Number Of Control Points Research Articles

COMPARISON OF PIXEL AND OBJECT BASED CLASSIFICATION METHODS ON RAPIDEYE SATELLITE IMAGE

The aim of this study is to evaluate the classification performances of land use/land cover (LULC) classification methods by comparing the results of pixel and object-based classification approaches on RapidEye satellite image. Pixel-based classification was carried out in ERDAS Imagine 10.4 using the Maximum Likelihood-supervised approach, whilst object-based classification was performed in e-Cognition Developer 64 using the nearest neighbour-supervised classification method. A LULC map of eight classes was created in both methods. While the accuracy for thematic LULC classes varied in both methods, the overall accuracy and kappa values of LULC maps for pixel and object-based classification methods were 58.39%-0.45 and 89.58%-0.86, respectively. Accuracy assessments and comparative results showed that object-based classification gives better results for thematic LULC classes as well as the overall accuracy of LULC maps. Even though pixel-based classification method was good at mapping many thematic classes, there were misclassifications between natural/semi-natural LULC classes. These results can be attributed to parameters set by users, such as the number of control points, etc. However, the capacity of object-based classification method to include auxiliary data (e.g. DEM, NDVI) increases the accuracy of LULC maps with high-resolution satellites.

Radiation Pressure Field Reconstruction for Ultrasound Midair Haptics by Greedy Algorithm With Brute-Force Search.

Non-contact tactile presentation using ultrasound phased arrays is becoming a powerful method for providing haptic feedback on bare skin without restricting the user's movement. In such ultrasonic mid-air haptics, it is often necessary to generate multiple ultrasonic foci simultaneously, which requires solving the inverse problem of amplitudes and phases of the transducers in a phased array. Conventionally, matrix calculation methods have been used to solve this inverse problem. However, a matrix calculation requires a non-negligible amount of time when the number of control points and the number of transducers in the array are large. In this article, we propose a simple method based on a greedy algorithm and brute-force search to solve the field reconstruction problem. The proposed method directly optimizes the desired field without matrix calculation or target field phase optimization. The empirical results indicate that the proposed method can reproduce the target sound with an accuracy of more than 80%.

Model and structure of the network internet of things for monitoring milk quality

Belarusian state University of Informatics and Radioelectronics, Minsk, Republic of Belarus The quality of milk is evaluated by a number of control points, which include a number of indicators, such as fat content, protein, lactose, density, etc. It is proposed to use the Internet of things (IoT) technology to control the quality of milk from distributed dairy farms. A multi-agent model of IoT network and the structure of such an IoT network for monitoring the quality of milk from different farms is presented. The model is represented by a variety of agents: milk analyzers, converter, storage of quality indicators, their processing, decision-making, monitoring of milk quality indicators. The structure of the IoT network includes milk analyzers, gateways-converters, a cloud platform, and mobile devices. The cloud platform rents a server that hosts knowledge and data bases, special software (solver) for processing and making decisions on milk quality, and a farm website. The database of the cloud structure server stores milk quality characteristics, and the knowledge base stores the rules for processing them. The solver outputs deviations from the current milk quality indicators from the standards. The site is used for communication of specialists in milk quality control. Monitoring of milk quality characteristics is implemented from mobile devices of specialists with access to the site components. The 4th generation LTE network using NB-IoT technology was chosen as the network for transmitting information from dairy farms to the cloud. The review of milk analyzers of both domestic and foreign companies is carried out. A gateway solution for querying milk analyzers and transmitting parameters to the cloud infrastructure is presented. Popular cloud platforms for building a network of IoT are presented.

Global smoothing for five-axis linear paths based on an adaptive NURBS interpolation algorithm

The five-axis tool path generated by CAM software usually consists of a series of linear paths. The tangent direction at the corner of the adjacent line segment will suddenly change, and the curvature is also discontinuous, which will cause vibration and shock during the machining process. Thus, a global corner smoothing algorithm based on cubic NURBS interpolation is proposed to smooth the linear paths in this paper, so as to achieve G2 continuous for five-axis linear paths. The algorithm proposed does not require matrix operations to solve the control points, and it can also reduce the number of control points while satisfying the interpolation error. The algorithm is then used to generate smooth NURBS path for ceramic core burrs and blockage repair. The simulation and experiment show that the algorithm proposed can satisfy the error constraints, reduce the vibration of the motion axis, and improve the surface quality of laser cutting.

Nonuniform Rational Basis Spline Interpolation for Off-Axis Aspheric Mirror Grinding Based on Wheel Path Planning

Large-diameter aspheric mirrors made of hard and brittle materials suffer from low efficiency in the grinding stage, making them difficult to process. In this study, a nonuniform rational basis spline (NURBS) interpolation method is proposed and developed based on the grinding wheel path planning. The characteristic parameters of NURBS machining program are calculated to ensure the accuracy of curve interpolation path planning, and a series of control points are selected according to the normal vector points of the grinding wheel path. The control points were determined by the distance between the aspheric tangent and the next type value point at a fixed distance d. We then established a mathematical model for the knot point and simulated the relationship between the knot point and d. This indicated that d must be optimized according to the number of points to reduce the number of control points. According to this established model, a comparison experiment was conducted using an off-axis aspheric mirror, with a 280 mm diameter. Straight line and NURBS grinding were compared, and the NURBS interpolation method was shown to effectively improve grinding accuracy and efficiency by about 30%.

The Impact of Photo Overlap, the Number of Control Points and the Method of Camera Calibration on the Accuracy of 3D Model Reconstruction

This research attempted to determine the optimal photo overlap, number of control points and method of camera calibration for a photogrammetric 3D model reconstruction of an object of cultural heritage value. Terrestrial images of the object were taken with a hand‑held digital camera and processed in the ContextCapture software using the Structure‑from‑Motion (SfM) algorithm. A total station was used to measure ground control points (GCPs) and check points. Here, the research workflow, methodology, and various analyses concerning different configurations of the aforementioned factors are described. An attempt to assess the parameters which should be implemented in order to provide a high degree of accuracy of the model and reduce time‑consumption both during fieldwork and data processing was taken. The manuscript discusses the results of the analyses and compares them with other studies presented by different authors and indicates further potential directions of studies within this scope. Based on the authors’ experience with this research, some general conclusions and remarks concerning the planning of photo acquisition from the terrestrial level for the purpose of 3D model reconstruction were formulated.

Two-point calibration method for a zoom camera with an approximate focal-invariant radial distortion model.

A zoom camera can change its focal length and track moving objects with an adjustable resolution. To extract precise geometric information for the tracked objects, a zoom camera requires an accurate calibration method. High-precision camera calibration methods, however, usually require a number of control points that are not guaranteed in some practical situations. Most zoom cameras suffer radial distortion. Athough a traditional method can recover an undistorted image with known intrinsic parameters, it fails to work for a zoom camera with an unknown focal length. Motivated by these problems, we propose a two-point calibration method (TPCM). In this scheme, we first propose an approximate focal-invariant radial distortion (AFRD) model. With the AFRD model, an RGB image can be undistorted with an unknown focal length. After that, the TPCM method is presented to estimate the focal length and rotation matrix with only two control points for one image. Synthetic experiments demonstrate that the AFRD model is efficient. In the real data experiment, the mean reprojection error of the TPCM method is less than one pixel, which is smaller than current state-of-the-art methods, and we believe meets the demand for high-precision calibration.

Real-time smoothing of G01 commands for five-axis machining by constructing an entire spline with the bounded smoothing error

G01 commands generated by computer-aided manufacturing (CAM) software need to be smoothed to eliminate the tangential discontinuities at corners. Although the smoothing methods for five-axis tool paths have been widely studied, it is still challenging to realize the high machining efficiency of short, dense G01 commands with real-time processing. This article proposes a real-time five-axis tool path smoothing algorithm for short G01 commands. The uniform smoothing of adjacent two corners with cubic uniform B-spline is developed. Through connecting the pieces of splines, all the G01 commands are smoothed by an entire B-spline. Therefore, the curvature increment induced by the avoidance of the intersection of adjacent micro-splines is prevented, and thus, high allowable feedrate and high machining efficiency can be achieved. Especially, the smoothing errors are theoretically proved to be constrained by using the convex polyhedron method. At the same time, the required number of control points is greatly reduced by sharing the control points with the adjacent G01 commands. Simulation and experimental results demonstrate that the proposed method can significantly reduce the machining time by more than 26% for short linear trajectories.

Improving Co-Registration for Sentinel-1 SAR and Sentinel-2 Optical Images

Co-registering the Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 optical data of the European Space Agency (ESA) is of great importance for many remote sensing applications. However, we find that there are evident misregistration shifts between the Sentinel-1 SAR and Sentinel-2 optical images that are directly downloaded from the official website. To address that, this paper presents a fast and effective registration method for the two types of images. In the proposed method, a block-based scheme is first designed to extract evenly distributed interest points. Then, the correspondences are detected by using the similarity of structural features between the SAR and optical images, where the three-dimensional (3D) phase correlation (PC) is used as the similarity measure for accelerating image matching. Lastly, the obtained correspondences are employed to measure the misregistration shifts between the images. Moreover, to eliminate the misregistration, we use some representative geometric transformation models such as polynomial models, projective models, and rational function models for the co-registration of the two types of images, and we compare and analyze their registration accuracy under different numbers of control points and different terrains. Six pairs of the Sentinel-1 SAR L1 and Sentinel-2 optical L1C images covering three different terrains are tested in our experiments. Experimental results show that the proposed method can achieve precise correspondences between the images, and the third-order polynomial achieves the most satisfactory registration results. Its registration accuracy of the flat areas is less than 1.0 10 m pixel, that of the hilly areas is about 1.5 10 m pixels, and that of the mountainous areas is between 1.7 and 2.3 10 m pixels, which significantly improves the co-registration accuracy of the Sentinel-1 SAR and Sentinel-2 optical images.

Automated calculation of the profile of a disk cutter for the manufacture of helical grooves

The calculation of the profile of disk cutters, excluding undercutting for any complex profile of the helical groove, is proposed. The feature of the method is in the fact that the profile is specified by a small number of control points, which, using interpolation, is increased by tens or hundreds of times. The rational profile of the cutter is investigated depending on its three setting parameters. A numerical experiment was carried out for the profile of the cutter with the optimization of the setting parameters. Keywords: disk cutter, profile, helical groove, computer-aided design, calculation zov20@mail.ru

Efficient radial basis function mesh deformation methods for aircraft icing

This paper presents an approach to update the moving ice boundary resulting from aircraft icing simulations using radial basis function mesh deformation techniques. State-of-the-art surface and volume point reduction schemes are used to reduce the computational cost of the mesh deformation. The data reduction schemes which are utilised include multi-level greedy surface point selection and volume point reduction. The multi-level greedy surface point selection reduces the number of control points to increase the efficiency of the interpolation operation. While the volume point reduction improves the computational cost of the volume mesh update operation which is important for large data sets. The paper assesses the capabilities of radial basis function mesh deformation for both two and three-dimensional problems. Furthermore, the effectiveness of the deformation technique is assessed for both local, non-smooth deformations and global, smooth deformations. The convergence history of the multi-level greedy point selection is assessed in terms of number of control points and computational cost. The location of the selected control points near the ice accretion illustrates the efficacy of the method for localised deformations. The results show that the radial basis function mesh deformation performs well for both the two and three-dimensional problems. The data-reduction schemes utilised in this work represent a significant improvement to standard radial basis function mesh deformation for aircraft icing problems comprising of large data-sets typical of three-dimensional problems.

Seismic horizon extraction with dynamic programming

Horizon picking is a fundamental and crucial step for seismic interpretation, but it remains a time-consuming task. Although various automatic methods have been developed to extract horizons in seismic images, most of them may fail to pick horizons across discontinuities such as faults and noise. To obtain more accurate horizons, we have developed a dynamic programming algorithm to efficiently refine manually or automatically extracted horizons so that they can more accurately track reflectors across discontinuities, follow consistent phases, and reveal more geologic details. In this method, we first compute an initial horizon using an automatic method, manual picking, or interpolation with several control points. The initial horizon may not be accurate, and it only needs to follow the general trend of the target horizon. Then, we extract a subvolume of amplitudes centered at the initial horizon and meanwhile flatten the subvolume according to the initial horizon. Finally, we use the dynamic programming to efficiently pick the globally optimal path that passes through the global maximum or minimum amplitudes in the subvolume. As a result, we are able to refine the initial horizon to a more accurate horizon that follows consistent amplitude peaks, troughs, or zero crossings. Because our method does not strictly depend on the initial horizon, we prefer to directly interpolate an initial horizon from a limited number of control points, which is computationally more efficient than automatically or manually picking an initial horizon. In addition, our method is convenient to interactively implement to update the horizon while editing or moving the control points. More importantly, these control points are not required to be exactly placed on the target horizon, which makes the human interaction highly convenient and efficient. We develop our method with multiple 2D and 3D field examples that are complicated by noise, faults, and salt bodies.

Influence of the Number and Spatial Distribution of Ground Control Points in the Accuracy of UAV-SfM DEMs: An Approach Based on Generalized Additive Models

The accuracy of digital elevation models (DEMs) obtained with unmanned aerial vehicle (UAV)-SfM photogrammetry depends on the quality, number, and distribution of ground control points (GCPs). In this work, generalized additive models (GAMs) are used to analyze the relationship between both, the root mean square error (RMSEz) and the mean absolute error (MAEz) in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Z$ </tex-math></inline-formula> coordinate, in a group of checkpoints and in a set of covariates related to the number and spatial distribution of the GCPs. Beyond the exploratory data analysis frequently used to analyze the effect of GCPs on UAV-generated DEM accuracy, our approach also allows the determination of the shape of the association between the response (RMSEz and MAEz) and the predictor variables describing GCP number and distribution when they are all combined in a single model. Among the different predictor variables studied, the number of GCPs has, by far, the greatest influence on vertical accuracy. Other variables such as mean distance between control points (CPs) or distance of checkpoints from their nearest CP are statistically significant but contribute much less to explaining RMSEz and MAEz. The analysis was performed by constructing 4600 DEMs from different GCP combinations, divided into four sampling methods: random, stratified, spatially balanced, and contour (edge) distribution. As expected, the random method produced the poorest results, while the stratified and contour distribution methods produced the smallest range and dispersion of errors.

Optimization of RFM Problem Using Linearly Programed ℓ₁-Regularization

Due to the existence of a large number of highly correlated parameters in the rational function model (RFM), known as rational polynomial coefficients (RPCs), RFM suffers from both ill-posedness and overparameterization problems. To tackle these problems, recently, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> -regularized least-squares, in which <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula> -norm of residuals and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> -norm of RPCs are minimized, has been introduced. Nonetheless, RFM still suffers from these two phenomena, especially in the presence of a limited number of ground control points (GCPs). This study proposes a new parameter-free linear framework for RFM optimization. In this framework, called linearly programed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> -regularized RFM framework (LPRFM), the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> -norms of RPCs and residuals are simultaneously minimized through a linear objective function. To solve LPRFM as a linear optimization problem, the commonly used dual-simplex method is applied. LPRFM can be implemented for both RPC estimation and correction. Our experimental results indicated the superiority of the LPRFM against well-known competing methods in both estimation and correction of RPCs. The results showed that, in the estimation of RPCs, the proposed framework has led to accurate and robust results with only five GCPs. Moreover, accurate coordinates were obtained after correcting vendor-provided RPCs with only one GCP.

Boundary Element Modeling for Simulation and Optimization of Three-Temperature Anisotropic Micropolar Magneto-thermoviscoelastic Problems in Porous Smart Structures Using NURBS and Genetic Algorithm

The main objective of the present paper is to propose a new boundary element modeling technique for simulation and optimization of three-temperature micropolar magneto-thermoviscoelastic problems in anisotropic porous smart structures, where we implemented the genetic algorithm (GA), as a method of optimization based on the free form deformation (FFD) methodology to improve the performance of our proposed technique. Two numerical examples are presented herein, in order to prove that the proposed technique is able to optimize the shape of the domains with minimum computational effort. A nonuniform rational B-spline curve (NURBS) has been introduced to define the optimum boundary where it decreases the number of control points and offers a new degree of versatility in the design of various different shapes. The profiles of the items considered shall be represented by the FFD methodology. The location vectors of the FFD control points are known to be the genes, and then the chromosomes for the profiles are determined by the gene sequence. The population is made up of several chromosomes individuals, where the fitness functions of individuals are assessed using BEM. The numerical results are depicted graphical forms to show the effects of viscosity and magnetic fields on the three temperatures, displacement components, microrotation components, pore pressure, electric potential, and thermal stress components. The validity, accuracy, and computational efficiency of the proposed BEM technique were demonstrated by comparing our BEM-obtained results with the corresponding results of normal mode analysis method (NMAM), finite difference method (FDM), and finite element method (FEM).

Concentrated Slip and Low Rupture Velocity for the May 20, 2012, MW 5.8, Po Plain (Northern Italy) Earthquake Revealed From the Analysis of Source Time Functions

AbstractWe analyse the rupture properties of the May 20, 2012, MW 5.8, Po Plain (Northern Italy) earthquake by using two different modeling procedures based on the source time functions: a forward modeling and a global inversion Bayesian method. While the forward modeling allows to retrieve general information on the source characteristics, the global inversion allows to explore a substantially larger number of possible solutions, with more parameters, providing a quantitative estimate of the misfit. We invert for the spatial slip distribution and for the rupture velocity on a planar fault model. The unknown slip is given at the nodes of the subfaults (control points) and then given at the elementary subfaults through a bilinear interpolation. The number of control points is progressively increased to move from a high‐ to low‐wavelength description of final slip on the fault plane. The optimal model parameter set is chosen according to the Akaike Information Criterion. The uncertainty on the slip distribution and rupture velocity has been estimated by a statistical analysis of the model ensemble and, in particular, through the weighted mean model and the standard deviation. We find that the most earthquake slip occurred in the regions located northeast and southwest of the hypocenter, consistent with the forward modeling. Moreover, we find a low rupture propagation velocity (0.4 compressional Mach number) similarly to what has been observed for the close 29 May, MW 5.6, and radiation efficiency suggesting that half of the strain energy was used to create new fracture.

Effect of the number of control points on the plan quality of intensity-modulated radiotherapy for nasopharyngeal carcinoma

ABSTRACT This study aimed to investigate the effect of the number of control points (CPs) on the plan quality, plan delivery efficiency, and gamma passing rate (GPR) of intensity-modulated radiotherapy (IMRT) for nasopharyngeal carcinoma (NPC). Twenty patients with NPC were selected. With all other optimization conditions unchanged, only the number of CPs in each field was changed and optimized to formulate four groups of IMRT plans (CP10, CP15, CP20, and CP25) for each case. An IMRT factor (IF) was used to evaluate the plan complexity, and the plan quality index (PQI) was employed to measure the plan quality. The MatriXX was used to measure each plan, and the plan delivery time (PDT) was recorded. The CP20 group had the lowest PQI (20.2%), while the CP10 group had the highest PQI (51.4%). The monitor unit (MU) values and PDTs gradually increased as the number of control points increased, while the MUs/segment significantly decreased. A negative correlation was observed between GPR and IF at the three commonly used criteria (R2 = 0.39, 0.39, and 0.41, respectively). Considering the IMRT plan quality and the efficiency and accuracy of plan delivery, 20 CPs per field should be used in the IMRT planning for NPC.

The algorithm for determining an optimal system of routes for the mine ventilation and safety engineering masters for the purpose of monitoring aerodynamic parameters of the ventilation network in mines

Route control of the mine aerogasdynamic parameters is organized in such a way that the obtained information can supplement the information of the unified telecommunication system for dispatch control and automated control of mining machines and technological complexes or another similar system installed in the mine making this information more exact, promptly if possible, without duplications. The route control system is formed from the practical considerations with taking into account the data of the stationary system. Due to the joint functioning of stationary and route control systems with accounting the previous changes of aerogasdynamic parameters, it will be possible to build a predicted trajectory of such a change, which will improve reliability, optimize the control structure and more exactly predict the occurrence of emergency situations. In this article, the authors formulate the main definitions and properties of the route control system and the problem of creating the routes covered the entire mine ventilation network with a given number of control points. An algorithm for constructing a route control system is characterized with taking into account economic and ergonomic conditions, time factor and safety requirements. To solve this problem, it is proposed to use the method of sequential improvement of admissible plan. The essence of the method is that, having received a certain solution (an admissible plan) as an initial approximation, the measures are proposed for improving it till further improvement becomes impossible. The "improvement" here means more complete satisfaction of the proposed criterion for minimizing total time of the master travelling for executing his work on the route. Improvement of the admissible plan is carried out by the Monte Carlo method. The possibility of duplication of data obtained from an automated system and by route control is analyzed, and a reduction of the basis of control stations is grounded. The set of routes for monitoring parameters of the ventilation network elements by mine experts chosen in this way will reduce the risk of obtaining incomplete information about its aerogasdynamic state, and cross-monitoring of measurements within the transversal of the bases of two components of the control system will improve reliability and accuracy of the monitoring.

Controle estatístico de processo e padrão de exatidão cartográfico aplicado a aerolevantamento

Remotely piloted aircraft (RPA) are established in the market as a powerful tool for acquiring aerial images and facilitating mapping for various purposes. The aim of this study was to evaluate the quality of processes originating from the generation of georeferenced digital products employing a differing number of ground control points (GCP), using Statistical Process Control (SPC) and Mapping Accuracy Standards (MAS) in an orthomosaic produced with images from an RPA. A multirotor RPA was used to acquire aerial images over an area of 2 hectares. An orthomosaic was later generated using the PhotoScan software, and georeferenced with eight, five and three GCP (ground control points). Positioning errors were submitted to SPC to evaluate the quality of each process, and the orthomosaics were qualified by MAS. The results are promising, in view of the positioning errors of less than 0.1 m in the generated orthomosaics, which are classified as Mapping Accuracy Standards class ‘A’. Statistical Process Control showed acceptable levels of error, indicating the high accuracy of surveys of this nature. The precision obtained when mapping shows that aerial images obtained by means of RPA can be used in topographic surveys as long as error standards and process control are observed, attesting to the quality of the results.

UAV PHOTOGRAMMETRY-BASED FOR OPEN PIT COAL MINE LARGE SCALE MAPPING, CASE STUDIES IN CAM PHA CITY, VIETNAM

The use of lightweight Unmanned Aerial Vehicle with the aerial photogrammetry approach to construct the Digital Surface Model (DSM) has been effectively applied for various types of topography. However, the ability to carry out this approach for huge active open coal mines is insufficiently investigated, furthermore, the influences of topographical factors on the accuracy of DSM are ambiguous. This experiment attempts to apply the UAV method for the two active coal mines with the total area of 7.99 km2 , exploited at a range from -300 m to 300 m altitude to figure out the effect of topographic factors on the accuracy of DEM constructed from UAV images. A total of 972 UAV images and 17 ground control points have been coupled to construct DSM of the mines. Besides, 16 checking points located at different elevations are used to evaluate the accuracy of DEM and to define the influence. DEMs are generated with the maximum RMSE of 0.086 m, 0.099 m, and 0.170 m corresponding to X, Y, and Z dimensional errors. The results show the unclear correlation between the vertical accuracy of DEM and the relative elevation (R2=0.064), the general slope of the mines, and the number of ground control points using in the coal mines as well.