness of the rape leaf is closely related to its biomass and photosynthesis. The study of leaf traits is significant for improving rape leaf production and optimizing crop management. Canopy structure and individual leaf traits are the major indicators of quality during the rape seedling stage. Differences in canopy structure reflect the influence of environmental factors such as water, sunlight and nutrient supply. The traits of individual rape leaves traits indicate the growth period of the rape as well as its canopy shape. RESULTS: We established a high-throughput stereo-imaging system for the reconstruction of the three-dimensional canopy structure of rape seedlings from which leaf area and plant height can be extracted. To evaluate the measurement accuracy of leaf area and plant height, 66 rape seedlings were randomly selected for automatic and destructive measurements. Compared with the manual measurements, the mean absolute percentage error of automatic leaf area and plant height measurements was 3.68 and 6.18%, respectively, and the squares of the correlation coefficients (R2) were 0.984 and 0.845, respectively. Compared with the two-dimensional projective imaging method, the leaf area extracted using stereo-imaging was more accurate. In addition, a semi-automatic image analysis pipeline was developed to extract 19 individual leaf shape traits, including 11 scale-invariant traits, 3 inner cavity related traits, and 5 margin-related traits, from the images acquired by the stereo-imaging system. We used these quantified traits to classify rapes according to three different leaf shapes: mosaic-leaf, semi-mosaic-leaf, and round-leaf. Based on testing of 801 seedling rape samples, we found that the leave-one-out cross validation classification accuracy was 94.4, 95.6, and 94.8% for stepwise discriminant analysis, the support vector machine method and the random forest method, respectively. CONCLUSIONS: In this study, a nondestructive and high-throughput stereo-imaging system was developed to quantify canopy three-dimensional structure and individual leaf shape traits with improved accuracy, with implications for rape phenotyping, functional genomics, and breeding.

Variable angle stereo imaging for rapid patient position correction in an in-house real-time position monitoring system.

PURPOSE: To develop and validate a variable angle stereo image based position correction methodology in an X-ray based in-house online position monitoring system. MATERIALS AND METHODS: A stereo imaging module that enables 3D position determination and couch correction of the patient based on images acquired at any arbitrary angle and arbitrary angular separation was developed and incorporated to the in-house SeedTracker real-time position monitoring system. The accuracy of the developed system was studied by imaging an anthropomorphic phantom implanted with radiopaque markers set to known offset positions from its reference position in an Elekta linear accelerator (LA) and associated XVI imaging system. The accuracy of the system was further validated using CBCT data set from 10 prostate SBRT patients. The time gains achieved with the stereo image based position correction was compared with the manual matching of seed positions in Digitally Reconstructed Radiographs (DRRs) and kV images in the Mosaiq record and verify system. RESULTS: Based on phantom and patient CBCT dataset study stereo imaging module implemented in the SeedTracker shown to have an accuracy of 0.1(σ=0.5)mm in detecting the 3D position offset. The time comparison study showed that stereo image based methodology implemented in SeedTracker was a minimum of 80(4)s faster than the manual method implemented in Mosaiq R&V system with a maximum time saving of 146(6)s. CONCLUSION: The variable angle stereo image based position correction method was shown to be accurate and faster than the standard manual DRR-kV image based correction approach, leading to more efficient treatment.

Understanding the ballistic event: methodology and initial observations.

The purpose of the study is to accelerate the development of ceramic materials for armour applications by substantially increasing the information obtained from a high-energy projectile impact event. This has been achieved by modifying an existing test configuration to incorporate a block of ballistic gel, attached to the strike face of a ceramic armour system, to capture fragments generated during the ballistic event such that their final positions are maintained. Three different materials, representative of the major classes of ceramics for armour applications, alumina, silicon carbide, and boron carbide, have been tested using this system. Ring-on-ring biaxial disc testing has also been carried out on the same materials. Qualitative analysis of the fracture surfaces using scanning electron microscopy and surface roughness quantification, via stereo imaging, has shown that the fracture surfaces of biaxial fragments and ballistic fragments recovered from the edges of the tile are indistinguishable. Although the alumina and boron carbide fragments generated from areas closer to the point of impact were also similar, the silicon carbide fragments showed an increase in porosity with respect to the fragments from further away and from biaxial testing. This porosity was found to result from the loss of a boron-rich second phase, which was widespread elsewhere in the material, although the relevance of this to ballistic performance needs further investigation. The technique developed in this work will help facilitate such studies.

4-mm-diameter three-dimensional imaging endoscope with steerable camera for minimally invasive surgery (3-D-MARVEL).

High-resolution three-dimensional (3-D) imaging (stereo imaging) by endoscopes in minimally invasive surgery, especially in space-constrained applications such as brain surgery, is one of the most desired capabilities. Such capability exists at larger than 4-mm overall diameters. We report the development of a stereo imaging endoscope of 4-mm maximum diameter, called Multiangle, Rear-Viewing Endoscopic Tool (MARVEL) that uses a single-lens system with complementary multibandpass filter (CMBF) technology to achieve 3-D imaging. In addition, the system is endowed with the capability to pan from side-to-side over an angle of [Formula: see text], which is another unique aspect of MARVEL for such a class of endoscopes. The design and construction of a single-lens, CMBF aperture camera with integrated illumination to generate 3-D images, and the actuation mechanism built into it is summarized.

A mixed reality approach for stereo-tomographic quantification of lung nodules.

To reduce the radiation dose and the equipment cost associated with lung CT screening, in this paper we propose a mixed reality based nodule measurement method with an active shutter stereo imaging system. Without involving hundreds of projection views and subsequent image reconstruction, we generated two projections of an iteratively placed ellipsoidal volume in the field of view and merging these synthetic projections with two original CT projections. We then demonstrated the feasibility of measuring the position and size of a nodule by observing whether projections of an ellipsoidal volume and the nodule are overlapped from a human observer's visual perception through the active shutter 3D vision glasses. The average errors of measured nodule parameters are less than 1 mm in the simulated experiment with 8 viewers. Hence, it could measure real nodules accurately in the experiments with physically measured projections.

The leaf angle distribution of natural plant populations: assessing the canopy with a novel software tool.

BACKGROUND: Three-dimensional canopies form complex architectures with temporally and spatially changing leaf orientations. Variations in canopy structure are linked to canopy function and they occur within the scope of genetic variability as well as a reaction to environmental factors like light, water and nutrient supply, and stress. An important key measure to characterize these structural properties is the leaf angle distribution, which in turn requires knowledge on the 3-dimensional single leaf surface. Despite a large number of 3-d sensors and methods only a few systems are applicable for fast and routine measurements in plants and natural canopies. A suitable approach is stereo imaging, which combines depth and color information that allows for easy segmentation of green leaf material and the extraction of plant traits, such as leaf angle distribution. RESULTS: We developed a software package, which provides tools for the quantification of leaf surface properties within natural canopies via 3-d reconstruction from stereo images. Our approach includes a semi-automatic selection process of single leaves and different modes of surface characterization via polygon smoothing or surface model fitting. Based on the resulting surface meshes leaf angle statistics are computed on the whole-leaf level or from local derivations. We include a case study to demonstrate the functionality of our software. 48 images of small sugar beet populations (4 varieties) have been analyzed on the base of their leaf angle distribution in order to investigate seasonal, genotypic and fertilization effects on leaf angle distributions. We could show that leaf angle distributions change during the course of the season with all varieties having a comparable development. Additionally, different varieties had different leaf angle orientation that could be separated in principle component analysis. In contrast nitrogen treatment had no effect on leaf angles. CONCLUSIONS: We show that a stereo imaging setup together with the appropriate image processing tools is capable of retrieving the geometric leaf surface properties of plants and canopies. Our software package provides whole-leaf statistics but also a local estimation of leaf angles, which may have great potential to better understand and quantify structural canopy traits for guided breeding and optimized crop management.

Particle sizing measurements in pharmaceutical applications: comparison of in-process methods versus off-line methods.

It has been previously described that when a sample's particle size is determined using different sizing techniques, the results can differ considerably. The purpose of this study was to review several in-process techniques for particle size determination (Spatial Filtering Velocimetry, Focused Beam Reflectance Measurements, Photometric Stereo Imaging, and the Eyecon® technology) and compare them to well-known and widespread off-line reference methods (laser diffraction and sieve analysis). To start with, a theoretical explanation of the working mechanism behind each sizing technique is presented, and a comparison between them is established. Secondly, six batches of granules and pellets (i.e., spherical particles) having different sizes were measured using these techniques. The obtained size distributions and related D10, D50, and D90 values were compared using the laser diffraction wet dispersion method as reference technique. As expected, each technique provided different size distributions with different D values. These dissimilarities were examined and explained considering the measurement principles behind each sizing technique. The particle property measured by each particle size analyzer (particle size or chord length) and how it is measured as well as the way in which size information is derived and calculated from this measured property and how results are presented (e.g., volume or mass distributions) are essential for the interpretation of the particle size data.

Reconstruction of Stereo MR Angiography Optimized to View Position and Distance using MIP

PURPOSE: We studied enhanced method to view the vessels in the brain using Magnetic Resonance Angiography (MRA). Noticing that Maximum Intensity Projection (MIP) image is often used to evaluate the arteries of the neck and brain, we propose a new method for view brain vessels to stereo image in 3D space with more superior and more correct compared with conventional method. MATERIALS AND METHODS: We use 3T Siemens Tim Trio MRI scanner with 4 channel head coil and get a 3D MRA brain data by fixing volunteers head and radiating Phase Contrast pulse sequence. MRA brain data is 3D rotated according to the view angle of each eyes. Optimal view angle (projection angle) is determined by the distance between eye and center of the data. Newly acquired MRA data are projected along with the projection line and display only the highest values. Each left and right view MIP image is integrated through anaglyph imaging method and optimal stereoscopic MIP image is acquired. RESULTS: Result image shows that proposed method let enable to view MIP image at any direction of MRA data that is impossible to the conventional method. Moreover, considering disparity and distance from viewer to center of MRA data at spherical coordinates, we can get more realistic stereo image. In conclusion, we can get optimal stereoscopic images according to the position that viewers want to see and distance between viewer and MRA data. CONCLUSION: Proposed method overcome problems of conventional method that shows only specific projected image (z-axis projection) and give optimal depth information by converting mono MIP image to stereoscopic image considering viewers position. And can display any view of MRA data at spherical coordinates. If the optimization algorithm and parallel processing is applied, it may give useful medical information for diagnosis and treatment planning in real-time.