43 results about "Edge matching" patented technology

The invention relates to the technical field of multi-image fusion recognition, in particular to a data fusion method and system for CCD visual detection, and the method comprises the following steps: obtaining a horizontal pixel row calculation gradient construction trend sequence, repairing an edge fracture to generate an integrity index, extracting a gray value to detect feature mutation, and distributing fusion weights to establish a mapping relation. And executing image fusion and balancing the contrast to generate a fusion matrix result. According to the method, the fracture edge region is identified, interpolation compensation is executed, the structural similarity index of the local gray sequence in the image overlapping region and feature direction mutation detection are combined, accurate identification of the edge matching result is guided, and fusion weight factor mapping corresponding to signal-to-noise ratio distribution is introduced; according to the method, the distribution relation between the pixels in the region and the credible weight is effectively established, the edge transition among the multi-source images is more natural through Poisson constraint and contrast balance adjustment of the fusion region, and the structural fidelity and the judgment stability of the fusion image are remarkably enhanced.

The present invention relates to the technical field of image detection, and in particular to a method for rapid detection of a fracture region in a precision-stamped part of a new energy vehicle. The method comprises: acquiring a complete stamped part grayscale image; acquiring each sub-region in the complete stamped part grayscale image; for each sub-region, taking a fitting curve of all edge pixels of the sub-region as an edge curve of the sub-region, and constructing a curvature evaluation factor between each pixel and the adjacent previous pixel on the edge curve; constructing the degree of curvature change of the edge curve; constructing a curvature sequence and a distance sequence of the edge curve; acquiring each subsequence of the curvature sequence of the edge curve; constructing the fracture edge matching degree, a local stress discontinuity index and a fracture region confidence level of the sub-region; and on the basis of the fracture region confidence levels of all sub-regions, using a clustering algorithm to cluster and delineate a fracture region. According to the present invention, the accuracy of detection of the fracture region in the precision-stamped part of the new energy vehicle can be improved.

The invention relates to the technical field of anti-counterfeiting, in particular to a double-layer anti-counterfeiting label system and method based on artificial intelligence, and the system comprises an image acquisition module, a color block analysis module, a particle distribution module and an anti-counterfeiting recognition module. The method comprises the following steps: acquiring an initial anti-counterfeiting image containing an anti-counterfeiting label according to user requirements, and splitting the initial anti-counterfeiting image into a color block frame image, a particle distribution image and a two-dimensional code image; analyzing the color block frame image to obtain an edge feature of the color block frame image, and performing feature matching on the edge feature of the color block frame image and the two-dimensional code image to obtain an edge matching feature; performing matching analysis on metal particle distribution in the particle distribution image to obtain a particle distribution state of the metal particles; performing feature matching on the particle distribution state and the two-dimensional code image to obtain a particle state vector; verifying the initial anti-counterfeiting image based on the edge matching feature and the particle state vector; and the identification precision and reliability of the anti-counterfeit label are improved.

The invention discloses a distributed urban and rural planning decision support method and system, and relates to the technical field of data analysis, and the method comprises the following steps: S100, drawing a planar graph of a to-be-planned region, dividing the planar graph of the region according to a Morse decomposition method, and constructing a region matrix, S200, calculating the coverage rate of the region matrix, and S300, calculating the coverage rate of the region matrix. And planning the surveying and mapping path. According to the method, planning units and surveying and mapping grids are unified into the same quadrilateral matrix through Morse complex, repeated zoning and edge matching errors are effectively avoided, the edge weight is inversely proportional to the building coverage rate, an unmanned aerial vehicle and a surveying and mapping vehicle automatically and preferentially encrypt a high built-up area, field working hours are saved, the data precision of a core construction area is guaranteed, and the construction efficiency is improved. The regional matrix naturally corresponds to edge nodes, and each node only communicates with an adjacent unit, so that the MST and the local route can be locally solved, the communication complexity is reduced, and the method is suitable for large-scale regional surveying and mapping.

The invention provides a self-adaptive reverse multiple exposure phase fusion technology, and relates to the field of high-dynamic-range three-dimensional reconstruction. The method includes the following steps that firstly, a saturated pixel mask matrix is obtained by judging pixels of a high-reflection area, then uniform grey-scale maps are selected step by step through a gradient adjustment method to obtain the optimal local projection intensity, and local coding and decoding are conducted on the high-reflection area through the optimal projection intensity pattern. And replacing an invalid phase value in the high-SNR image with a local phase value under the optimal projection intensity through an edge matching and phase fusion technology, and obtaining high-quality complete three-dimensional imaging information through coordinate mapping after a complete phase diagram is obtained. According to the method, the optimal projection intensity is adaptively determined through a small number of patterns, meanwhile, the high SNR of imaging patterns is guaranteed, and high-precision complete three-dimensional imaging is carried out on an HDR object. Experimental results show that in a traditional method, a large number of point clouds are lost in a saturated pixel area, the imaging integrity and the measurement precision cannot achieve the normal imaging effect, and the algorithm of the invention shows high integrity and high point cloud density in a dark area and a high-reflection area.

The invention discloses an acquisition device of a background knife edge matching graph and an acquisition method of a background schlieren graph, and belongs to the technical field of schlieren imaging.The acquisition device of the background knife edge matching graph uses a transparent background particle plate as a particle background of background schlieren; and the transparent background particle plate is placed in a knife edge schlieren light path to form a fusion light path. The knife edge schlieren and the background schlieren are integrated on the same fusion light path, so that a matching graph between the background schlieren and the knife edge schlieren under a gas density disturbance flow field is acquired under the conditions of the same flow field and the same visual angle. Further, carrying out difference calculation and filtering on the image A and the image B according to pixels to remove particle ghosts, and obtaining an image D only carrying knife edge schlieren; carrying out difference calculation and particle morphology enhancement on the image A and the image D to obtain an image E only containing particle information, and then carrying out particle displacement calculation; the operation is simple, the calculation complexity is low, and the accurate background schlieren graph can be quickly obtained.

The invention provides an edge matching positioning method and system. The method comprises the following steps: acquiring a real-time image and a reference image in a sample library; inputting the real-time image and the reference image into a pre-constructed region score model to obtain a matching calculation score output by the region score model; based on the matching calculation score, performing paraboloid fitting by taking a matching peak value and a neighborhood as sampling points to obtain a sub-pixel position offset; and adding the sub-pixel position offset to the coordinate value of the current matching position to obtain a final positioning position coordinate. The technical problem that the positioning precision of edge matching calculation is low is solved.

The invention discloses a shipping accident analysis method. The method comprises the following steps: constructing a shipping accident knowledge graph; inputting questions, retrieving the shipping accident knowledge graph by adopting a retrieval enhancement generation method, and generating answers; wherein the retrieval enhancement generation method is adopted to retrieve the shipping accident knowledge graph and generate the answer, and the method comprises the following steps of: analyzing a question by adopting a large language model to generate a query statement; retrieving in the shipping accident knowledge graph according to the query statement, outputting nodes and edges matched with the query statement from the shipping accident knowledge graph, and generating a Bayesian network according to the matched nodes and edges; generating a query result according to the conditional probability of a target node and a father node thereof and / or the posterior probability of a child node thereof in the Bayesian network, and inputting the query result into the large language model; and the large language model generates an answer according to the query result. The invention further discloses a shipping accident analysis device, computer equipment and a storage medium. The method comprises the following steps: extracting and storing shipping accident data by adopting a large language model in combination with a knowledge graph, and analyzing the shipping accident data in combination with a Bayesian network analysis model to obtain an occurrence probability of a complete causal chain from causes to accident results in an accident, so that objective and accurate accident causals are sorted out for complex shipping accidents, and the probability of occurrence of the complete causal chain is improved. And reliable conclusions and suggestions are provided for subsequent shipping businesses.

The invention provides a missile carrier positioning ring assembling method and system based on vision and angle registration, and the method comprises the steps: collecting a missile carrier positioning hole region image through an industrial camera, extracting hole position geometric information after image processing, and calculating the angle of a missile carrier positioning hole column relative to a camera coordinate system; the chuck is controlled by the PLC to rotate the missile carrier, and the target hole column of the missile carrier is adjusted to be in the vertical upward direction; acquiring an image of the positioning ring, identifying asymmetric structure features to extract a main shaft direction angle, and calculating an angle difference between the missile carrier and the positioning ring; a positioning ring is clamped through a clamp at the tail end of a robot, a planning path is converted through a multi-stage coordinate system, angle pre-compensation is conducted on the positioning ring in the carrying process, the positioning ring is inserted into a missile carrier hole site through an adsorption and limiting structure, and meanwhile the insertion force and speed are adjusted based on feedback of a force / torque sensor; and after assembly, collecting a reinspection image, analyzing and evaluating the insertion depth and the boundary offset through edge matching, and judging whether the assembly is qualified or not according to a preset threshold value.

The application discloses a motor insert sheet defect detection method based on multi-sensor fusion, relates to the technical field of motor insert sheet defect detection, and comprises the following steps: in the presence of boundary penetration, calculating edge matching mismatch degree, edge jump rate, edge inversion proportion and edge closure deviation to form a geometric conflict feature set of an insert sheet edge, which is used for representing image geometric expression differences caused by boundary penetration; inputting the geometric conflict feature set into a fusion confidence evaluation function to obtain a fusion confidence evaluation factor, which is used for identifying whether the insert sheet edge has a fusion distortion risk. The application solves the structural expression conflict problem caused by boundary penetration in the multi-view imaging fusion process of the motor insert sheet, constructs a fusion confidence evaluation mechanism to identify the fusion distortion risk, dynamically limits the image participation fusion condition, and thus improves the recognition accuracy of the edge structure and the stability of the fusion result in the insert sheet defect detection.

The application discloses a shipping accident analysis method, comprising the following steps: constructing a shipping accident knowledge graph; inputting a question, searching the shipping accident knowledge graph by using a search enhancement generation method, and generating an answer; wherein the search enhancement generation method comprises the following steps: analyzing the question by using a large language model, generating a query statement, searching the shipping accident knowledge graph according to the query statement, outputting nodes and edges matched with the query statement from the shipping accident knowledge graph, generating a Bayesian network according to the matched nodes and edges, generating a query result according to the conditional probability of a target node and its parent nodes and / or the posterior probability of the target node and its child nodes in the Bayesian network, inputting the query result into the large language model, and generating an answer according to the query result by the large language model. The application further discloses a shipping accident analysis device, a computer device and a storage medium. By using a large language model combined with a knowledge graph to extract and store shipping accident data, and by using a Bayesian network analysis model to analyze the shipping accident data, the occurrence probability of a complete cause-and-effect chain from causes to results of an accident can be obtained, so that objective and accurate causes and effects of a complex shipping accident can be sorted out, and reliable conclusion opinions can be provided for subsequent shipping business.

The invention discloses an incremental mapping method and device and a storage medium, and the method comprises the steps: stopping employing a priori map for positioning if it is detected that a mobile device is out of the range of the priori map, and carrying out the positioning based on a constructed incremental map; if it is detected that the mobile device moves from the outside of the prior map range to the inside of the prior map range, starting a prior map for positioning, matching the environment perception data at the current moment with the prior map based on a branch and bound algorithm, and obtaining a matching score corresponding to a successfully matched pose; unary edge constraints are added to poses corresponding to the environment perception data with the matching scores larger than a preset score threshold value; and carrying out accumulative error optimization on the calculated pose by utilizing unary edge constraint so as to align the incremental map with the prior map. The mapping pose is restrained by adding the unary edge matched with the prior map, the alignment effect between the incremental map and the prior map can be improved, and map ghosting and faults are avoided.

The application discloses a photovoltaic array fault detection and positioning method based on bipartite graph matching, comprising the following steps: 1) based on the connection structure of a photovoltaic array, a photovoltaic array bipartite graph is established, and the connection points of components on the same photovoltaic component string constitute an independent node set in a sub-bipartite graph; 2) under the complete matching rule of the bipartite graph, the minimum edge covering rule and the constraint that equal-weight points in the bipartite graph are not connected, edge matching of the bipartite graph is derived, the edge is converted into a voltage sensor, and optimal configuration of the voltage sensor is obtained; 3) the fault voltage threshold of the photovoltaic component under different faults is calculated, the actual measured value of the photovoltaic component voltage collected by the voltage sensor is compared with the fault voltage threshold, and photovoltaic array fault detection and positioning are realized. The application realizes accurate detection and positioning of open-circuit, short-circuit, aging and shading faults of each photovoltaic component by using fewer voltage sensors, and the voltage sensor only needs to be connected between adjacent photovoltaic component strings, and is easy to operate.

The present invention discloses an image edge matching method, device, computer device, and storage medium. The image edge matching method includes: obtaining an image matching request, where the image matching request includes a target image and search matching parameters; performing pyramid compression processing on the target image to obtain target gradient information corresponding to the target image; screening a plurality of pre-created angular templates according to the search matching parameters to determine a template to be matched and corresponding edge gradient information to be matched with the template to be matched; using the target gradient information to match the plurality of edge gradient information to be matched, obtaining an edge matching degree corresponding to each edge gradient information to be matched, and determining an optimal matching position and an optimal matching angle according to the edge matching degree. This technical solution determines the optimal matching position and the optimal matching angle according to the edge matching degree, improving the edge matching efficiency and matching accuracy of the target image.

The invention discloses an irregular polygon mesh pattern generation algorithm. The generation algorithm comprises the following steps: S1, constructing an initial polygon cluster in a two-dimensional coordinate system; s2, extracting a peripheral boundary polygon of the current polygon cluster as a growth base point; s3, performing Poisson disk sampling on each growth base point to generate a secondary polygon cluster; s4, carrying out topological splicing on the secondary polygon cluster and the current polygon cluster by adopting an edge matching algorithm, and realizing geometric fusion of polygons in overlapped regions through vertex coordinate weighted average; s5, taking the fused polygon cluster as a new current cluster, and repeating the steps S2-S4 until a preset area size is reached; s6, performing curvature smoothing processing on the final polygon cluster; according to the irregular polygonal mesh pattern generation algorithm, the moire phenomenon in the touch display screen can be effectively eliminated, so that the watching experience and the visual effect are remarkably improved, and by adopting the irregular polygonal mesh pattern, the regular structure of an optical assembly is reduced.

The invention is suitable for the technical field of operation and maintenance management of Internet of Things equipment, and provides an Internet of Things equipment repair process management method and system and computer device.The method comprises the steps that on the basis of a directed graph structure, a repair process model comprising multiple nodes and multiple edges connected with the nodes is constructed in advance; binding an automatic task node in the repair process model with a task script, and respectively configuring circulation conditions for a plurality of edges led out from the automatic task node; when a repair request is received, creating a work order based on the repair request and starting a repair process instance; when the repair process instance flows to the automatic task node, automatically triggering and executing the task script bound with the repair process instance; and according to the received execution feedback data, a target edge with a transfer condition matched with the execution feedback data is decided in the repair process model, and the repair process instance is driven to transfer to a next node along the target edge. According to the invention, the problems of slow response and low efficiency of repair management of the existing Internet of Things equipment are solved.

The invention discloses a bipartite graph matching-based photovoltaic array fault detection and positioning method, which comprises the following steps of: 1) establishing a photovoltaic array bipartite graph based on a photovoltaic array connection structure, and forming an independent node set in a sub bipartite graph by component connection points on the same photovoltaic component string; 2) exporting edge matching of the bipartite graph under the constraints of a complete matching rule and a least edge coverage rule of the bipartite graph and unconnected medium weight points in the bipartite graph, converting edges into voltage sensors, and obtaining optimal configuration of the voltage sensors; and (3) calculating fault voltage thresholds of the photovoltaic module under different faults, collecting voltage measured values of the photovoltaic module through a voltage sensor, and comparing the voltage measured values with the fault voltage thresholds to realize fault detection and positioning of the photovoltaic array. According to the method, fewer voltage sensors are adopted, accurate detection and positioning of open circuit, short circuit, aging and shielding faults of each photovoltaic module are achieved, the voltage sensors only need to be connected between the adjacent photovoltaic module strings, and operation is easy.

Methods and apparatuses that may improve the accuracy of three-dimensional models from intraoral scan data using edge mapping of an un-patterned illumination images (e.g., white light, near-infrared light, fluorescent light, etc.) and a depth map from a 3D model of the dentition generated from the same intraoral scan as the un-patterned illumination image. This method involves generating an alignment transform using edges identified in an un-patterned illumination image captured during an intraoral scan and images of taking patterned illumination scans, to match edges extracted from the uniform light image with edges in the 3D model (and / or from the patterned illumination image).

The present disclosure provides an outdoor apple recognition and positioning method and system based on multi-sensor fusion, which relates to the technical field of target detection. It includes obtaining image data and lidar point cloud data of outdoor apples, inputting the image data into a target detection model to obtain an RGB image; obtaining an ROI depth information area through calibrating the external reference matrix; using an edge detection algorithm to extract image edge features from the RGB image to obtain an ROI edge information map; denoising and detecting discontinuous points in the ROI depth information area to obtain depth edge data; using a double-edge matching algorithm to perform edge feature matching on the depth edge data and the ROI edge information map, and using a RANSAC fitting algorithm to generate a smooth edge curve of the apple; constructing a sphere model according to the fitting result, and solving the center coordinates and radius by minimizing the sum of squared residuals to obtain the three-dimensional positioning information of the apple.

The invention belongs to the technical field of surveying and mapping, and particularly relates to a multi-source digital elevation model splicing optimization method combining a third-order polynomial and a Bezier curve. The method is suitable for splicing DEM data obtained by unmanned aerial vehicle oblique photography and RTK measurement, and is especially used for solving the abrupt and discontinuous problems of heterogenous digital elevation model (DEM) data in an edge matching area due to inconsistent resolution and elevation precision. The method comprises the steps of data acquisition and conversion, grid resampling, overlapped region extraction and weighted splicing, third-order polynomial fitting processing, Bezier curve smooth correction and the like. Buffer areas are constructed on the two sides of the splicing line, a similarity threshold value is set, trend surface fitting and transition curved surface construction are guided, and the elevation continuity and the model smoothness of the splicing area are effectively improved. And finally, precision verification is carried out through a root mean square error (RMSE), and the consistency and availability of the spliced DEM in spatial expression are ensured.

The invention discloses a panoramic image splicing method and system based on multi-feature guidance and related equipment, and belongs to the technical field of computer vision and image processing, and the method comprises the steps: respectively carrying out the extraction of point features, linear structures and edge curve structures of a reference image and a target image; performing neighborhood division on the extracted straight line structures and the edge curve structures, selecting point features in neighborhoods to construct projection invariants, and calculating matching relations between the straight line structures and between the edge curve structures to obtain straight line structure matching pairs and intersection point matching pairs based on curve structure matching; and performing grid division on the reference image and the target image, generating a distorted image aligned with the reference image according to the point feature matching pair, the linear structure matching pair and the intersection point matching pair based on curve structure matching, and obtaining a panoramic image. Under a low-texture image scene, the defects of point and line features are overcome through irregular edge matching constraints, and the alignment quality and splicing precision of image splicing are improved.

The present invention discloses a point cloud registration method combining edge features, which includes obtaining the point cloud of a template workpiece, searching for edge points and storing them in the template edge point cloud; obtaining the measured workpiece point cloud, searching for edge points and storing them in the measured edge point cloud; using the nearest neighbor search method to obtain the measured matching point set and the edge matching point set; constructing an objective function using the template workpiece point cloud, the measured matching point set, the template edge point cloud, and the edge matching point set; and using an optimization method to iteratively solve the objective function to obtain the rotation matrix R and the translation matrix t, thereby completing the registration between the template workpiece point cloud and the measured workpiece point cloud. This method aims to solve the registration problem in the case where the surface topography of the workpiece has a small undulation and the texture is not rich.

A perception and map edge association system for an autonomous vehicle includes one or more controllers executing instructions to receive a plurality of perception lane edge candidates that are each representative of a perception lane edge and a plurality of map lane edge candidates that are each representative of a map lane edge. The one or more controllers identify a discrepancy between a selected perception lane edge candidate and a best fit map edge candidate for a lane characteristic based on a posterior association probability matrix and a discrepancy flag. The one or more controllers segment the pair of inconsistent perception and map lane edges into one or more matching segments. The one or more matching segments indicate where the perception lane edge and the map lane edge match one another based on the lane characteristics. The perception and map edge association system improves localization and scene creation performance.

The invention discloses a motor insert defect detection method based on multi-sensor fusion, and relates to the technical field of motor insert defect detection, and the method comprises the following steps: calculating an edge matching mismatch degree, an edge jump rate, an edge inversion ratio and an edge closing deviation under the condition of boundary interspersion, forming a geometric conflict feature set of insert edges, and calculating the edge matching mismatch degree, the edge jump rate, the edge inversion ratio and the edge closing deviation; the representation module is used for representing image geometric expression differences caused by boundary interpenetration; and inputting the geometric conflict feature set into a fusion confidence evaluation function to obtain a fusion confidence evaluation factor for identifying whether the edge of the insert has a fusion distortion risk or not. According to the method, the problem of structural expression conflict caused by boundary interpenetration in the multi-view imaging fusion process of the motor insert is solved, a fusion confidence evaluation mechanism is constructed to identify the fusion distortion risk, and the image participation fusion condition is dynamically limited, so that the identification accuracy of an edge structure and the stability of a fusion result in insert defect detection are improved.

Methods and apparatuses that may improve the accuracy of three-dimensional models from intraoral scan data using edge mapping of an un-patterned illumination images (e.g., white light, near-infrared light, fluorescent light, etc.) and a depth map from a 3D model of the dentition generated from the same intraoral scan as the un-patterned illumination image. This method involves generating an alignment transform using edges identified in an un-patterned illumination image captured during an intraoral scan and images of taking patterned illumination scans, to match edges extracted from the uniform light image with edges in the 3D model (and / or from the patterned illumination image).

This application discloses a method, apparatus, device, and storage medium for recognizing the edge contour of a graphic, relating to the field of machine vision technology. The method includes: image processing of an image to be recognized to obtain pyramid gradient images at different levels of the image; inputting the pyramid gradient images into a preset edge matching model to obtain a set of candidate points for the contour of a target graphic in the image to be recognized, wherein the preset edge matching model is a model trained based on sample images labeled with the target graphic using a sparse sampling method and an adaptive threshold segmentation method; and connecting the candidate points in the candidate point set to obtain the target graphic in the image to be recognized. In this application, the adaptive threshold segmentation method clearly distinguishes the contour of the target graphic from the contours of other graphics, and the sparse sampling method reduces the number of candidate points obtained. Therefore, the preset edge matching model can obtain a small number of accurate candidate points, thereby improving the accuracy of recognizing the target graphic using the matching method.

The invention provides a road surface target identification method and system based on Hough transformation, and the method comprises the steps: obtaining an edge image of a target image and an edge image of a to-be-matched image, and carrying out the generalized Hough transformation of the edge image of the target image and the edge image of the to-be-matched image; establishing a mapping table of the edge image of the to-be-matched image; initializing a matching area confidence accumulator according to the size of the edge image of the target image; traversing the edge points of the edge image of the target image, calculating the position of each possible image to be matched according to the edge angle, and adding 1 to the confidence accumulator; a plurality of local maximum values in the target area are obtained through matching parameter space searching, and each local maximum value corresponds to one road surface target in the target area. Edge matching replaces an existing surface matching algorithm, the calculation amount in the recognition process is reduced, and the accuracy of road surface target recognition is improved.

The invention discloses an urban three-dimensional model data generation method, an urban three-dimensional model data generation device, urban three-dimensional model data generation equipment and a computer readable storage medium, and the method comprises the steps: carrying out the construction processing of a three-dimensional model based on obtained oblique photogrammetry data, and obtaining first urban three-dimensional model subdata; performing three-dimensional model construction processing outside the range of the oblique photogrammetry data based on the high-resolution satellite stereoscopic image to obtain second urban three-dimensional model sub-data; and performing edge matching processing on the first urban three-dimensional model sub-data and the second urban three-dimensional model sub-data based on a geometric continuity principle, a texture consistency principle and an attribute uniformity principle to obtain urban three-dimensional model data. Multi-source data are efficiently integrated, and global modeling precision and efficiency are improved.

The invention discloses a spatio-temporal interpolation neural network model and a spatio-temporal data modeling method based on the spatio-temporal interpolation neural network model, relates to the technical field of spatial interpolation, and aims to accurately model spatial dependence by introducing an embedded layer of spatial coordinates and a spatio-temporal basis function so as to establish a direct relation between DNN and Kriging spatial prediction. By means of a deep neural network structure, the model can automatically extract features in large-scale and dynamically-changing spatial data, and effectively identify a nonlinear relationship between spatial points, thereby realizing more accurate spatial interpolation. The method is not only suitable for non-linear prediction with covariables, but also can process non-Gaussian or non-stationary data, and greatly improves the applicability and robustness of the model. Besides, the deep learning model is excellent in performance on solving the local grid edge matching problem, the edge matching area can be smoothed, and the accuracy and reliability of gridding processing are improved.