Contour Points Research Articles

An investigation on adaptive sculpting for the thin-walled surface parts using on-machine measurement

PurposeComplex and exquisite patterns are sculpted on the surface to beautify the parts. Due to the thin-walled nature, the blank of the part is often deformed by the forming and clamping processes, disabling the nominal numerical control (NC) sculpting programs. To address this problem, a fast adaptive sculpting method of the complex surface is proposed.Design/methodology/approachThe geometry of the blank surface is measured using on-machine measurement (OMM). The real blank surface is reconstructed using the non-uniform rational basis spline (NURBS) method. The angle-based flattening (ABF) algorithm is used to flatten the reconstructed blank surface. The dense points are extracted from the pattern on the image using the OpenCV library. Then, the dense points are quickly located on the complex surfaces to generate the tool paths.FindingsBy flattening the reconstructed surface and creating the mapping between the contour points and the planar mesh triangular patches, the tool paths can be regenerated to keep the contour of the pattern on the deformed thin-walled surface.Originality/valueThe proposed method can adjust the tool paths according to the deformation of the thin-walled part. The consistency of sculpting patterns is improved.

A Novel Prediction Model for Brain Glioma Image Segmentation Based on the Theory of Bose-Einstein Condensate.

BackgroundThe input image of a blurry glioma image segmentation is, usually, very unclear. It is difficult to obtain the accurate contour line of image segmentation. The main challenge facing the researchers is to correctly determine the area where the points on the contour line belong to the glioma image. This article highlights the mechanism of formation of glioma and provides an image segmentation prediction model to assist in the accurate division of glioma contour points. The proposed prediction model of segmentation associated with the process of the formation of glioma is innovative and challenging. Bose-Einstein Condensate (BEC) is a microscopic quantum phenomenon in which atoms condense to the ground state of energy as the temperature approaches absolute zero. In this article, we propose a BEC kernel function and a novel prediction model based on the BEC kernel to detect the relationship between the process of the BEC and the formation of a brain glioma. Furthermore, the theoretical derivation and proof of the prediction model are given from micro to macro through quantum mechanics, wave, oscillation of glioma, and statistical distribution of laws. The prediction model is a distinct segmentation model that is guided by BEC theory for blurry glioma image segmentation.ResultsOur approach is based on five tests. The first three tests aimed at confirming the measuring range of T and μ in the BEC kernel. The results are extended from −10 to 10, approximating the standard range to T ≤ 0, and μ from 0 to 6.7. Tests 4 and 5 are comparison tests. The comparison in Test 4 was based on various established cluster methods. The results show that our prediction model in image evaluation parameters of P, R, and F is the best amongst all the existent ten forms except for only one reference with the mean value of F that is between 0.88 and 0.93, while our approach returns between 0.85 and 0.99. Test 5 aimed to further compare our results, especially with CNN (Convolutional Neural Networks) methods, by challenging Brain Tumor Segmentation (BraTS) and clinic patient datasets. Our results were also better than all reference tests. In addition, the proposed prediction model with the BEC kernel is feasible and has a comparative validity in glioma image segmentation.ConclusionsTheoretical derivation and experimental verification show that the prediction model based on the BEC kernel can solve the problem of accurate segmentation of blurry glioma images. It demonstrates that the BEC kernel is a more feasible, valid, and accurate approach than a lot of the recent year segmentation methods. It is also an advanced and innovative model of prediction deducing from micro BEC theory to macro glioma image segmentation.

Multimodal image registration for power equipment using clifford algebraic geometric invariance

Imaging inspection and video monitoring are important means for power equipment condition monitoring and diagnosis. However, single model image cannot supply sufficient information for power equipment condition monitoring, such as infrared images and visible images. The image registration can bridge this gap. This paper develops an image registration method fused by infrared and visible images, which constructs the principal direction of corner points using neighborhood contour point geometric invariance under Clifford algebraic space. Simultaneously, we also design a law for fitting optimal spatial information in the main direction of corner points, where the Clifford rotation operator is utilized to realize the spatial transformation of the image to be registered. The experiment reveals that the average registration error is less than 3 pixels by this developed method, reaching sub-pixel registration, subsequently obtaining satisfactory fusion effect of power equipment. This algorithm enriches the multimodal image registration scheme and meets the requirements of monitoring power equipment.

Comparison of auto-contouring and hand-contouring of ultrasound images of the tongue surface

ABSTRACT Contours traced by trained phoneticians have been considered to be the most accurate way to identify the midsagittal tongue surface from ultrasound video frames. In this study, inter-measurer reliability was evaluated using measures that quantified both how closely human-placed contours approximated each other as well as how consistent measurers were in defining the start and end points of contours. High reliability across three measurers was found for all measures, consistent with treating contours placed by trained phoneticians as the ‘gold standard.’ However, due to the labour-intensive nature of hand-placing contours, automatic algorithms that detect the tongue surface are increasingly being used to extract tongue-surface data from ultrasound videos. Contours placed by six automatic algorithms (SLURP, EdgeTrak, EPCS, and three different configurations of the algorithm provided in Articulate Assistant Advanced) were compared to human-placed contours, with the same measures used to evaluate the consistency of the trained phoneticians. We found that contours defined by SLURP, EdgeTrak, and two of the AAA configurations closely matched the hand-placed contours along sections of the image where the algorithms and humans agreed that there was a discernible contour. All of the algorithms were much less reliable than humans in determining the anterior (tongue-tip) edge of tongue contours. Overall, the contours produced by SLURP, EdgeTrak, and AAA should be useable in a variety of clinical applications, subject to spot-checking. Additional practical considerations of these algorithms are also discussed.

An innovative PSO-ICCP matching algorithm for geomagnetic navigation

Geomagnetic aided navigation is an effective approach to eliminate the cumulative error in inertial navigation system (INS). Iterative closest contour point (ICCP) geomagnetic matching algorithm is sensitive to initial error, which will degrade the navigation accuracy greatly. To solve the problem, ICCP and particle swarm optimization (PSO) are improved separately, and an innovative PSO-ICCP geomagnetic matching algorithm is proposed. Firstly, a multi-attribute decision-making problem is introduced to optimize the output of ICCP. Secondly, PSO and ICCP are combined to diminish the sensitive of ICCP to initial error with the global search capability of PSO. Finally, to improve the performance of PSO, a particle initialization strategy is adopted using sliding window and quad-tree. Experimental results verified that PSO-ICCP can effectively reduce INS error. When magnetic measurement noise is 15nT, the position error and heading error are reduced from 1318.83 m, 7.83° to 23.51 m, 2.08°, which is more accurate compared with state-of-art algorithm.

Improved Iterative Closest Contour Point Matching Navigation Algorithm Based on Geomagnetic Vector

The geomagnetic matching aided positioning system based on Iterative Closest Contour Point (ICCP) algorithm can suppress the accumulation error of the inertial navigation system and achieve the accurate positioning of the vehicle. Aiming at the problem that the ICCP algorithm is sensitive to heading error and easily mismatches in regions with similar geomagnetic general features, an improved ICCP matching algorithm based on geomagnetic vector is proposed. The ant colony algorithm is designed to improve the search strategy in a large probability range. The geomagnetic three-dimensional vector feature and the Hausdoff distance are employed as the objective function for multiple iterations, improving matching efficiency and accuracy. Simulation results show that compared with the traditional ICCP algorithm, the positioning error of the matching track, the heading error, and the matching time of the improved ICCP algorithm are reduced by 69.6%, 44.0% and 39.0%, respectively.

Generation Algorithm of a Novel Platform Attached Support Structure for FDM-Fused Deposition Modeling

In the process of 3D printing, the setting of the initial layer is the most important step to achieve perfect printing results, and its main function is to prevent warping in 3D printing. There are three main types of the first layer: Raft, Brim, and Skirt. The Brim is a special skirt and is usually the preferred starting layer for the printing process. In order to increase the adhesion, multiple Brim contour edges will be printed, which increases the difficulty of removal. Otherwise, poor adhesion effect will occur. By analyzing the distinction between inner and outer contours of polygons, the offset process of contour points in different cases is calculated in this paper, and a simplified processing method of contour offset line is designed by using the idea of Douglas–Peucker simplifying curve feature points. According to the functional characteristics of the Brim edge structure, a novel platform attached support structure is generated based on ray-casting algorithm and contour offset algorithm. The proposed algorithm is encapsulated into the slicing engine and compared with three common initial layer structures for conducting part printing comparison experiments. The experimental results show that the edge structure realized by the proposed generation optimization algorithm of a novel platform attached support can effectively reduce the slicing execution time, and the auxiliary structure has little impact on the forming quality. It can be easier to remove on the premise and the warpage of the printing model is small.

Singular integral operators in the case of a piecewise Lyapunov contour

The article attempts to present the results obtained by the author in recent years (in a number of cases with some additions) on the theory of singular integral equations and Riemann boundary value problems in the case of a piecewise Lyapunov contour. It has a survey character of problems and results related to the influence of corner points of integration contour on various properties of singular operators. At the same time, much attention is paid to the research of other authors related to the scientific interests of the author of this work.

SPECIFICS OF CALCULATING AREAS OF CITY BLOCKS BY UTILIZING THE PHOTOGRAMMETRIC (PHOTOTHEODOLITE) METHOD

The definition of the territory of urban development by various methods, including such as geodetic, photogrammetric and cartographic, is considered. It is found that the use of geodetic methods with direct coordination of contour points of the figure on the ground allows to obtain the most accurate and reliable result. The advantages and disadvantages of using photogrammetric method of research located in a closed area, where you can not always see the entire contour of the area. It is noted that when processing aerial photographs, regardless of what they were obtained, there are questions of correct decoding. In the process of decoding is finding the right area, which is associated with the correct location of the contour surrounding the area. It is proved that photogrammetric methods for determining the area remain priority methods that helps to proper allocation of time and funding through the use of such an approach. Problems of using quasi-aerial photographs taken from a height of about 2 km are described. The main obstacles that arise when processing aerial photographs are analyzed, namely - correct decoding, which depends on the openness of the territory in which the city district is located, that is the presence of dead zones. Recommendations are given to eliminate problems that occur in dead zones where 3D measurements are virtually impossible, for example, in this case, you can use either multiple measurements or a comparative method with other methods of determining areas.

DISCRETE INTERPOLATION OF TWO-DIMENSIONAL POINT SETS BY FOUR POINTS SUPERPOSITIONS FOR PARABOLIC SURFACES

In the article it was proposed the general approach to determine change patterns of superposition coefficients of two-dimensional point sets. This makes possible to solve problems of continuous discrete interpolation and extrapolation any two-dimensional functional dependencies by numerical sequences, using four arbitrary nodal points.
 Coordinates of any point of two-dimensional point set can be represented by a coordinates’ superposition of four arbitrary points from this set. This allows to get analytical dependences to determine superposition coefficients values, solving corresponding systems of equations.
 It was investigated the discrete analogues formation process of two-dimensional geometric images, using as an example surfaces, whose components are polynomial functional dependences.
 In the research we established change patterns of superposition coefficients values of three nodal basic contour points and an internal nodal point. These patterns are represented in the form of surfaces-graphs of two variables numerical sequences for a chosen calculation scheme.
 The received regularities allow to form surfaces, using the applicates of three basic contour points and an internal point. These surfaces are on a given calculation scheme and components of their frames are polynomial functional dependences.
 The studies determine the general approach of obtaining similar change patterns of four arbitrary points superposition coefficients. These points can be as adjacent as non-adjacent node points of a selected calculation scheme. The regularities are used to determine n points coordinates of any two-dimensional functional dependences and arbitrary two-dimensional point sets.
 In the future, the results of this work will allow to determine value change patterns of one of four superposition coefficients of given four node points (both adjacent and non-adjacent) of different two-dimensional numerical sequences. This will make possible to solve problems of continuous discrete interpolation and extrapolation of any two-dimensional functional dependences by numerical sequences (such as determination the applicates of required points of discrete frames of two-dimensional geometric image) without laborious operations of compilation and solving huge systems of linear and transcendental equations.

Multilevel Image Edge Detection Algorithm Based on Visual Perception

Multilevel image edge repair results directly affect the follow-up image quality evaluation and recognition. Current edge detection algorithms have the problem of unclear edge detection. In order to detect more accurate edge contour information, a multilevel image edge detection algorithm based on visual perception is proposed. Firstly, the digital image is processed by double filtering and fuzzy threshold segmentation; Through the analysis of the contour features of the moving image, the threshold of the moving image features is set, and the latest membership function is obtained to complete the multithreshold optimization. Adaptive smoothing is used to process the contour of the object in the moving image, and the geometric center values of the two adjacent contour points within the contour range are calculated. According to the calculation results, the curvature angle is further calculated, and the curvature symbol is obtained. According to the curvature symbol, the contour features of the moving image are detected. The experimental results show that the proposed algorithm can effectively and accurately detect the edge contour of the image and shorten the reconstruction time, and the detection image resolution is high.

Studying the deformation and failure of salt rocks for geomechanical assessing the stability of elements of the system for the mining at potash deposits

Сomplex studies aimed at developing methods for assessing the stability of inter-chamber pillars used in the conditions of the Verkhnekamskoe potash salt deposit has been carried out. Field measurements of massif deformations in the vicinity of the treatment chambers were done using contour and deep reference points. It has been established that the most informative indicator reflecting the geomechanical situation in the underground section of the potassium salt deposit is the lateral deformation of the pillars. To assess the standard rates of deformation of inter-chamber pillars, laboratory research was conducted to study the deformation of salt samples under the action of a constant load in the step loading mode, as well as the determination of longitudinal and lateral deformations during compression of large scale samples. As a part of the development of a method for calculating the equivalent strength of inter-chamber pillars, complex experimental studies were undertaken on layered cement-sand samples. In order to reveal the influence of the length of inter-chamber pillars on their stability, experimental studies of the shape coefficient were held on rectangular sylvinite samples of various lengths. To take into account the influence of the time factor on the stability and deformability of the rocks in the roof of mine workings, the creep of salt rocks under uniaxial stepped tension was studied experimentally. Within the framework of solving the problem of transferring the results of experimental determination of physical and mechanical properties of rocks to the full-scale level, theoretical and experimental studies were conducted to detect the scale effect in salt rocks under uniaxial compression.

Coupled Splines for Sparse Curve Fitting.

We formulate as an inverse problem the construction of sparse parametric continuous curve models that fit a sequence of contour points. Our prior is incorporated as a regularization term that encourages rotation invariance and sparsity. We prove that an optimal solution to the inverse problem is a closed curve with spline components. We then show how to efficiently solve the task using B-splines as basis functions. We extend our problem formulation to curves made of two distinct components with complementary smoothness properties and solve it using hybrid splines. We illustrate the performance of our model on contours of different smoothness. Our experimental results show that we can faithfully reconstruct any general contour using few parameters, even in the presence of imprecisions in the measurements.

ACE: Anchor-Free Corner Evolution for Real-Time Arbitrarily-Oriented Object Detection.

Objects with different orientations are ubiquitous in the real world (e.g., texts/hands in the scene image, objects in the aerial image, etc.), and the widely-used axis-aligned bounding box does not compactly enclose the oriented objects. Thus arbitrarily-oriented object detection has attracted rising attention in recent years. In this paper, we propose a novel and effective model to detect arbitrarily-oriented objects. Instead of directly predicting the angles of oriented bounding boxes like most existing methods, we evolve the axis-aligned bounding box to the oriented quadrilateral box with the assistance of dynamically gathering contour information. More specifically, we first obtain the axis-aligned bounding box in an anchor-free manner. After that, we set the key points based on the sampled contour points of the axis-aligned bounding box. To improve the localization performance, we enrich the feature representations of these key points by exploiting a dynamic information gathering mechanism. This technique propagates the geometrical and semantic information along the sampled contour points, and fuses the information from the semantic neighbors of each sampled point, which varies for different locations. Finally, we estimate the offsets between the axis-aligned bounding box key points and the oriented quadrilateral box corner points. Extensive experiments on two frequently-used aerial image benchmarks HRSC2016 and DOTA, as well as scene text/hand datasets ICDAR2015, TD500, and Oxford-Hand, demonstrate the effectiveness and advantage of our proposed model.

ИЗМЕНЕНИЕ НАПРЯЖЕННОГО СОСТОЯНИЯ СКЛОНА ГОРЫ С УСТУПОМ ПОД ДЕЙСТВИЕМ ВНЕШНЕЙ НАГРУЗКИ С УБЫВАЮЩЕЙ ТРЕУГОЛЬНОЙ ЭПЮРОЙ

The Kyrgyz Republic covers an area of – 198,5 thousand km2. Mountains and mountain slopes occupy more than 94 % of the country. For this reason, in mountainous areas, mountain slopes are used for conducting various types of human economic activity ledges at different heights of the mountain slope, from hundreds of meters to 4–5 km. The object of the study is the ledges of the mountain slope, which are necessary for economic activity, located at different heights of the slope. The subject of the study is the initial and changed stress-strain state of the massif near the scarp of the mountain slope from the action of gravitational and tectonic forces. The aim of the study is to create a mathematical model and calculate the stress-strain state of the massif near the scarps of the mountainside to check the boundary conditions with the load of a decreasing triangular epure. The objective of the study is to establish the laws of stress distribution in each point of the massif by solving the differential equation of equilibrium using the Kolosov-Muskhelishvili method. Ledges are formed either by nature or created by man, technogenically, and are mated with the mountain slope at a different angle of inclination at different heights of the slope. To assess the stability and safety from landslide processes of structures located in the ledge zone, it becomes necessary to carefully study the stress-strain state of the massifs. To study the stress state of a rock mass, the following main methods have been used: the unloading method, the finite element method, the finite difference method, as well as the analytical methods of Kolosov-Muskhelishvili in the version where the conformal mapping is used [Gulnara]. Thus, to study the state of massifs in the zone of ledges of the mountain slope, it is necessary to create an analytical model of the stress-strain state of massifs of ledges of the mountain slope, in which the zones of conjugation of the ledge and the mountain slope, the possible heights of the ledge, the effect of volumetric and surface loads would be taken into account in a single analytical model. In this case, the authors consider the problem when the stress state of a mountain massif with a symmetrical scarp in natural conditions, which is formed under the combined action of gravitational, horizontal tectonic forces and external distributed loads with a triangular epure. The problem is solved using the Kolosov-Muskhelishvili method and the MATNCAD software environment. As a result of the calculations, the patterns of stress distribution in the massifs of the mountain slope with a ledge have been created, where the actions of gravitational, horizontal tectonic forces were taken into account each separately. To check the boundary conditions with a load with a decreasing triangular diagram, the stresses are calculated for the contour points in the vicinity of the loaded section of the contour. The patterns of distribution of the initial stress state of the slope mass with ledges are presented for each stress component in the form of stress isolines.

Interpretation of dynamic parameters of local anomalies of refracted waves

The «common contour point» (CCP) technique for finding oil and gas deposits is based on identifying simple local minima on the graphs of the amplitude and energy of seismic waves passing through the reservoir. Simple local minima according to the CCP technique are provided by the identification of crossline profile geophones, the stability of the critical angle of the refracted wave, minor changes in the geometric divergence of seismic waves and the source-receiver distance. Other anomalies caused by local inhomogeneities of the geological environment are overcome based on the correlation of the dynamic parameters of waves recorded from different directions in the crossline profile. The article experimentally demonstrates obtaining simple minima by eliminating the distorting effect of local heterogeneity in the upper part of the section, determining the corresponding characteristic points of minima, as well as the contour and depth of the predicted reservoir. Keywords: oil and gas reservoir; direct search; seismic wave amplitude; local anomaly; «Common contour poin» technique.

Estimation of Arc Welding Pressure Pipeline Weld Peaking Parameters Based on Data Prediction

Peaking parameter is the key content in the regular inspection of the pressure pipeline. Solving the problem of the peaking measurement method defined by a standard cannot be applied to a situation in which there exists a weld surface with reinforcement and misalignment. In this paper, a peaking estimation method based on data prediction was proposed to estimate the contour information of the base metal at the weld joint using the contour point set data of the base metal part of the weld. Herein, the longitudinal weld peaking estimation method based on a piecewise logistic regression (PLR) and the girth weld peaking estimation method based on a piecewise Bayesian linear regression (PBLR) were studied, and the midpoint of the two symmetrical points of the base metal on either side of the weld was used as a reference for calculating the peaking. Finally, we collected the surface profile data of longitudinal weld pressure pipes with diameters of 155 mm, 255 mm, 550 mm, and 600 mm and the surface profile data of girth weld pressure pipes with diameters of 120 mm, 130 mm, 140 mm, and 170 mm. This weld seam data used the data estimation method proposed in this article and traditional long short-term memory and fitting methods. The results showed that the proposed data prediction method could accurately predict the position of the base metal, and the theoretical mean absolute error of the peaking estimation based on the PBLR and PLR could attain 0.06 mm and 0.07 mm, respectively, which meets the parameter measurement requirements of related verification fields.

About the approximation of the tunnel lining deformations according to the measurement results

The article deals with the approximation of the displacements of the points of the tunnel lining contour, obtained, for example, by geodetic survey. In the future, the processed data can be used to calculate the internal forces in the tunnel lining, which will help in monitoring the technical condition of the bearing structures of underground structures. In the article, calculation formulas have been obtained that allow using the measured displacements of the reference points to find the displacements of any point of the lining. Displacements are determined by approximating deformations with periodic cubic splines. To determine the coefficients of splines, it is proposed to apply the common least squares method. A method for calculating the weighting coefficients of basic functions for a spline with an arbitrary step of the nodes is presented. As an intermediate result, analytical dependences were obtained between the Cartesian coordinates of the tunnel lining points and the arc length. In this case, the design data on the radii of curvature of the lining sections and the coordinates of the points of section conjugation were used. It is assumed that the data obtained will increase the information content of the control and can be used to monitor its technical condition of underground structures at all stages of its life cycle.

Accurate and robust feature description and dense point-wise matching based on feature fusion for endoscopic images.

Despite the rapid technical advancement of augmented reality (AR) and mixed reality (MR) in minimally invasive surgery (MIS) in recent years, monocular-based 2D/3D reconstruction still remains technically challenging in AR/MR guided surgery navigation nowadays. In principle, soft tissue surface is smooth and watery with sparse texture, specular reflection, and frequent deformation. As a result, we frequently obtain only sparse feature points that give rise to incorrect matching results with conventional image processing methods. To ameliorate, in this paper we enunciate an accurate and robust description and matching method for dense feature points in endoscopic videos. Our new method first extracts contours of the low-rank image sequences based on the adaptive robust principal component analysis (RPCA) decomposition. Then we propose a multi-scale dense geometric feature description approach, which simultaneously extracts dense feature descriptors of the contours in the original Euclidean coordinate space, the accompanying 3D color coordinate space, and the derived curvature-gradient coordinate space. Finally, we devise a new algorithm for both global and local point-wise matching based on feature fusion. For global matching, we employ the fast Fourier transform (FFT) to reduce the dimension of the dense feature descriptors. For local feature point matching, in order to enhance the robustness and accuracy of the matching, we cluster multiple contour points to form "super-point" based on dense feature descriptors and their spatio-temporal continuity. The comprehensive experimental results confirm that our novel approach can overcome the highlight influence, and robustly describe contours from image sequences of soft tissue surfaces. Compared with the state-of-the-art feature point description and matching methods, our analysis framework shows the key advantages of both robustness and accuracy in dense point-wise matching, even when the severe soft tissue deformation occurs. Our new approach is expected to have high potential in 2D/3D reconstruction in endoscopy.

A novel cooling hole inspection method for turbine blade using 3D reconstruction of stereo vision

Cooling holes (number 100 ∼ 200, diameter 0.3 ∼ 1.2 mm) are important heat dissipation structures of a turbine blade in aero-engine. Due to the small sizes and similar contours of cooling holes, it is difficult to extract and match their features by traditional stereo reconstruction methods. This paper proposes a novel cooling hole inspection method for turbine blades utilizing 3D reconstruction technique of stereo vision, which combines the stereo vision principle with the invariance of cross-ratio. The feature points of contours are extracted and matched by calculating two intersection points of circular contours and a line through the center points of adjacent cooling holes. Additionally, the 3D points corresponding to the feature points are reconstructed, by which, the diameters of cooling holes can be calculated successfully. Moreover, measurement experiments verify the effectiveness and accuracy of the proposed method. The experimental results show that the average errors of the standard circle ruler and tiny hole sample are within 0.05 mm, which satisfies the inspection requirement of cooling holes.