Alignment Of Rows Research Articles

Feature selection based on the self-calibration of binocular camera extrinsic parameters

The accuracy of feature-based vision algorithms, including the self-calibration of binocular camera extrinsic parameters used in autonomous driving environment perception techniques relies heavily on the quality of the features extracted from the images. This study investigates the influence of the depth distance between objects and the camera, the feature points in different object regions, and the feature points in dynamic object regions on the self-calibration of binocular camera extrinsic parameters. To achieve this, the study first filters out different types of objects in the image through semantic segmentation. Then, it identifies the areas of dynamic objects and extracts the feature points in the static object region for the self-calibration of binocular camera extrinsic parameters. By calculating the baseline error of the binocular camera and the row alignment error of the matching feature points, this study evaluates the influence of feature points in dynamic object regions, feature points in different object regions, and feature points at different distances on the self-calibration algorithm. The experimental results demonstrate that feature points at static objects close to the camera are beneficial for the self-calibration of extrinsic parameters of binocular camera.

Row orientation influences the diurnal cycle of solar-induced chlorophyll fluorescence emission from wheat canopy, as demonstrated by radiative transfer modeling

Although multiple studies have used solar-induced chlorophyll fluorescence (SIF) of the crop canopy to estimate photosynthetic activity, the effect of canopy geometry (row orientation) on diurnal SIF remains uncertain. Using a combination of 3D canopy radiative transfer modeling and spectroscopic observations collected in a winter wheat field, we investigated (i) the relationships between observed SIF and factors including temperature, humidity, absorbed photosynthetically active radiation (APAR), and row orientation; (ii) the temporal pattern and multi-angle distribution of diurnal canopy SIF; and (iii) the mechanisms influencing components of diurnal SIF under the effect of row orientation. The relationship between observed SIF and APAR was relatively strong at the early growth period, but SIF was influenced by various factors (temperature, humidity, and row–sun angle) at the middle of the growth period. To test an asymmetric crop row effect as a potential cause of this skewness, we evaluated the modeled SIF with a 3D northwestward (315°) crop row alignment and other orientations. Each row orientation resulted in a trough-like depression parallel to the row in simulated canopy SIF, which could cause a diurnal asymmetry of canopy SIF, a fraction of fluorescence escape, and a fraction of APAR. View angles, the dimension of canopy objects (1D/3D), inter-row width, and leaf structure parameters impacted the representativeness of these simulations. An increased shade SIF, synchronized with the time when row–sun angles become zero at the incident sunlight being parallel to the crop row, was linked to decreasing canopy SIF emissions and would cause a non-linear SIF–APAR relationship at certain row orientations especially facing diagonally to the south. The concept of row orientation provides a novel viewpoint of diurnal canopy SIF from which to test the effect of row geometry in cropland, and will promote a mechanistic understanding of photosynthesis and canopy light use.

Design and Experiment of an Automatic Row-Oriented Spraying System Based on Machine Vision for Early-Stage Maize Corps

Spraying pesticides using row alignment in the maize seedling stage can effectively improve pesticide utilization and protect the ecological environment. Therefore, this study extracts a guidance line for maize crops using machine vision and develops an automatic row-oriented control system based on a high-clearance sprayer. First, the feature points of crop rows are extracted using a vertical projection method. Second, the candidate crop rows are obtained using a Hough transform, and two auxiliary line extraction methods for crop rows based on the slope feature outlier algorithm are proposed. Then, the guidance line of the crop rows is fitted using a tangent formula. To greatly improve the robustness of the vision algorithm, a Kalman filter is used to estimate and optimize the guidance line to obtain the guidance parameters. Finally, a visual row-oriented spraying platform based on autonomous navigation is built, and the row alignment accuracy and spraying performance are tested. The experimental results showed that, when autonomous navigation is turned on, the average algorithm time consumption of guidance line detection is 42 ms, the optimal recognition accuracy is 93.3%, the average deviation error of simulated crop rows is 3.2 cm and that of field crop rows is 4.36 cm. The test results meet the requirements of an automatic row-oriented control system, and it was found that the accuracy of row alignment decreased with increasing vehicle speed. The innovative spray performance test found that compared with the traditional spray, the inter-row pesticide savings were 20.4% and 11.4% overall, and the application performance was significantly improved.

Developing an image processing pipeline to improve the position accuracy of single UAV images

Unmanned aerial vehicle (UAV) based remote sensing has been extensively used in precision agriculture applications, such as vegetation growth and health monitoring, yield estimation, and irrigation management. Conventional procedures for UAV data collection and processing require collecting highly overlapped images, stitching images to generate an orthomosaic, and using ground control points (GCPs) in the field or UAV onboard real-time-kinematic (RTK) global navigation satellite system (GNSS) data to improve position accuracy. For improving efficiency, a previous study developed a framework to process individual UAV images for mapping cotton emergence. The current study aimed to build a near-real time image processing pipeline to further improve the positioning accuracy of single UAV images. The improved image processing pipeline comprised feature detection and matching, false matches removal, geometric transformation matrix calculation, crop row alignment, image position assignment, and mapping. The developed pipeline was tested for mapping in both cotton and corn fields. Results showed that the position accuracies for measuring the distance between GCPs were 0.32 ± 0.21 m and 0.57 ± 0.28 m in a cotton and a corn field, respectively, when compared to ground truth data collected with an RTK-GNSS. The developed pipeline did not require GCPs in the field or image post-processing steps, such as image mosaicking and feature extraction, which allowed processing in near-real time and may possibly be implemented in real-time using an onboard edge computing system. The pipeline was used to map emergence parameters for cotton and corn fields, including stand count, canopy area, mean days to imaging after emergence, and plant spacing standard deviation. These maps demonstrated the success of the developed methods in providing a low-cost near real-time tool (8.6 and 3.6 s/image for the cotton and corn fields, respectively) for mapping emergence parameters at field-scale for use in both research and agricultural production.

Development and Testing of Automatic Row Alignment System for Corn Harvesters

Corn harvester row alignment is a critical factor to improve harvesting quality and reduce cob drop loss. In this paper, a corn harvester automatic row alignment system is designed with a self-propelled corn combine harvester, incorporating a front-end touch row alignment mechanism of the cutting table and a harvester steering control system. Corn stalk lateral deviation from the reference row during harvesting is detected by a front-end touch-row alignment mechanism that serves as an input to the automatic alignment system. The harvester steering control system consists of Hirschmann PLC controller, electric steering wheel, steering wheel deflection angle detection device, display module and mode selection module, etc. The adaptive fuzzy PID control algorithm is used to determine the desired turning angle of the harvester steering wheel by combining with the harvester kinematic model, and the model is simulated and analyzed by Matlab/Simulink software. The automatic row alignment system was mounted on a 4LZ-8 self-propelled corn harvester for field tests, and the test results showed that the average percentage of deviation of corn stalks from the center of the row alignment cutting path within ±15 cm during the automatic row alignment process was 95.4% at harvester speeds ranging from 0 to 4.6 km/h, which could meet the requirements of the corn harvester for row alignment harvesting. The test results meet the requirements of the corn harvester for row alignment and serve as a benchmark for the research on automatic row alignment of corn harvesters.

High Throughput Image Analytics Using Hough Transformation for Wheat Phenotyping

HighlightsRGB-based vegetation and leaf area indexes using a smartphone camera.Geo-rectification of skewed images via row detection using Hough Transformation.Open-source software to automate the image stitching and plot-level phenotypic metrics extraction. Abstract. An agricultural field is not always accessible for plant phenotyping with existing mobile platforms due to the limited space and regulated aviation area. Smartphone-triggered ground images were collected on a wheat field that has a limited access to monitor growth conditions of four wheat varieties: Shinyoung (SY), Joseong (JS), Taewoo (TW), and Cheongwoo (CW). For field mapping during the growing season, six sets of the raw images were acquired by a smartphone in an oblique view angle and processed to transform into nadir view images. Algorithms were developed to process the raw tile images for geometric rectification via row detection using Hough Transformation. Stitching software was developed to automate the high throughput image analytics of the skewed tile images into a stitched field image through deskewing, row alignment, overlap trimming, and resizing. Plot-level metrics were extracted to analyze plant growth of the wheat varieties using a gridding method for vegetation and leaf area indexes. The processed images resulted in the successful transformation and consistency of algorithms on image alignment and stitching. Plot-level analysis indicated that SY variety performed superior to the other varieties in both vegetation and leaf area indexes and was significantly different in the canopy coverage from the least performed TW variety. The image analytic methods developed in the study offer a flexible solution to stitch and align tile images by a hand-held camera in both oblique and nadir view via user-friendly interface software for high through plant phenotyping and can be adapted to other stationary or mobile imaging platforms in greenhouse and fields. Keywords: Calibration, Image processing, Phenotyping, Python, Software, Stitching.

Minimum‐time row transition control of a vision‐guided agricultural robot

AbstractThis paper presents a vision‐based, subspace optimal controller aiming to improve the row transition performance of an agricultural robot in a strawberry field. The contribution of this paper is twofold. First, only RGB cameras, instead of complicated sensor suites, are used for cross‐bed navigation and row alignment. Second, a real‐time adaptive dynamic programming‐based algorithm is designed for an optimal row transition. The conditions for row alignment are derived in an augmented pixel coordinate frame. Based on these conditions, a simple motion rule is utilized to reduce the search space dimension so that the proposed algorithm can be implemented in real‐time. Additionally, the inverse‐dynamics policy of the algorithm is updated using vision feedback at each control step to adapt to uncertainties. The proposed controller is tested in both simulations and field experiments. In a simulation comparison, the minimum‐time solution achieved using the proposed algorithm is 44.7 s, which is very close to that of a benchmark algorithm (44.4 s). However, the CPU time required by the proposed algorithm is only 4.3% of time needed by the benchmark algorithm. Twenty field experiments using the presented design were all successful in row transition, with a mean final alignment error of 0.5 cm.

Traumatic Nondissociative Carpal Instability: A Case Series

We report 8 cases of acute or subacute unilateral nondissociative carpal instability (CIND) in the context of nondisplaced scaphoid fractures. Eight patients from 3 centers developed abnormal volar intercalated segment instability (VISI) or dorsal intercalated segment instability (DISI) following the diagnosis of a nondisplaced scaphoid fracture. An operative inspection in each patient confirmed intact scapholunate and lunotriquetral interosseous ligaments. We outline the demographic characteristics of our patient cohort, radiologic and operative findings of CIND-DISI and CIND-VISI, and the outcomes of acute and delayed treatment. Two patients were diagnosed with CIND-DISI and 6 with CIND-VISI associated with ipsilateral nondisplaced scaphoid fractures. The average time from injury to diagnosis of CIND was 11 weeks, and the mean clinical and radiographic follow-up was 18 months. Rapid healing of the scaphoid fractures was achieved in all patients (4 open reduction internal fixation, 4 cast). All patients underwent surgery to improve proximal carpal row alignment: in 3 of the 4 patients who were diagnosed and treated surgically within 12 weeks of injury, the radiolunate angle (RLA) was successfully restored. A contracture release and ligament repair or reconstruction with tendon graft 12 or more weeks following injury was unsuccessful in restoring proximal row alignment in all 4 patients. Two patients in the delayed treatment group required secondary surgery for partial fusion. Based on the arthroscopic, imaging, and operative findings, we propose that the ligamentous restraints to CIND-VISI are dorsal at the radiocarpal joint and volar at the midcarpal joint. Conversely, the ligamentous restraints to CIND-DISI are dorsal at the midcarpal joint and volar at both the radiocarpal and midcarpal joints. In our series, a delayed diagnosis and late reconstructive surgery were associated with no improvement in RLA. We recommend early recognition of traumatic CIND and prompt treatment of injured ligaments prior to the development of a fixed deformity. Therapeutic V.

Statistical study of the impact of climate warming on productivity

The global warming had a significant impact on agriculture in Russia over the past decades, what causes an urgent need for scientific analysis of warming impact on agriculture production and its efficiency. On the example of published data concerning weather conditions of grain crops cultivation in Tambov Region, methodical questions of statistical estimation of their influence on the level and variation of productivity are considered. Within the framework of metrological support, techniques are offered for constructing the qualitatively homogeneous time series of productivity and climate factors, alignment of rows and assessment of the degree of influence of air temperature and precipitation during the vegetation period on the productivity based on the correlation analysis of deviations of characteristics from the aligned series. It is recommended to use the offered approaches as the metrological support for the analysis of dynamics of productivity in all subjects of the Russian Federation, and differences in the level of productivity between them.

Design Implementation With Noninteger Multiple-Height Cells for Improved Design Quality in Advanced Nodes

Standard-cell libraries can be developed with different cell heights (e.g., in FinFET technology, corresponding to different numbers of fins). Larger cell heights provide higher drive strengths, but at the cost of larger area and power consumption as well as pin capacitance. Cells with smaller heights are relatively smaller in area, but have weaker drive strengths and are more likely to suffer from routing congestion and pin accessibility issues. Existing design methodologies and tool flows are able to mix cells with different heights at the block level (i.e., each block contains cells with heights being integer multiples of a particular “single row” cell height). To our knowledge, no design methodology in the literature or in production mixes cells with different, noninteger multiple heights in a fine-grained manner. In this paper, we propose a novel physical design optimization flow to implement design blocks with mixed cell heights in a fine-grained manner. Our optimization resolves the “chicken-and-egg” loop between floorplan site definition and the optimized choices of cell heights after placement with full comprehension of the constraints and costs of mixing cells of different heights (e.g., the “breaker cell” area overheads of row alignment between sub-blocks of 8 T and 12 T cell rows), our optimization achieves up to over 30% area and power reductions versus 12 T-only implementation while maintaining the same performance, and up to over 10% performance improvement along with power and area reductions versus 8 T-only implementation.

Error in Table Row Alignment and No. of Participants

Error in Table Row Alignment and No. of Participants

Large eddy simulation studies of the effects of alignment and wind farm length

Large eddy simulations of wind farms are performed to study the effects of wind turbine row alignment with respect to the incoming flow direction. Various wind farms with fixed stream-wise spacing (7.85 rotor diameters) and varying lateral displacements and span-wise turbine spacings are considered, for a fixed inflow direction. Simulations show that, contrary to common belief, a perfectly staggered (checker-board) configuration does not necessarily give the highest average power output. Instead, the highest mean wind farm power output is found to depend on several factors, the most important one being the alignment that leads to minimization of wake effects from turbines in several upstream rows. This alignment typically occurs at significantly smaller angles than those corresponding to perfect staggering. The observed trends have implications for wind farm designs, especially in sites with a well-defined prevailing wind direction.

Cellular structure and chemical composition of cork from the Chinese cork oak (Quercus variabilis)

Quercus variabilis Blume, the Chinese cork oak, is an oak species with a thick cork outer bark. The cork is exploited at a limited scale in China and considered of lower quality than the commercial cork from Quercus suber. We studied an industrial cork granulate feedstock of Q. variabilis in relation to cellular structure and chemical composition and compared it to Q. suber cork under a material’s perspective. The cork of Q.variabilis has 1.1 % ash, 9.6 % extractives, 34.8 % suberin and 19.1 % lignin. The monosaccharide composition with shows a predominance of hemicelluloses: glucose 42.8 % of total neutral sugars, xylose 27.5 %, arabinose 15.4 %, galactose 9.0 %, mannose 4.0 %, rhamnose 1.2 %. The FT-IR spectrum shows the indicative peaks of suberin. The composition is overall similar to that of Q. suber cork. Q. variabilis cork has the typical cellular characteristics of bark cork tissues with a regular and radially aligned structure of cells without intercellular voids. Solid volume fraction was estimated at approximately 16 %. Compared with Q. suber, the Q. variabilis cork cells are smaller, the cell wall undulation and the overall row alignment less homogeneous, the cell surface is irregular and the solid volume proportion higher. The characteristics of Q. variabilis cork support its use as a cellular material for sealing, insulation and energy absorption, but the overall quality is lower than that of Q. suber cork. The negative impact of the higher density and structural lower uniformity at tissue and cell level should be evaluated for processing and product performance.

Identification of live hair cells in rat cochlear sections in culture with FM1-43 fluorescent dye

Cochlear hair cells are presumed to live in culture for many days, yet they are difficult to identify in cultured tissues. We stained hair cells in cochlear sections with FM1-43 and cultured them in collagen matrix. Three rows of outer hair cells and a single row of inner ones were distinguished by staining with FM1-43. Fixation of the sections with paraformaldehyde caused loss of the FM1-43 fluorescence, indicating that FM1-43 stained only live hair cells. In sections cultured for 48 h, almost all hair cells were still positive with FM1-43. Culture with gentamycin caused loss of FM1-43-positive cells. In serum-free, long-term cultures (15 days) performed without antibiotics or neurotrophins, the row alignment of FM1-43-positive hair cells was still maintained. Membranous labyrinth-like vacuoles enveloping hair cells were formed in the collagen matrix. Accordingly, FM1-43 is an efficient marker for identifying live hair cells in cultured tissues. Moreover, cochlear hair cells are revealed to live for weeks in serum-free culture without exogenous neurotrophins.

On access and alignment of data in a parallel processor

We describe a complete solution to the problem of parallel, conflict-free access and alignment of rows, columns, forward and backward diagonals of an N× N matrix in a parallel processor with N processing elements sharing N memory modules via an interconnection network, where N=2 n with any n > 1.

Access and Alignment of Data in an Array Processor

This paper discusses the design of a primary memory system for an array processor which allows parallel, conflict-free access to various slices of data (e.g., rows, columns, diagonals, etc.), and subsequent alignment of these data for processing. Memory access requirements for an array processor are discussed in general terms and a set of common requirements are defined. The ability to meet these requirements is shown to depend on the number of independent memory units and on the mapping of the data in these memories. Next, the need to align these data for processing is demonstrated and various alignment requirements are defined. Hardware which can perform this alignment function is discussed, e.g., permutation, indexing, switching or sorting networks, and a network (the omega network) based on Stone's shuffle-exchange operation [1] is presented. Construction of this network is described and many of its useful properties are proven. Finally, as an example of these ideas, an array processor is shown which allows conflict-free access and alignment of rows, columns, diagonals, backward diagonals, and square blocks in row or column major order, as well as certain other special operations.