1246 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 relates to the technical field of image analysis, in particular to a dispensing track optimization control system based on visual template conversion, which comprises a visual template analysis module, a contour point position correction module, a track vector generation module, a multi-parameter linkage feedback module and an optimal path planning module. According to the method, a boundary is extracted through clustering pixel superposition brightness and channel weight, a line segment frequency screening track is counted, feature stability and precision are enhanced through datum line construction, a deviation value is calculated through gradient direction segmentation boundary, a matching degree is improved through tangent point interpolation correction contour, and a weight factor is generated through included angle change and tool parameter normalization. A reference point is optimized through superposition increment, a path fusion tool attribute dynamic adaptation parameter is adopted, a multi-dimensional data fusion visual offset and floating weight real-time adjustment track is acquired, an execution point and an adjustment vector are superposed to calculate a distance matrix, an optimal path is screened through minimum distance and energy consumption, efficiency and consumption are both considered, and the system robustness and execution economical efficiency are remarkably improved.

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 relates to the technical field of image analysis, in particular to an automatic marking robot calibration method based on visual guidance, which comprises the following steps of: establishing an image set comprising different resolution levels based on operation site image data acquired by a marking robot, and performing corner detection and straight line segment detection on each level image in parallel. According to the method, through a parallel detection mechanism of a multi-resolution hierarchical image set, angular point and straight line segment features under different scales are synchronously extracted, and a multi-scale feature point set with high robustness is constructed in combination with cross-hierarchical coordinate stability measurement and response intensity quantification. And performing dynamic screening and grouping association on the feature points based on a preset geometric constraint condition, eliminating noise interference and false detection features, and generating a candidate calibration structure set with spatial consistency. Weighted contribution value fitting is adopted, cross-scale stability and detection confidence of feature points are integrated, and geometric accuracy and anti-interference capability of calibration reference point coordinates are improved.

The invention provides an automatic identification method and system for a linear structural plane in a complex rock mass outcrop, and belongs to the field of rock mass engineering, and the method comprises the steps: obtaining a DeepLabV3 + model of a rock mass outcrop image, carrying out the semantic segmentation of an input image, outputting a binary mask image of the trace pixel of the structural plane, and carrying out the topology reconstruction; establishing a mapping relation between the image coordinate system and the three-dimensional point cloud; calculating a space included angle between the direction vector of the trace and the average occurrence of the structural plane groups, classifying the three-dimensional point cloud data according to the structural plane groups according to an angle threshold value, and performing three-dimensional line segment extraction by adopting an improved iterative Hough transform algorithm; and realizing global multi-segment connection and trace length calculation of discrete segments based on a greedy algorithm. The method breaks through the limitation of a topographic region when the rock mass structural plane data is obtained through manual measurement, and improves the precision and efficiency of structural plane extraction in the complex rock mass.

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 method and a system for rapidly measuring cable force of a stay cable based on a digital image correlation method. The method comprises the following steps: acquiring video data of the stay cable; a line segment measurement calibration method is adopted, stay cable texture points serve as feature points, and a feature point selection mechanism is established; establishing a pixel-physical space coordinate mapping model based on a redundant observation method; model parameters are calculated through a collaborative calibration method; performing displacement measurement based on a digital image correlation method; establishing a double-layer feature extraction mechanism to complete local and global feature extraction; weight distribution of the local features and the global features is dynamically adjusted through a weight adaptive fusion strategy; and finally, establishing a double-layer tracking and failure recovery mechanism to complete hierarchical collaboration of coarse-grained global tracking and fine-grained local tracking. And carrying out fast Fourier transform on the dynamic displacement measurement result, and calculating to obtain the cable force. And reliable technical support is provided for non-contact accurate calculation and measurement of the cable force.

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.

A region detection device (1) according to the present disclosure includes a line segment detection unit (32) that detects a line segment from a captured image including an image of a target object having a linear band shape, a main line segment extraction unit (33) that extracts a main line segment (SL) that is a line segment having a length equal to or more than a predetermined value; a correction unit (34) that generates, as a corrected image, a rotated image obtained by rotating the captured image such that the main line segment (SL) is perpendicular or parallel to an arrangement direction of pixels in the captured image, and a region detection unit (35) that detects a target object region indicating the image of the target object from the corrected image.

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 provides a curvature-continuous AGV trajectory planning method and system, and relates to the technical field of trajectory planning. The method comprises the following steps: firstly, establishing a two-dimensional coordinate system taking a starting point as an original point, and acquiring a final position and angle information; based on the data, the system determines proper basic trajectory path types from a preset trajectory classification library, including straight lines, various curves and the like. Then, the basic track is segmented, and the basic track is divided into a combination of a straight line segment, a gradual change curve segment and an arc segment; and a track information packet containing complete attribute information is formed by calculating gradual change curve parameters and integrating all sections of routes. And finally, the system performs trafficability verification on the track to ensure that the finally generated track meets the movement requirement of the AGV. According to the method, the gradual change curve is introduced to serve as the transition section, and continuous and smooth change of the track curvature is achieved.

The invention discloses a method for constructing a computable road network. Road data in the vector map are extracted, line string data or line segments obtained by splitting the line string data are used as connecting edges, geographic feature codes containing Geohash information are given to starting points and ending points of the connecting edges, and therefore a basic road network map is constructed. And extracting a middle vertex set of the basic road network diagram and an edge attribute set of middle vertex connection edges, and carrying out road network vertex optimization based on edge attributes to obtain an optimized computable road network. Geographic feature codes adopted by the method comprise spatial geographic information and have the characteristics of graph vertex coding, and the constructed road network graph can be used for graph calculation and verification and restoration of road connection relations. Furthermore, in combination with a representation point acquisition scheme provided by the invention, a road network map fusing facilities and equipment can be constructed, so that the application range of the computable road network is expanded. The computable road network constructed by the method is high in operation efficiency and suitable for different production environments.

The present invention discloses a method and system for identifying dispensing defects based on machine vision. The method includes: fitting each first glue point contour point in a first glue point contour point set to obtain a first line segment and a second line segment, and fitting each second glue point contour point in a second glue point contour point set to obtain a third line segment and a fourth line segment, and determining whether a first degree of deviation between the first line segment and the third line segment, and a second degree of deviation between the second line segment and the fourth line segment, is greater than a preset threshold; if the first degree of deviation is not greater than the preset threshold, the first defect identification result of the first binary dispensing image and the second defect identification result of the second binary dispensing image are used as defect identification results for other binary dispensing images in a certain binary dispensing image set. The method can detect smaller local distortions as much as possible, thereby effectively improving the accuracy of subsequent defect identification result coverage and effectively increasing the speed of defect identification.

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 an engineering image-text cross-modal automatic reconstruction method based on a large model. For a gas path diagram of integrated circuit manufacturing equipment, firstly, all characters in the diagram are analyzed by adopting a PDF analysis method, and are written into a character analysis result file; and then identifying an image main region through a YOLOv5 training model, writing the image main region into a main region identification result file, identifying various devices through the YOLOv5 training model, and writing the devices into a device identification result file. And obtaining a main area of the engineering drawing through the coverage function, filtering out characters and devices in the main area, recognizing a straight line through an LSD algorithm, and writing the straight line into a straight line recognition result file. And integrating all the analysis result files to form an input analysis file of the engineering drawing multi-modal large model. Advanced technologies such as artificial intelligence, PDF analysis and line segment recognition are comprehensively applied, sensing and data analysis of IC manufacturing equipment gas path diagram information are achieved, and deep fusion and reconstruction of multi-source engineering information are achieved.

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 two-dimensional laser radar positioning method based on intersection point constraint, and belongs to the technical field of robot positioning. The method comprises the following steps: acquiring point cloud data of an indoor environment based on a two-dimensional laser radar; extracting straight line segments from the point cloud data by adopting a seed region growing method; based on a self-adaptive axis selection strategy of a line segment main extension direction, straight line segment category division is carried out, and a straight line matching relation of adjacent frames is established according to intersection point information of the straight line segment and a coordinate axis; and on the basis of the straight line matching relationship of adjacent frames, according to the distance residual error from the minimization point to the straight line of the Gaussian Newton equation, obtaining the pose information of the robot. According to a matching result, a Gaussian Newton method is used to minimize a distance residual error from a point to a straight line to solve a robot pose; the whole method is low in calculation time consumption, can still keep high efficiency under the high cloud density, is suitable for a low-power-consumption processor, and meets the requirements of an indoor robot for light weight and real-time performance.

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 the technical field of model section filling, in particular to a section filling method and system suitable for a triangular mesh model of a complex structure, and the method comprises the steps: S1, calculating directed line segments, intersecting with a section cutting plane, of a triangular patch of the model, and storing the directed line segments to a list ListE1, directed line segments corresponding to the inner contour and the outer contour of the model are opposite in direction; s2, the coordinates of directed line segments in the ListE1 are mapped to a two-dimensional plane coordinate system where a section cutting plane is located, and a list ListE2 is formed; s3, extracting a profile contour of the model from the list ListE2 and storing the profile contour to a list ListC based on the included angle, spacing and overlapping frequency information of directed line segments in the list ListE2; s4, determining the contour type of each profile contour in the list ListC, and associating the outer contour with the corresponding inner contour based on the contour space relationship; and S5, constructing a triangular mesh based on the associated inner contour and outer contour, and reversely mapping the triangular mesh to a three-dimensional space. According to the invention, automatic profile filling of a surface fitting or structure nesting complex model is realized.

The present invention relates to the technical field of chip detection and image processing, and discloses a method for detecting dense gold wires on the surface of a chip, comprising the following steps: 1. Read in the collected image of the dense gold wires on the surface of the chip, the detection area and the number of gold wires; 2. Divide the gold wires within the detection area into several segments, and fit each segment of the gold wire into a straight line segment; 3. Select a number of radial cross-sections at equal intervals in the area of each straight line segment, and use Gaussian curve fitting to obtain the position of the center point of each cross-section; 4. If the number of center points of the cross-sections is equal to the number of gold wires, assign the center points of the cross-sections to the point sequences corresponding to the straight line segments. If they are not equal, use the center points as spare points; 5. Perform linear fitting on all the point sequences on the same straight line segment; 6. Repeat steps 3 to 5 in other segmented areas of the detection area; 7. Connect all the fitted straight line segments into complete gold wires. The detection performance of the present invention is excellent, with strong robustness and good compatibility.

The invention relates to a DSM data extraction method based on a high-fidelity scene, and the method comprises the steps: obtaining a world coordinate range of the high-fidelity scene, carrying out the two-dimensional grid division of the high-fidelity scene, obtaining a grid coordinate and a grid index of each grid unit in the high-fidelity scene, and storing the grid coordinates and the grid index in an intermediate file File1; creating a line segment group perpendicular to the two-dimensional grid; the line segments in the line segment group are in one-to-one correspondence with the grid units; grid coordinates of the two-dimensional grids are converted into world coordinates of a high-fidelity scene, grid units are traversed in a simulation environment, vertical ray collision detection is sequentially carried out on ground object line segments corresponding to the grid units, and collision detection values are obtained; and storing the grid index and the collision detection value of each grid unit into an intermediate file File2, merging the intermediate file File1 and the intermediate file File2, and storing the merged intermediate file File1 and intermediate file File2 as a DSM data file in a fixed format.