1120 results about "Line segment" patented technology

The invention relates to the technical field of defect detection, in particular to a heat-conducting adhesive tape defect detection method and system based on machine vision, and the method comprises the following steps: obtaining a surface image of a heat-conducting adhesive tape, extracting a texture trend and marking an aggregation block, adjusting the trend and offset of a connecting line segment, and analyzing the angle change of a sideband node. And recognizing a skeleton trend reverse section and closing a boundary, and extracting a continuous direction changing region to obtain a defect structure image annotation layer. According to the method, the turning position in the sideband region is extracted by constructing the direction aggregation graph of the texture aggregation block, enhancing the direction identification of the direction of the regional texture, combining the grouping organization and coordinate offset processing of the line segment path, enhancing the continuous association of the image structure, and by means of the repeated distribution characteristic of the angle mutation node; and through a skeleton trend reverse paragraph and boundary closing mode, an identification range of a structure disturbance block is expanded, and coherent tracking and multi-level labeling of a structure abnormal region are completed by combining a spatial relationship between a contour trend difference and a turning point.

The invention discloses an abnormal detection method and system for a splayed anti-loosening line of a rail train, and relates to the technical field of rail traffic detection, and the method comprises the steps: image collection and processing: shooting an image of a fixed point region containing the anti-loosening line, and preprocessing the image to obtain a target image; line integrity judgment: extracting a bolt, a bolt marking line and an anti-loosening line through an analysis model to form a target area graph, and judging whether the anti-loosening line is complete or not according to line segment continuity and form; performing line deformation depth analysis, and synchronously obtaining the position of an anti-loosening line intersection point and deformation data through the model in combination with the loosening angle of the bolt marking line when the line deformation is complete; performing line deformation safety judgment, setting a safety threshold group based on historical data, and comparing deformation data to output a signal; after line deformation abnormity judgment and comparison signal receiving, actual data are compared with theoretical data output by the mechanical model, and abnormal or normal signals are output. The anti-loose line full-dimension high-precision detection is achieved, automation and real-time performance are improved, and train operation safety is guaranteed.

The invention discloses a photovoltaic cleaning control method fusing RTK positioning and visual compensation, and belongs to the technical field of photovoltaic module cleaning. According to the invention, through the RTK track points acquired offline, the least square method is combined with the RANSAC algorithm to carry out segmented straight line fitting, and the original points are projected to the corresponding straight lines to realize collinear correction, so that the measurement error is eliminated, and a continuous and collimated navigation path can be generated; edge lines (photovoltaic module grid lines) with geometrical characteristics in the environment are detected in real time through a visual sensor, the line segment direction is extracted through Hough transform, the line segment direction is compared with the target course calculated through RTK, course deviation is estimated, dynamic correction is conducted through a control strategy, and it can be ensured that the photovoltaic cleaning robot operates along the expected path with high precision; and on the basis of a lightweight YOLOv7 model, the photovoltaic panel is subjected to pollution category division and mapped to optimal water pressure and brush speed parameters, cleaning parameters are dynamically modified, and then cleaning strategy control is completed.

The invention discloses a geological map-oriented breakpoint repairing and closed curve reconstruction method and system and a medium. The method comprises the following steps of: preprocessing an original geological map to obtain a grayscale image; carrying out binarization and morphological closed operation processing to obtain a grayscale image of the edge of the smooth contour curve; performing pixel skeletonization to obtain a pixel-level skeleton diagram; performing secondary edge extraction, connected domain marking and endpoint statistics on the pixel-level skeleton diagram, and screening out a non-closed curve and an endpoint set; carrying out nearest neighbor retrieval by adopting KD-Tree to obtain a candidate pairing set of each end point; performing priority pairing in combination with the spatial distance and the direction smoothness; and generating a transition line segment according to a pairing result to supplement the fracture part of the non-closed curve. According to the method, non-closed breakpoints generated by scanning or drawing errors in the geological map can be automatically restored, and a closed curve with topological integrity and a smooth boundary is generated.

The invention belongs to the technical field of electric power engineering digitization and intelligent drawing auditing, and particularly relates to a dynamic rule engine and multi-target auditing task decomposition method oriented to electric power drawings. Obtaining a power rule file, analyzing and verifying to generate qualified rules, and screening the qualified rules to obtain an effective rule pool; the method comprises the following steps: reserving candidate areas by preprocessing an electric power engineering drawing, generating structured cells through line segment classification and combination and table detection, extracting and cleaning a text, and affiliating the text to the corresponding cells to form a structured result; screening candidate rules from the effective rule pool, extracting auditing objects from the structured result, generating auditing points, calculating the priority of the auditing points, and packaging the auditing points into an assignment unit set capable of being executed in parallel; on the basis of the dispatching unit set, optimizing task distribution by adopting a dynamic model and a greedy algorithm in an execution environment with the maximum concurrency, and doubly optimizing task execution by quantifying benefits and verifying rules; and performing rule judgment and result measurement on a task execution result.

The invention provides an effective room identification method, device and equipment and a storage medium, and the method comprises the steps: converting wall elements in an architectural plan into a line segment set, and carrying out the intersection detection and topology analysis to obtain an undirected weighted graph structure; determining an influence area in response to a user editing operation, and performing incremental updating on the influence area to obtain a locally updated graph structure; performing ring detection processing on the locally updated graph structure by applying a minimum ring basis algorithm to obtain a minimum ring basis containing a basic ring in the influence region; and identifying the effectiveness of the rings according to the geometric features and the topological features of each ring in the minimum ring basis, and identifying the effective rings as effective rooms. According to the method, through incremental updating and local processing, the calculation overhead of full-amount reconstruction is avoided, the calculation efficiency and real-time performance of room recognition are remarkably improved, and the method is suitable for interactive design scenes of large complex architectural planar graphs.

The invention discloses a wall surface identification method and device and a storage medium, and relates to the technical field of sensor positioning, and the method comprises the steps: carrying out the fitting processing of a laser radar point cloud collected by a laser point cloud radar, and obtaining a plurality of fitting line segments; screening a target line segment which is greater than a first length threshold and has the longest length from the plurality of fitting line segments; projecting target point clouds associated with the position of the target line segment in wall point clouds and obstacle point clouds collected by the depth camera on the target line segment, and determining at least one target wall surface line segment; and if the length of the target wall surface line segment is greater than a line segment threshold value, outputting the target wall surface line segment under a robot coordinate system to be used by a welting program. According to the invention, after laser point cloud filtering fitting, depth camera wall surface obstacle point cloud projection calibration is fused, the technical problem that the wall surface is difficult to effectively identify is solved, and the wall attaching precision and obstacle avoidance reliability of the cleaning robot in a complex scene are improved.

The invention discloses a method and system for positioning a panoramic camera in a point cloud map, and the method comprises the steps: carrying out the preprocessing of a panoramic image and three-dimensional point cloud map data, and obtaining two-dimensional line segment features and three-dimensional line segment features; based on the two-dimensional and three-dimensional line segment features, calculating two-dimensional and three-dimensional line segment main directions and comparing to obtain candidate rotation estimation; designing a two-dimensional distance function and a three-dimensional distance function based on candidate rotation estimation to evaluate the rough pose, designing a two-dimensional / three-dimensional line segment loss function to score the candidate pose, and screening out # imgabs0 candidate poses meeting requirements according to scores; and carrying out two-dimensional and three-dimensional key point extraction on the # imgabs1 # candidate pose, matching the two-dimensional key points with the three-dimensional key points, and carrying out further pose estimation on the candidate pose with the maximum matching quantity by adopting a PnP-RANSAC algorithm, so as to obtain final fine pose estimation. The method overcomes the defects that in the prior art, point feature detection is unstable and depends too much on an ideal static environment.

A method includes obtaining, using at least one processing device, image data associated with a scene. The method also includes identifying, using the at least one processing device, multiple line segments based on the image data. The method further includes identifying, using the at least one processing device, one or more boundaries around one or more objects detected in the image data. In addition, the method includes estimating, using the at least one processing device, a position of a vanishing point associated with the image data based on multiple collections of the line segments while excluding, from the multiple collections, one or more of the line segments that overlap with or that are included within the one or more boundaries.

The invention discloses a three-dimensional conversion method for a two-dimensional geological profile map, and the method comprises the steps: S100, data obtaining and preprocessing: obtaining an original geological profile map, carrying out the format conversion of the original geological profile map, eliminating overlapped line segments and micro short line segments, and maintaining the topological consistency; s200, conversion parameter calculation is conducted, specifically, drilling coordinates are obtained, and a conversion script is compiled based on the real geodetic coordinates, the two-dimensional profile map coordinates and the azimuth angle; and S300, conversion execution: reading the map subjected to format conversion in the S100 into three-dimensional modeling software, and executing the script language compiled in the S200 to obtain a three-dimensional geological profile map. According to the method, the whole file is converted, the conversion from the two-dimensional geological prospecting line section to the three-dimensional geological section map can be rapidly and integrally completed through the existing software technology and simple script codes so as to be used for three-dimensional geological modeling, a large amount of manpower and material resources can be effectively saved, and the production efficiency can be improved.

The invention relates to a circuit diagram-to-netlist generation method and system based on deep learning and a product. The circuit diagram-to-netlist generation method comprises the following steps: S1, identifying devices in a circuit diagram through a YOLOv8 model to obtain position information and category of each device; identifying a straight line segment in the circuit diagram through a probabilistic Hough transform algorithm to obtain a starting point coordinate, an end point coordinate and an orientation corresponding to the straight line segment; and S2, generating corresponding text description information according to the position information, the category, the starting point coordinate, the end point coordinate and the orientation. According to the method, by effectively integrating multi-modal information and combining image and text data, comprehensive understanding of a circuit diagram is provided, the recognition accuracy and robustness are improved, even if a single component has a recognition error, the influence of noise on the whole model can still be reduced through final information fusion, and the recognition accuracy and robustness are improved. Therefore, misjudgment and missed judgment in recognition are reduced, and the recognition accuracy of the element and the connection relation is remarkably improved.

The invention discloses a GIS-based cross-section diagram real-time synchronous display method and system, and relates to the technical field of geological modeling, and the method comprises the steps: importing multi-source heterogeneous geographic data, carrying out the standardized preprocessing, and generating a geographic information data set in a unified format; carrying out multi-dimensional feature extraction on the geographic information data set by adopting a feature level fusion algorithm, and constructing a multi-dimensional geographic feature model fusing geological structure, terrain elevation and earth surface coverage information; performing data optimization by adopting a spatial interpolation algorithm based on the multi-dimensional geographic feature model to generate a continuous geographic surface model; and performing parallel contour tracking and topological sorting on the discrete section line segment set, and generating a user-defined section diagram supporting interactive parameter adjustment in real time. According to the method, the multi-dimensional geographic feature model is constructed through the feature level fusion algorithm, semantic level association of the geologic structure, the terrain elevation and the earth surface coverage information is realized, the problem of pixel level fusion is solved, and the data space consistency error is reduced.

The invention relates to the technical field of stage mechanical device motion track planning and safety anti-collision, and particularly discloses a stage mechanical device motion track planning and safety anti-collision control method. Comprising the steps of dynamic environment map generation, elastic time window distribution, dynamic priority generation, collision avoidance strategy generation, motion control instruction output and optimal control parameter multiplexing. Multi-source sensor data are acquired and fused to generate a dynamic environment map containing object positions and motion trends, then a predetermined path is decomposed into a line segment sequence and an elastic time window is distributed, then a dynamic priority is generated, and then a line segment sequence space-time crossing risk is detected and a collision avoidance strategy is generated. A motion control instruction is output according to the strategy, and finally optimization control parameters are extracted and reused; according to the method, an elastic time window and a dynamic priority are introduced, and a virtual buffer domain and a self-learning mechanism are combined, so that the parallel working efficiency of multiple devices, the stage scene conversion fluency and the operation safety are improved.

The invention discloses a camera parameter calibration method and device, a computer readable storage medium and a vehicle, and the method comprises the steps: collecting a checkerboard image shot by at least one camera, and extracting a line contour in the checkerboard image based on an edge detection algorithm; in the line contour, detecting a straight line segment based on Hough transformation or an LSD algorithm, and fitting the straight line segment based on a least square method; determining an internal reference matrix and a distortion coefficient of the camera based on the fitted straight line segment and a nonlinear optimization algorithm; and determining a rotation matrix and a translation vector of the camera based on the straight line segment, the internal reference matrix and the distortion coefficient. According to the method, the robustness of parameter calibration in a calibration field aging, fouling or reflective scene can be improved, the success rate, the automation degree and the efficiency of the calibration process are improved, and the driving safety of a user is improved.

The invention discloses a three-dimensional Gaussian splashing method and system for sparse view curve reconstruction, and the method reconstructs a three-dimensional curve scene through a sparse image: firstly, obtaining a dense point cloud and a camera pose, extracting a two-dimensional line segment graph, employing a line segment guide Gaussian initialization strategy, and obtaining a three-dimensional curve scene; generating an initial Gaussian set on the basis of the dense point cloud and the two-dimensional line segment graph; structure perception Gaussian pruning is executed in the optimization process of the initial Gaussian set, and spatial outliers and visibility redundant gauss are removed; and finally, calculating the total loss containing sparse regular terms through the difference between the rendered image and the sparse image, and iteratively optimizing Gaussian parameters until the total loss converges, thereby obtaining a final three-dimensional curve reconstruction result. According to the method, the problem of geometric prior deficiency under a sparse view is solved through line segment guide initialization, overfitting and artifacts are effectively inhibited by using structure pruning and sparse constraint, and high-quality three-dimensional curve reconstruction is realized.

The invention discloses an automatic verification method and system for a topological relation of ocean charting data, and relates to the technical field of charting verification, and the method comprises the steps: obtaining a chart vector element, splitting a broken line into a line segment unit according to a node, splitting a surface domain into a ring domain unit according to an outer ring and an inner hole, and extracting a control point; constructing fractal spectrums for the line segment units based on a multi-resolution box dimension method, comparing the fractal spectrums with normal spectrums, and marking complexity abnormal sections; constructing a polymorphic behavior matrix according to predefined geometric expectation and semantic rules, analyzing conflicts, and identifying topology anomalies; a tide level field is obtained, a coupling constraint field is constructed in combination with equal-depth closed loop hierarchical nesting, and tide depth coupling abnormity of a channel boundary and a closed loop is verified; a lighthouse, a navigation mark and a tide level station control point are screened, and connectivity abnormity is verified according to a semantic rule; and summarizing to generate a verification report. Fractal analysis, a semantic matrix, isodepth coupling and a communication rule are combined, break point errors are accurately distinguished, topological anomaly is detected in a fusion mode, and the time-space consistency of a sea chart and the connectivity of control points are guaranteed.

The invention relates to the technical field of pattern design intelligent optimization, in particular to an embroidery pattern optimization design method and system based on a machine learning model.The method comprises the following steps that a grey-scale map structure is obtained, edges are extracted to construct a direction node map, node intersection points are positioned to generate path vectors, boundaries are drawn according to the symmetrical relation to generate annotation map blocks, and the annotation map blocks are obtained. Establishing a pattern code generation structure label group, and extracting a repeated paragraph classification style to generate a style training sample label set; according to the method, a composition node map is constructed through the direction continuity of edge pixel points, path candidate intersection points are positioned through the intensity of node space distribution and are connected into skeleton path line segments, an edge structure closed area is extracted by using a path symmetric projection relation, and ordered association of a pattern structure and a pattern is realized. The pattern design process has the capabilities of being controllable in structure, adjustable in style and traceable in feature, and the intelligent level of composition processing and style induction is remarkably improved.

The invention relates to a wall recognition modeling method based on a two-dimensional CAD drawing, belongs to the technical field of data modeling, and solves the problem that a closed single-line wall cannot be automatically and accurately generated from the two-dimensional CAD drawing in the prior art. Comprising the following steps: extracting a straight line segment set of all walls from a two-dimensional CAD drawing; calculating a wall continuity index value of the straight line segment set according to a first matching condition, and obtaining a segment grouping set by adopting a corresponding wall line grouping method; based on the line segment grouping set, multiple wall body center lines are generated through fitting according to the distance and the line segment direction; the method comprises the steps of identifying suspended endpoints in a plurality of wall body center lines, obtaining corresponding target intersection points according to other wall body center lines and endpoints in a region adjacent to each suspended endpoint, adjusting the corresponding suspended endpoints according to the target intersection points, and cutting and reconstructing the wall body center lines where the target intersection points are located to obtain optimized wall body center lines. And then a single-line wall body is constructed. The closed single-line wall is automatically and accurately generated.

The invention discloses a method for automatically correcting radial distortion of a wide-angle lens, and relates to the technical field of computer vision and image processing, and the method comprises the steps: collecting an original image, calculating the distance from a pixel to an imaging principal point, and extracting a multi-scale image and edge features; analyzing the edge direction and radial change and linear extension of the structure, extracting a linear structure candidate region, obtaining a distortion compensation parameter, generating a multi-scale candidate linear parameter set, and calculating a multi-scale linear consistency index for adaptive adjustment; extracting a point set from the candidate straight line parameter set, executing forward and reverse mapping to calculate a dual-space consistency index, and optimizing local parameters and the point set; calculating a minimum linear complexity index based on the line segment curvature, the curvature change rate and the length, and implementing local optimization; and performing weighted fusion on each index to construct a comprehensive objective function, performing step-by-step shrinkage optimization to obtain an optimal compensation parameter, performing global geometric correction on an original image, generating a distortion correction image, and realizing improvement of the structure recognition precision and the geometric correction effect.

A system configured to rearrange and distribute data of an incoming image for processing by a number, K≥4, of processing clusters. The incoming image has a number of scanlines, each scanline being arrangeable as a plurality of data units. The system is configured to logically partition the incoming image into K uniform regions corresponding to the number of processing clusters, wherein the K regions are defined by a number, R≥2, of rows and a number, C≥2, of columns, by i) dividing each scanline into a number, C≥2, of uniform line segments, the length of a line segment being equal to the width of a region, ii) dividing each line segment into a number, W≥2, of data units, each having a number, Q≥2, of bytes, i.e. Q-byte data units, and iii) defining a region height of a number, H≥2, of scanlines for each region. The system is configured to store, in an associated memory, data units from different regions interleaved with respect to each other, while consecutive data units of each line segment of each row of regions of the incoming image are stored with an offset of K memory positions such that the consecutive data units are stored K memory addresses apart. The system is configured to transpose each assembly of K number of Q-byte data units stored in said memory into a transposed assembly of Q number of K-byte words, each K-byte word including one byte per cluster, and transfer the bytes of each K-byte word to said processing clusters in parallel, one byte per cluster.

The invention provides a three-dimensional path planning method and system for a safe track of an unmanned aerial vehicle, and relates to the technical field of intelligent control, and the method comprises the steps: generating a new expansion node coordinate containing wind field compensation through combining a sampling node direction vector, a current adaptive step length and a wind drift compensation amount; the method comprises the following steps: performing three-dimensional spherical collision inspection on a new expansion node according to an unmanned aerial vehicle envelope radius; if yes, performing voxelization ray collision detection on a line segment from the nearest node to the new extension node to obtain a collision detection result; and periodically counting collision detection results, dynamically adjusting the step length by adopting a PID optimization algorithm based on a historical collision rate, inputting the collision rate into a PID controller, outputting a step length adjustment coefficient, multiplying the current step length by the adjustment coefficient to obtain a new step length, and constraining the new step length in a preset proportion interval of the heuristic initial step length. According to the invention, intelligent path planning can be realized.

The invention provides an optical proximity correction method and related equipment. The method comprises the following steps: identifying a target sideline from a to-be-processed initial pattern; the initial pattern is a pattern in a design layout of the semiconductor device; performing fairing processing on the target sideline to obtain a to-be-Manhattan line segment; performing Manhattan processing on the to-be-Manhattan line segment to obtain a to-be-corrected line segment; and performing optical proximity correction on the line segment to be corrected, and constructing a target pattern corresponding to the initial pattern. According to the method disclosed by the invention, the pattern after Manhattan processing is prevented from being too complicated and containing unnecessary fine structures, the simplicity and the effectiveness of the pattern after Manhattan processing are ensured, the final mask design can be simpler, and the possible problems in the subsequent manufacturing process are also reduced.

The invention relates to the technical field of computer graphics, in particular to a three-dimensional geological section real-time cutting method and system and a storage medium, and the method comprises the steps: constructing a BVH tree to accelerate the cutting of a three-dimensional geological model, and calculating the projection of intersecting line segments on a cutting surface two-dimensional coordinate system to obtain a projection line segment set; constructing an undirected graph structure based on the projection line segment set; and extracting a closed profile contour based on the undirected graph structure, subdividing a triangular grid, and rendering and displaying. The implementation of the scheme can break through the traditional preprocessing dependence, and improve the profile generation efficiency and the visualization integrity.

The invention relates to the technical field of power transmission line inspection, and discloses a power transmission line unmanned aerial vehicle autonomous inspection path planning method and system, and the method comprises the steps: scanning a power transmission line corridor through a laser radar to obtain three-dimensional point cloud data, and constructing a three-dimensional entity model of the power transmission line corridor; taking a lead between adjacent towers as a line section, and calculating a risk thermal value of each line section; generating a tower inspection sequence list according to the risk thermodynamic value; according to the three-dimensional entity model and the inspection sequence list, generating a surrounding waypoint set for each tower, and generating a single inspection path of the tower; according to the tower inspection sequence list, transition paths between adjacent sequence towers are generated, and global inspection paths of the towers are obtained; and obtaining a final inspection path according to the single inspection path and the global inspection path. According to the scheme, the unmanned aerial vehicle can preferentially inspect the high-risk area, the flight path better fits the actual line form, and the whole-line inspection efficiency and safety are improved.

The invention provides a U-shaped station pose recognition method and system based on laser point cloud and LSD, and relates to the technical field of AGV pose recognition, and the method comprises the steps: obtaining 2D laser point cloud data of a U-shaped station through an obstacle avoidance laser radar configured by an AGV, and carrying out the preprocessing; performing line segment detection on the 2D laser point cloud data by adopting an LSD algorithm to form a candidate line segment set; screening the candidate line segment set according to geometric constraint conditions, and determining U-shaped structure line segments; calculating pose parameters based on the U-shaped structure line segments; on the basis of the dynamic deviation, the pose parameters are adjusted through a Kalman filtering optimization algorithm and a dynamic updating mechanism, and the final pose parameters are output to a navigation control system, so that the characteristics of the U-shaped station can be extracted from the laser point cloud through an LSD algorithm, accurate pose recognition without auxiliary marking is realized, the dynamic deviation of the station is adapted, and the positioning accuracy is improved. The automation level and the production efficiency of the AGV are improved, and the pose recognition precision and stability are improved.

The application discloses a discrete fracture network generation method based on an iterative function system, which comprises the following steps: generating a traditional discrete fracture network model according to set parameters; then, converting all line segments into multi-segment lines with different directions and shapes at random; converting the multi-segment lines into fractal curves representing fractures by using an iterative function system; then, smoothing the fractal curves by using a curve smoothing algorithm and exporting the processed model into a geometric file, such as a dxf format file; realizing intersection operation between the curves by using software or code; setting an error value to detect small lines and gaps, deleting the short lines, merging small gaps into a point, and merging points close to the boundary; and finally, carrying out mesh division on the model. Compared with the traditional discrete fracture network model, the application can generate fractal curves representing fractal fractures, can control the roughness degree of the fractures through relevant parameters, can more accurately describe the fractures, and can improve the efficiency and precision of numerical simulation.

The invention relates to a virtual three-dimensional model rapid construction method and device, and relates to the technical field of three-dimensional modeling, and the method comprises the steps: obtaining three-dimensional model data information; contour edge extraction is carried out on the three-dimensional model, and the extracted contour edge is stored in an edges array; carrying out self-intersection calculation on the contour edges in the edges array, storing line segments after the self-intersection calculation into an outputEdges array, and storing the vertexes of the line segments into an outputPoints array; constructing a half-edge data structure, and extracting an outer contour line of the three-dimensional model through the half-edge data structure on the basis of the outputPoints array and the outputEdges array; generating a virtual three-dimensional model based on the extracted outer contour line; and carrying out visual display on the virtual three-dimensional model. The invention provides a segmented spatial indexing method, line-line segmentation is quickly realized, and the method is suitable for sparse and dense line segment distribution.

The invention discloses a video infringement detection method, medium and system based on slope constraint, and the method comprises the steps: obtaining a to-be-detected inter-frame similarity image, and inputting the to-be-detected inter-frame similarity image into a pre-trained line segment detection model, a line segment detection result corresponding to the inter-frame similarity image to be detected is output through the line segment detection model, and a loss function of the line segment detection model comprises a slope penalty coefficient; analyzing the line segment detection result to obtain video infringement segment position information corresponding to the to-be-detected frame; the convergence speed in the model training process can be effectively improved, and the time consumed by model training is saved; meanwhile, the accuracy of a final detection result is improved.

The invention discloses a plane target contour reconstruction method and device suitable for geographic information data processing, which are used for recovering the contour shape of a target geographic element from a disordered discrete point set, and comprises the following steps: obtaining a plane discrete point set representing the target geographic element, the plane discrete point set being disordered coordinate data; the plane discrete point set is processed, the plane discrete point set is structured into a group of line segment sets representing local contour features of the plane discrete point set through iterative splitting and merging operation based on an elliptic model, and the splitting and merging operation is controlled by a linearity threshold value and a disconnected connectivity threshold value which are generated in a self-adaptive mode; processing the line segment set, and integrating the line segment set into closed polygon contour data representing the target geographic element by establishing a spatial index for end points of the line segment set and executing nearest neighbor connection; and outputting closed polygon contour data. According to the method and the device, the accuracy and the automation degree of contour reconstruction and the robustness of an algorithm are improved.

The invention provides an end face burr defect detection method suitable for pole piece slitting, and the method comprises the steps: obtaining a collection image of a to-be-detected pole piece slitting end face, extracting an actual foil in the collection image, and generating a skeleton line sub-pixel contour line segment of the actual foil; combining adjacent sub-pixel contour line segments at the fracture into one segment, and fitting into a straight line segment; and according to the straight line segment and the height of the foil, a virtual foil is obtained, the protruding contour of the actual foil protruding out of the virtual foil at the fracture is determined, and a burr defect identification result is generated in combination with a preset burr threshold value. The technical problem that in the prior art, the detection efficiency of pole piece slitting end face burr defects is low is effectively solved.