58 results about "Minimum bounding box" patented technology

The invention discloses a high-precision plane fitting method for a multi-noise point cloud, and the method comprises the steps: carrying out the plane rough fitting of an original point cloud after down-sampling, taking the longest side of a minimum bounding box of a lower sampling point cloud as a distance threshold value, and calculating the distance weight of each point through a weight mathematical model, then, plane fine fitting is carried out on the weighted down-sampling point cloud, the distance weight of each point is updated after each fitting, plane fitting is carried out on the point cloud of which the weight is updated again, and a fine fitting plane of the down-sampling point cloud is calculated in an iterative manner; and finally, calculating the distance weight of each point in the original point cloud based on the fine fitting plane and the iterated distance threshold value, performing plane fitting on the weighted original point cloud in an iteration mode, and finally obtaining the fine fitting plane of the original point cloud. According to the technical scheme, the method is high in stability and low in calculation amount, can obtain a high-precision fitting plane in a weighted iteration mode under the condition of more noise, and is suitable for different types of point cloud data.

The invention discloses a man-machine interaction method, device and equipment based on an aircraft unstructured grid and a storage medium, and relates to the technical field of fluid mechanics, and the method comprises the steps: constructing a current directed bounding box as a root node based on a to-be-processed unstructured grid of an aircraft, equally dividing the current directed bounding box into a plurality of sub-bounding boxes from the root node, binding the sub-bounding boxes with sub-nodes of the root node, and carrying out layer-by-layer iteration until a preset hierarchy threshold value is reached to obtain a target space segmentation structure; determining a minimum bounding box of each interaction object in the generated interaction object grid set, performing intersection detection on the minimum bounding box and each node in the target space segmentation structure, and storing data of the interaction objects to a bottom leaf node; the capture state identifier is set by judging whether the interaction object data is stored in each bottom-layer leaf node, and collision detection with the bounding box of each bottom-layer leaf node provided with the capture state identifier is performed in the interaction range of the interaction instruction to obtain the target interaction object, so that the man-machine interaction efficiency is improved.

The invention discloses a neighbor soft package two-dimensional segmentation and three-dimensional positioning combined method, which comprises the following steps of: segmenting a two-dimensional picture by using a Segment Anything algorithm and carrying out preliminary screening according to the contour area of a segmented object; performing coordinate range screening, determining and calculating an external rectangle and an area thereof through processing of a two-dimensional minimum compact bounding box, and outputting a minimum area by rotating a line to be greater than 90 degrees; obtaining an included angle between an object center coordinate and x and y through a bounding box, calculating a result through a formula, and performing range screening to segment a recognition object; processing the soft package by using a two-dimensional minimum bounding box algorithm to obtain a center coordinate and an included angle; acquiring internal and external parameter matrixes, two-dimensional coordinates and depth of the camera, and converting two-dimensional image coordinates into three-dimensional coordinates in a camera coordinate system and a world coordinate system; and calculating a neighbor point cloud normal vector to obtain a three-dimensional attitude of the soft package center point. According to the positioning method disclosed by the invention, the problem of low positioning precision of the soft package is solved by a minimum compact bounding box algorithm, and a more accurate grabbing pose is conveniently provided for the robot.

The invention discloses a point cloud intersection-based space target optical segmental arc rapid association method. The method comprises the following steps: 1, acquiring optical segmental arc data and constructing a constraint admissible domain; 2, generating a track point cloud; 3, forecasting parallel orbit point cloud; 4, fast point cloud intersection is carried out; and 5, determining an initial orbit based on point cloud intersection. Through the above process, the space target rapid segmental arc correlation method based on point cloud intersection is provided, an admissible domain is constructed by two optical observation segmental arcs and orbit point clouds are generated, and then the point clouds of the two segmental arcs are forecasted to the same moment through a parallel orbit point cloud forecasting technology. Quickly locking an overlapping region of the two point clouds by adopting a minimum bounding box method, and judging the relevance between the point clouds through a mahalanobis distance; and finally, based on the Bayesian estimation principle, carrying out initial orbit determination on the successfully associated arc segments.

The invention provides an object segmentation method based on multimodal data fusion and an image annotation tool. The method includes acquiring an initial RGB image, an initial infrared image, and an initial depth image that contain an object; aligning the initial RGB image, the initial infrared image, and the initial depth image to obtain a first RGB image, a first infrared image, and a first depth image; specifying an initial prompt point in the first RGB image, and acquiring first masks characterizing an object region from the images in different modalities; fusing pixel values of the images in different modalities based on the first masks of the first RGB image, the first infrared image, and the first depth image to obtain a second mask; and determining a minimum bounding box of the object, and calibrating the minimum bounding box to obtain a segmentation result of the object.

The invention provides an object contour minimum bounding box generation method and device, a storage medium and equipment, and is applied to the technical field of computers. The method comprises the following steps: screening out a maximum distance point and an angular point of a target point cloud cluster, and determining a pre-selected long edge of the target point cloud cluster; performing linear fitting on at least one long side point cloud in the target point cloud cluster, wherein the linear distance between the long side point cloud and the pre-selected long side point cloud is within a preset distance threshold value to obtain a course angle; and according to a rotation matrix constructed by the course angle, carrying out translation and rotation transformation on the target point cloud cluster, then calculating the contour size and the center point of the point cloud cluster, and generating an object contour minimum bounding box of the target point cloud cluster. The method determines the pre-selected long edge by screening the maximum distance point and the angular point, improves the course angle precision by combining the threshold filtering point cloud and straight line fitting, and performs coordinate transformation on the point cloud based on the rotation matrix to generate the minimum bounding box closely fitting the object contour, thereby improving the course detection and bounding box precision, and improving the course detection precision. And more reliable environment information is provided for intelligent driving perception.

The invention provides a polygon clipping processing method based on GPU acceleration, comprising the following steps: forming a minimum frame: reading the shape of a to-be-processed graph to form the minimum frame surrounding the to-be-processed graph, the minimum frame having a plurality of extreme points; the center of a first segmented grid is determined according to one of the extreme points, the segmented grid is a regular polygon, coordinates of all vertexes of the first segmented grid are obtained through calculation according to the center of the first segmented grid, other segmented grids are formed according to center coordinate deviation of the first segmented grid, and the center of the first segmented grid is a regular polygon; the minimum frame is completely covered by the segmentation grids; and kernel clipping: grouping the segmentation grids, performing parallel processing on each group of segmentation grids by using a GPU calculation unit so as to clip each group of segmentation grids edge by edge, and reserving vertexes of the segmentation grids in the to-be-processed graph and intersection points formed by the outer contour of the segmentation grids and the outer contour of the to-be-processed graph.

The present application discloses an ambient occlusion processing method, device and equipment, which relates to the field of game light and shadow processing technology, and can solve the current technical problem that the computing pressure of the server is increased and the user's gaming experience is easily affected when performing ambient occlusion processing. It includes: obtaining a target model unit of a target virtual object, the target model unit is a model unit to be processed for ambient occlusion, and the target model unit is provided with a minimum bounding box; obtaining a target three-dimensional texture corresponding to the target model unit, the target three-dimensional texture is a pre-baked three-dimensional texture of the target model unit, and the size of the target three-dimensional texture is related to the minimum bounding box size of the target model unit; obtaining a target cube model of the target model unit, the target cube model is used to render the target three-dimensional texture, and the size of the target cube model is the same as the size of the target three-dimensional texture; according to the target cube model and the target three-dimensional texture, the ambient occlusion effect of the target model unit is rendered.

The present invention discloses a quasi-minimum volume bounding box optimization method for a three-dimensional point set of an inclined mold, comprising the following steps: S1, based on the principle that a convex multi-deformation in two-dimensional space and a minimum enclosing rectangle must be collinear, the concept of a minimum volume constant coefficient is introduced, and a rotation axis calculation model for a quasi-minimum bounding box of a three-dimensional model is established using a linear space principle; S2, based on vertex area weighting and model detail feature evaluation, a two-dimensional projection vertex weight mathematical model is established; S3, the bounding box accuracy λ is set, a preliminary projection plane YOZ is determined based on the synchronization of the X axis based on the rotation axis calculation model, a covariance matrix model is constructed based on the two-dimensional projection vertex weight mathematical model and the projection vertex set, and then the vertex projection basis is solved, the Y and Z axes are synchronized, and the AABB algorithm is called to calculate the volume of the bounding box; S4, the Y and Z axes are used as the rotation axes to calculate the model synchronization object and S3 is iteratively repeated, thereby obtaining a quasi-minimum volume bounding box; the present invention achieves a reduction in bounding box solution time and an improvement in fitting rate.

The application discloses a kind of based on foreground perception's no ROI marking medical image classification method, comprising: the pre-processing of three-dimensional medical image data, obtain standardized three-dimensional image data;In the condition of no ROI marking, based on pixel intensity distribution and spatial connection relationship, self-adapting foreground mask is constructed and three-dimensional minimum bounding box is determined;Accordingly, the foreground three-dimensional image data is obtained by cutting;It is input three-dimensional convolutional neural network to extract three-dimensional convolutional feature, after channel attention weighting and multi-layer semantic feature fusion, input full connection layer and output the class probability of corresponding preset classification category by Softmax function.The application can automatically obtain foreground area without artificial ROI marking, reduce redundant background interference, and improve image classification accuracy and stability through three-dimensional convolution, channel attention and multi-layer semantic fusion.

The present invention discloses an element position adaptation method, medium, device and system, wherein the method includes: obtaining first size information of an original first canvas, second size information of a second canvas after a proportion change, and minimum bounding box information of a first element in the first canvas; determining a scaling ratio according to the first size information and the second size information, and determining the size of a second element in the second canvas according to the scaling ratio; calculating relative position information between the first element and the first canvas according to the minimum bounding box information of the first element, and calculating final position information of the second element in the second canvas according to the relative position information, so as to complete position adaptation of the second element after the canvas proportion changes; and being able to automatically adapt the elements in the canvas after the canvas proportion changes, so that the visual effects of the elements are consistent after the canvas proportion changes.

The application discloses a kind of based on robot scanning viewpoint planning process product three-dimensional measurement method and device, the method comprises: the size information of measured object is acquired, the minimum bounding box is determined according to size information, scanning viewpoint is planned according to the minimum bounding box, and coarse grid model is generated based on scanning viewpoint;Coarse grid model is discretized into point cloud model, and the hole recognition of point cloud model is carried out using maximum angle criterion, and the hole boundary feature point is obtained, the clustering of hole boundary feature point is carried out, and the local hole in point cloud model is determined, and the secondary fine scanning of each local hole is carried out, and secondary fine scanning model is generated;Point cloud registration and fusion are carried out to coarse grid model and secondary fine scanning model, and the digitization model of measured object is obtained, the integrity, precision and efficiency of scanning can be guaranteed, and the automatic measurement of process product is realized.

The invention relates to the field of electric power, and discloses a substation control equipment terminal strip drawing identification method, device and equipment, and the method is used for converting a terminal strip drawing into a standardized intermediate file. The method comprises the following steps: acquiring an electronic image of a terminal block drawing, and analyzing and identifying space coordinates of connection points, space coordinates of connection lines, line types, line widths and space coordinates of short circuit symbols; identifying and extracting a plurality of character sequences and corresponding minimum bounding box coordinates; establishing a semantic binding relationship between the connection points and the character sequence based on the spatial coordinates, determining a spatial proximity relationship of the connection points in combination with a terminal arrangement rule, and identifying a short-circuit relationship based on the proximity relationship and the spatial coordinates of the short-circuit symbols; integrating the space coordinates, the line types and the line widths of the connecting lines, the space coordinates of the connecting points, the semantic binding relation and the short-circuit relation, and constructing a topological relation graph; elements and loops in the atlas are classified based on a power industry coding rule base, and are converted into a standardized intermediate file in combination with an engineering modeling rule;

The invention belongs to the technical field of fabricated building design, and particularly relates to a BIM-based component collision analysis method and system in large-span steel arch construction, and collision judgment is systematically performed on a target component and remaining steel arch components by adopting a collision analysis process based on a minimum bounding box method. A bounding box parallel to a coordinate axis is constructed, according to component coordinate range comparison, collision risks are quickly and accurately recognized, collision and non-collision results are automatically generated, collision avoidance analysis is innovatively performed from the two aspects of direction and distance by accurately obtaining collision overlapping areas and intersection points according to the collision results, and the collision avoidance accuracy is improved. The avoidance angle and the translation distance are determined, detailed avoidance information is generated, accurate guidance is provided for construction adjustment, the collision risk is reduced, and smooth construction is guaranteed.

Embodiments of the present application provide a large gantry type identification method and device based on 3D vision, which comprises: acquiring a point cloud set of the upper surface features of a workpiece moving at a constant speed through a 3D camera; filtering out background point clouds in the point cloud set to obtain preliminary extracted point clouds; through statistical filtering, removing random noise points distributed globally from the preliminary extracted point clouds, and then through clustering segmentation, eliminating invalid point cloud clusters, and obtaining pure point clouds; calculating the minimum bounding box of the pure point clouds, and determining the main direction of the workpiece and establishing a workpiece coordinate system; in the constructed workpiece coordinate system, performing feature calculation on the workpiece; comparing the results of the feature calculation with a pre-stored all-gantry-type-feature database, and outputting the gantry type according to the comparison result. Through complete point cloud reconstruction, multi-feature fusion identification, size and structure double verification, and man-machine collaborative error correction mechanism, high-precision, high-flexibility and high-robustness automatic identification of large gantry types is realized.

The present invention provides a three-dimensional model scene rendering method, which includes: creating a hierarchical bounding volume hierarchy (BVH) structure tree; extracting model data to obtain all model component objects; traversing all building component objects, creating a minimum bounding box for each building component object, organizing and arranging the minimum bounding boxes with the same component type together and creating a new minimum bounding box to enclose them until all components in the scene are within a large minimum bounding circle; using a frustum culling algorithm to eliminate invalid components, and performing three-dimensional engine rendering on the BVH tree after component culling. The method of the present invention greatly improves the rendering efficiency of the three-dimensional engine for models, and effectively enhances the user experience during the use of the three-dimensional platform.

The invention discloses a control method, system, equipment and medium for carrying satellite components, and the method comprises the steps: obtaining a carrying instruction which comprises the number of the components, size data, an initial position and a target position, and generating minimum bounding rectangular box data according to the size data; inputting the minimum surrounding rectangular box data, the initial position and the target position corresponding to the to-be-carried assembly into a pre-trained path generation algorithm to obtain an initial carrying path corresponding to the to-be-carried assembly; the robot moves the to-be-carried assembly from the initial position to the target position according to the initial carrying path, point cloud data of the surrounding environment is obtained in real time in the carrying process, the safe distance on the carrying path is kept through calculation, if the safe distance is insufficient, the path is recalculated and planned, and then the to-be-carried assembly is moved to the target position from the initial position. The method has the advantages of being high in implementation degree, good in adaptability, reliable in safety and easy to integrate in a batch production line.

The embodiment of the invention provides a temporal joint observation method and system, and relates to the technical field of medical imaging, and the temporal joint observation method specifically comprises the steps: obtaining a to-be-detected scanning image, and obtaining a segmentation diagram corresponding to a target jaw bone according to the to-be-detected scanning image; the minimum bounding box of the mandibular condyle process in the target jaw bone is determined according to the segmentation schematic diagram, a target jaw joint reference line is constructed through the minimum bounding box and a preset coordinate system, the temporal joint is observed through the target jaw joint reference line, and the plane where the target jaw joint reference line is located is perpendicular to the plane where the temporal joint is located. Based on this, according to the observation method provided by the invention, the new observation plane is generated based on the minimum bounding box of the inferior zygopophysis, so that the observation plane is more perpendicular to the area needing to be observed, the limitation of the shooting body position of a patient in the prior art is overcome, the cross curve of the temporal joint is automatically generated, and the formed section is more beneficial to observation of the condition of the temporal joint; and meanwhile, the manual operation time is shortened.

To address the shortcomings of existing methods for detecting surface texture defects in complex curved parts, such as low detection efficiency, poor stability and recognition, and difficulty in rapidly and accurately quantitatively characterizing sub-millimeter-level surface texture defects in three dimensions, this invention provides a rapid three-dimensional quantitative characterization method for surface defects in curved parts. This invention utilizes a light field camera to simultaneously acquire two-dimensional images and three-dimensional point cloud data, improving the consistency and stability of subsequent three-dimensional quantitative characterization of defects. It employs a deep learning semantic segmentation model to extract two-dimensional contour information of defects, providing precise semantic guidance for subsequent three-dimensional spatial mapping. It establishes a coordinate mapping relationship between pixels in the two-dimensional image and physical points in the three-dimensional point cloud coordinate system, enabling precise selection of subsets of the defect's three-dimensional point cloud. Finally, it uses principal component analysis (PCA) to establish a local coordinate system, and within this coordinate system, employs the minimum bounding box method to calculate the three-dimensional geometric dimensions of the defects, achieving rapid and accurate three-dimensional quantitative characterization of the defects.

A computing system may include an eject direction determination engine configured to determine an eject direction for an injection mold design, including by determining a set of candidate eject directions for the injection mold design, including a bounding box candidate eject direction determined based on a minimum bounding box of an object representative of a product to be manufactured through the injection mold design and selecting the eject direction for the injection mold design from the set of candidate eject directions based on eject direction determination criteria. The computing system may also include an eject direction application engine configured to set the determined eject direction for the injection mold design so that physical mold pieces constructed from the injection mold design are configured to separate from one another in the determined eject direction during an injection mold production process to manufacture the product.

The invention discloses a display image uniformity statistical method and device and a storage medium, which are used for improving the accuracy of gray uniformity analysis of images shot by a display. Generating a row / column direction minimum bounding rectangular frame for the normalized image; performing intersection processing and connected domain separation processing according to the minimum bounding rectangular frame in the row / column direction, and calculating a gray statistical information value of a separation region; generating a blank image, replacing the gray value of the blank image with the gray statistical information value, and generating a row curved surface image and a column curved surface image; circulating the array of the blank images, generating a dynamic row and column coordinate array of a neighborhood, and generating a vector field image; performing algorithm remapping processing on the normalized image and the vector field image to generate a result image; combining the result images, and filling the maximum pixel value of the multi-channel image into the to-be-processed image to generate the to-be-processed image; and generating a target filling image, and carrying out gray level distribution uniformity analysis according to the gray level value data.

The invention discloses a two-dimensional code positioning method and system based on a grid jump degree and a readable storage medium. The method comprises the steps of obtaining a to-be-recognized two-dimensional code image, and performing sampling to obtain a grid image; traversing the gridding image to calculate rank jump degree scores, and sorting the jump degree scores; mapping the coordinate of the target point corresponding to the score with the highest jump degree into the two-dimensional code binary image to perform cross retrieval of a two-dimensional code connected domain; the retrieved minimum bounding box of the connected domain is judged, and if yes, coordinates of the minimum bounding box of the connected domain are mapped to the two-dimensional code image to obtain a two-dimensional code area; after the two-dimensional code area is corrected and adjusted, decoding is conducted to complete two-dimensional code positioning, and decoding is stopped when decoding succeeds and the number of the two-dimensional codes obtained through decoding meets the preset number. Through innovative jump degree evaluation and grid priority positioning, the problems of low speed and poor universality in the prior art are solved, and efficient and stable two-dimensional code recognition is realized in a complex environment.

The embodiment of the invention provides a detection method and device for deformation of a steel part, a storage medium and a computer program. Comprising the following steps: respectively determining first and second contour point clouds of a to-be-detected model steel piece; respectively constructing a first bounding box and a second bounding box for the first contour point cloud and the second contour point cloud; performing point cloud transformation to obtain a third point cloud and a fourth point cloud of the to-be-tested model steel part and the to-be-tested model steel part respectively; performing first rotation adjustment on the transformed first bounding box and the transformed second bounding box to obtain a first minimum bounding box and a second minimum bounding box for the to-be-tested model steel part and the to-be-tested model steel part respectively; performing point cloud transformation to respectively obtain a fifth point cloud and a sixth point cloud of the to-be-tested model steel part and the to-be-tested model steel part; performing second rotation adjustment on the transformed first minimum bounding box to obtain at least one third minimum bounding box; performing point cloud transformation to obtain at least one seventh point cloud for the to-be-tested steel part; performing point cloud fine registration on each seventh point cloud and the sixth point cloud to obtain a distance average value of a plurality of nearest neighbor points; and determining the deformation quantity of the to-be-measured steel part according to the minimum distance average value.

The invention discloses a dynamic ray tracing wireless channel modeling method, device, equipment and medium, and belongs to the technical field of wireless communication, and the method comprises the following steps: selecting a dynamic scene, and configuring scene parameters; judging whether the current simulation moment is smaller than preset simulation total time or not, and if yes, obtaining an initial ray path through a mirror image method; constructing a double-layer acceleration structure of a dynamic object and a static object; executing an intersection test of the ray and the hierarchical bounding box, and obtaining geometric information of each reflection point and a minimum bounding box where the reflection point is located; selecting the maximum speed of all the dynamic objects in the application scene and the minimum size of all the minimum bounding boxes, and obtaining and updating the coherence time; and executing dynamic ray tracing in the updated coherence time window and updating the simulation moment to realize dynamic ray tracing. According to the method, the calculation efficiency can be remarkably improved on the premise of ensuring relatively high calculation precision, and the method is particularly suitable for a mobility application scene with relatively high requirements on the calculation efficiency and the response speed.

The embodiment of the present application provides a kind of modeling method, system, equipment and storage medium for extracting foreground object, belong to three-dimensional reconstruction technical field.Modeling method for extracting foreground object includes: obtaining the image point cloud data of target object and camera pose information;The foreground and background in image point cloud data are separated, and the foreground object point cloud is obtained;According to the foreground object point cloud extracted, the minimum bounding box of foreground is determined;Based on the above data, foreground point data and background point data are determined;Based on foreground point data and background point data, the preset reconstruction network is used to determine foreground object reconstruction data and background reconstruction data;According to foreground object reconstruction data and background reconstruction data, generate target object model and display.The embodiment of the present application calibrates foreground and background using minimum bounding box, reduces the cost of manual annotation, also uses preset reconstruction network to predict model data, improves the accuracy and accuracy of model reconstruction.

The invention discloses a quantitative evaluation method and system for an open space between three-dimensional buildings, an intelligent terminal and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining a minimum external bounding box corresponding to a three-dimensional building model in a three-dimensional space; observation point control parameters are obtained, a three-dimensional observation point is generated according to the minimum external bounding box and the observation point control parameters, a corresponding push-broom point set is generated on the surface of the three-dimensional building model through a push-broom method, non-viewpoints are removed, and a visual push-broom point set composed of visual push-broom points is obtained; according to the visual push-broom set, building vision field volumes corresponding to the three-dimensional observation viewpoints are obtained through calculation; and obtaining a theoretical vision field volume corresponding to each three-dimensional observation viewpoint, calculating a vision field volume opening index corresponding to each three-dimensional observation viewpoint according to the building vision field volume and the theoretical vision field volume, and taking the vision field volume opening index as an opening space quantitative evaluation result. According to the invention, open space quantitative evaluation can be carried out on specific space points.

The chip defect detection method and system based on kernel norm minimization and machine learning, the method comprises the steps of: using the background separation method based on kernel norm minimization to separate the image foreground and background for the collected chip defect data; the pad position of the foreground image is identified through Huffman transformation, and the corresponding pixels are set to 0 to eliminate the pad image; the image processing techniques such as corrosion and expansion are used to process and eliminate noise points, realize defect area connection; all defect areas in the image are searched to obtain the minimum boundary box of the defect area; the K-Means clustering algorithm is used for defect labeling of different types of defect images to form a defect data set; finally, an end-to-end deep neural network chip defect classification cluster algorithm model is formed by using the training set and the test set. The method can realize real-time and accurate integrated circuit chip surface defect recognition, classification and positioning.

The embodiment of the invention provides a three-dimensional scene reconstruction method and device, equipment and a storage medium. The method comprises the following steps: acquiring a color image and a depth image of a three-dimensional scene at the same moment; according to the depth image, determining the prior depth of object pixel points subjected to depth clustering in a detection frame of each object in the color image; and performing depth diffusion on the pixel points in the detection frame according to the color information of each pixel point in the detection frame and the priori depth of the pixel points of the object to obtain the actual depth of each pixel point in the detection frame so as to generate a minimum bounding box of the object. According to the embodiment of the invention, the minimum bounding box with a simple geometric structure can be used for approximately replacing each complex object, the efficient and accurate reconstruction of each object in the three-dimensional scene is realized, the calculation overhead during the reconstruction of each object in the three-dimensional scene is greatly reduced, and the reconstruction reliability of each object in the three-dimensional scene is improved.

The present application relates to OLED point glue detection technical field, especially in kind, a kind of OLED point glue coating specification detection method, storage medium, equipment, it includes the following steps: step S10, point cloud data acquisition;Step S20, based on the transmission belt point cloud elimination of straight-through filtering;Step S30, based on the product point cloud area segmentation of point cloud registration;Step S40, based on the point glue coating area segmentation of Euclidean clustering;Step S50, based on the point glue coating specification detection of point cloud minimum bounding box has been used to judge whether to pass detection.The present application designs relevant algorithm can realize efficient and accurate OLED point glue coating specification detection, improves production efficiency and quality control level.

This application discloses a batch texture mapping method for irregular top surfaces of 3D models, including: S1. Generating matching texture images based on GIS features; S2. Calculating the rotation angle of the minimum bounding box of the GIS features; S3. Adding the rotation angle of the minimum bounding box to the GIS features; S4. Creating texture mapping CGA rules in CityEngine; S5. Applying texture mapping to the irregular top surface of the 3D model and correcting it. This application enables batch texture mapping of the top surface of 3D models. Based on GIS vector and raster data, the generated texture images can strictly maintain consistency with the shape of each model's top surface, thus ensuring the accuracy of the texture files; at the same time, by calculating and adjusting the texture rotation angle, the mapping accuracy is further guaranteed. As an automated batch processing solution, compared with traditional manual texture mapping, this application significantly saves labor costs and improves work efficiency.