226 results about "Point projection" patented technology

The invention relates to the technical field of multi-sensor fusion, in particular to an automatic calibration method and calibration device for laser radar-camera external parameters, and the method comprises the steps: synchronously collecting the point cloud data and image data of a road scene based on a vehicle-mounted laser radar and a camera; performing semantic segmentation on the image data to generate a semantic mask set of each image; based on the point cloud data, geometric attributes of a road scene are extracted from the vectorized map, a laser radar coordinate system of the vehicle-mounted laser radar and points in the vectorized map are projected into the image in combination with the semantic mask set, and a target consistency function is constructed; and adjusting the external parameter matrix based on the target consistency function until the target consistency function reaches a maximum value, and completing automatic calibration. Therefore, the problems that the calibration precision is insufficient and the high-precision perception requirement of automatic driving is difficult to meet due to the fact that related technologies depend on a large amount of labeled data or a specific environment, the generalization ability is poor, and a high-precision map and road prior information cannot be combined are solved.

The invention discloses a weld ROI segmentation method based on active and passive vision fusion. The method comprises the following steps: synchronously acquiring a two-dimensional image and a three-dimensional point cloud of the surface of a welded workpiece; inputting the trained deep learning network, and outputting a weld joint candidate region and a pixel-level mask graph thereof; establishing a cross-modal mapping relation through geometric calibration, and projecting the three-dimensional point cloud to a two-dimensional image to complete registration and fusion; cutting from the three-dimensional point cloud by using a cross-modal mapping relation to obtain a candidate point cloud region; generating a gray matrix for ray odd-even discrimination according to the pixel-level mask pattern; and each point of the candidate point cloud is projected to a pixel coordinate point by point, ray odd-even discrimination is carried out on the projection points according to the gray matrix, the points conforming to an odd-even rule are determined as welding line points and are aggregated into a welding line ROI point cloud, and the welding line ROI point cloud is output as a segmentation result. According to the method, the adaptive capacity to the unstructured welding seam is effectively improved, the point cloud processing complexity is reduced, and good real-time performance and robustness are achieved.

The invention discloses a pixel-level accurate texture generation method based on a multi-view artistic work. The method comprises the following steps: inputting an image file; performing multi-view projection on the 3d model for a plurality of views corresponding to the plane image to construct a texture space; aiming at coexisting points on the surface of the 3d model in the multiple visual angles, calculating a dot product of each visual angle direction and a normal of the surface of the 3d model so as to construct an initial texture map corresponding to the 3d model; projecting all contour points of the 3d model into a texture space to obtain corresponding texture information, and comparing the texture information with contour points contained in the initial texture map to construct a mask area; generating a shielding texture map corresponding to the mask area through a diffusion model; and carrying out rendering processing on the 3d model based on the initial texture map and the sheltered texture map so as to output a high-quality model with texture information. The invention further provides a pixel-level accurate texture generation device. According to the method provided by the invention, the high-quality texture can be generated for the grid, and meanwhile, the pixel-level consistency with the reference art is ensured.

The invention discloses a dual-path non-cooperative spacecraft pose estimation method based on uncertainty perception, and belongs to the technical field of spacecraft pose estimation. According to the method, a dual-path prediction framework based on a shared backbone network is constructed and comprises a geometric reasoning path and a global context sensing path. In the training stage, prediction results of the two paths are aligned through a geometric consistency loss function, and joint optimization is carried out by combining multi-task losses such as key point regression, classification, rotation and translation regression and the like. In the inference stage, the pose estimation result is adaptively fused according to the predicted variance output by each path, when the variance is low, the output of the global context sensing path is directly adopted, otherwise, the key point projections of the two paths are combined, and the final pose is recovered. The method has higher estimation precision, robustness and interpretability in complex space environments such as shielding, illumination variation and large-scale variation, and provides reliable visual navigation support for on-orbit autonomous tasks.

The invention discloses a building detail extraction method and device based on oblique photography and composite modal features, and the method comprises the steps: calculating a tilt parameter of a midpoint of a point cloud model based on the point cloud model of oblique photography data of a target building, and converting the tilt parameter into a color parameter; projecting points on the point cloud model to a target building view area of a two-dimensional plane to obtain a plurality of superpixel blocks, inputting features of the superpixel blocks into a variational auto-encoder, and performing optimization to obtain encoder optimization weight data; and inputting the features of the super-pixel blocks into an encoder to obtain corresponding optimized latent variables, clustering the super-pixel blocks based on the optimized latent variables, and mapping a clustering result to the three-dimensional model of the target building to obtain details of the target building. By adopting the technical scheme, the three-dimensional features and the color features are compounded, and the structure details and the distribution characteristics of the complex building are captured by utilizing the relevance between the features; an encoder of a pre-trained variational auto-encoder is used for aggregation, so that the accuracy of an aggregation result is improved.

The invention relates to the technical field of robots, and discloses an obstacle sensing method and a storage medium, and the method comprises the steps: obtaining image data of an environment in front of a mobile robot and three-dimensional point cloud data generated through laser radar scanning; pixel-level semantic segmentation is carried out on the image data, and a semantic segmentation map with each pixel having a semantic tag is generated; projecting each three-dimensional point in the three-dimensional point cloud data to a semantic segmentation map based on a calibration relationship between a camera and a laser radar, and generating a semantic point cloud with a semantic tag; for a detection blind area of the laser radar in front of the robot, generating a virtual three-dimensional point cloud in the detection blind area by using obstacle semantic information corresponding to an image area of the detection blind area in the semantic segmentation map; and determining the obstacle point cloud based on the three-dimensional point cloud of which the semantic label is the obstacle category in the semantic point cloud and the virtual three-dimensional point cloud. According to the invention, the obstacle detection precision in a complex environment can be improved.

The invention provides a power equipment three-dimensional modeling and route planning method based on laser point cloud and image fusion. The method comprises the steps that an original point cloud sequence and an original image sequence collected by an unmanned aerial vehicle and pose information of the unmanned aerial vehicle are acquired; preprocessing the original point cloud sequence to generate a clean point cloud sequence; preprocessing the original image sequence to generate an enhanced image sequence; performing rough matching on the clean point cloud sequence according to the pose information to generate a panoramic scene point cloud; projecting points of the panoramic scene point cloud to the enhanced image sequence; mapping the pixel color to the panoramic scene point cloud by applying an L-M algorithm to generate a color point cloud; inputting the enhanced image sequence into a pre-trained SegFormer semantic segmentation model to obtain semantic probability distribution of each image; mapping the color point cloud to a corresponding image according to the semantic probability distribution to generate a semantic point cloud, the semantic point cloud including color information and semantic information; and generating a three-dimensional scene model according to the semantic point cloud to output an inspection route.

The invention discloses a lunar surface target three-dimensional point cloud detection and positioning method and system based on semantic information, relates to the technical field of three-dimensional object detection, and receives three-dimensional point cloud data and a two-dimensional image detection result, the two-dimensional image detection result is obtained by detecting acquired image data based on a pre-established two-dimensional target detection model, performing ground segmentation on the three-dimensional point cloud data to obtain non-ground point cloud data, mapping the non-ground point cloud data into a two-dimensional grid with a preset size to obtain a two-dimensional clustering result, and performing clustering on the non-ground point cloud data to obtain a clustering result; mapping the two-dimensional clustering result to the three-dimensional point cloud data to obtain a plurality of point cloud clusters; the points of each point cloud cluster are projected into an image coordinate system, dynamic weighted scores are calculated based on the number and confidence of the projection points of each point cloud cluster falling into the detection frame and the geometrical characteristics of the point cloud clusters, the point cloud cluster with the highest dynamic weighted score is selected for distance calculation, and the distance of the point cloud cluster with the highest dynamic weighted score is calculated; and obtaining a lunar surface target three-dimensional point cloud detection and positioning result.

The invention provides a method for obtaining a relative position relation between linear welding seams and related equipment, and the method comprises the steps: obtaining a projection distance from an end point of a current linear welding seam to a reference linear welding seam which is any welding seam in repeated linear welding seams corresponding to the current linear welding seam; the projection distance comprises a starting point projection distance and an ending point projection distance; and determining a relative position relationship between the current linear weld and the reference linear weld based on the projection distance. The projection distances from the starting point and the end point of the current linear welding seam to the reference linear welding seam are obtained, the relative position relation between the current linear welding seam and the reference linear welding seam is determined through the obtained projection distances, and the purpose of rapidly and accurately obtaining the relative position relation between the welding seams is achieved.

The invention discloses an unmanned aerial vehicle sensing house safety appraisal management system and method based on BIM, and relates to the technical field of data processing. The method comprises the following steps: training a U-Net + + model, and based on a house three-dimensional BIM model, generating a preset track by combining a space grid sampling algorithm with a convex hull optimization algorithm; the unmanned aerial vehicle carries the dual-mode sensing pod to fly along a preset flight path, and image virtual columns and metadata are collected; de-noising enhancement processing is carried out on the image sequence, precision alignment is realized by utilizing BIM feature point projection to guide SIFT feature bidirectional matching, after Euclidean distance threshold verification, a pre-trained U-Net + + model is input to generate a crack binary mask, and the crack binary mask is converted into a physical crack parameter; the inclination angle of the wall is calculated through the SfM point cloud and ICP registration technology; integrating crack parameters, inclination angles and BIM attributes, and automatically triggering graded early warning through a risk rule base; the full-process automation from data acquisition, crack identification to risk assessment is realized, the detection precision and efficiency are remarkably improved, and the high-risk omission ratio is effectively reduced.

The invention discloses an automobile front anti-collision beam radian detection system, and relates to the technical field of anti-collision beam detection. The arc detection device comprises a detection table, a clamping assembly, a positioning assembly and a plurality of arc detection assemblies. The front anti-collision beam is reliably fixed to the clamping table through the clamping air cylinder and the rubber head, and automatic in-place and center correction are achieved through the conductive contact and the positioning conductive inclined block. When the position deviates, judgment is carried out through the resistance value difference, and early warning is given out. The arc measuring assembly is composed of image sensors, an imaging plate, a light shield and an adjusting fluted disc mechanism, the distance between the two sensors can be automatically adjusted according to detection requirements, multi-point projection imaging is conducted on a front anti-collision beam calibration point, and an overall radian curve is calculated. Meanwhile, the system is provided with a centrifugal impeller active heat dissipation mechanism, thermal noise of the image sensor is reduced, and detection stability is guaranteed.

The application relates to the chip detection technical field, in particular to a semiconductor packaging workpiece identification detection method and device and a cutting and sorting integrated machine, wherein the method comprises the following steps: acquiring a surface image of a workpiece to be detected; the surface image comprises an identification for marking a workpiece type of the workpiece to be detected; the workpiece type is a good material type or a bad material type; image skeleton extraction is performed on the surface image to obtain a skeleton line corresponding to a pattern in the surface image; for each pixel point on the skeleton line, if the minimum distance between the pixel point and a preset identification reference line is less than a first preset distance, the pixel point is projected onto the identification reference line; the identification reference line is drawn in the surface image according to the identification shape corresponding to the bad material type; and the identification corresponding to the workpiece type on the workpiece to be detected is determined according to the proportion of the area of the identification reference line projected by the skeleton line. The application can solve the problems of low identification detection precision and weak anti-interference capability of the identification on the workpiece to be detected.

The invention provides a method and a device for generating a process track. The method comprises the following steps: acquiring a group of discrete three-dimensional reference track points and original point cloud data for representing the three-dimensional shape of a workpiece; generating a group of three-dimensional intermediate target points with corresponding process forms through waveform interpolation based on the group of discrete three-dimensional reference track points; for each three-dimensional middle target point, according to the original point cloud data around the three-dimensional middle target point, fitting through a moving least square method to obtain a corresponding local three-dimensional curved surface; the three-dimensional middle target point is projected to the local three-dimensional curved surface, final three-dimensional track point coordinates and normal vector postures thereof on the local three-dimensional curved surface are obtained, the process track is generated based on the multiple final three-dimensional track point coordinates and the corresponding normal vector postures thereof, and it is ensured that the generated process track is attached to the real surface of the workpiece. And meanwhile, the method has process adaptability and high fidelity.

The application discloses a projection and touch fusion voltage control sensing type operation method and system, and relates to the field of projection interaction and touch detection fusion. The method comprises the following steps: determining effective touch pressure according to the construction of a voltage control array baseline and an excitation quantity and the generation of an adaptive threshold value based on static sampling; forming a pressure feature and generating touch point coordinates and a comprehensive pressure amount according to the position and pressure of the effective touch pressure; establishing a mapping from projection coordinates to physical coordinates according to a calibration pattern and generating a touch point projection position in interaction; dividing voltage control levels according to the comprehensive pressure amount and analyzing interaction instructions in combination with the projection position; and realizing adaptive correction by recursively updating mapping parameters according to running increment residuals. Through nonlinear touch pressure recognition, integrated analysis of touch point position and force, and adaptive correction of mapping parameters, stable, accurate and long-term consistent voltage control interaction in a projection and touch fusion scene is realized.

The invention relates to the field of image processing, and provides an image generation method, electronic equipment and a vehicle, and the method comprises the steps: obtaining a fisheye image corresponding to the current position of the vehicle, projecting each pixel point in the fisheye image to a preset spherical model, and determining a first projection point corresponding to each pixel point; projecting each first projection point to a preset cylinder model to obtain a second projection point corresponding to each first projection point; and obtaining target internal and external parameter data corresponding to the fisheye image, and performing texture mapping processing on all the second projection points according to the target internal and external parameter data to obtain a planetary visual angle top view corresponding to the current position of the vehicle. The fisheye image is sequentially projected twice through the spherical model and the cylinder model, alignment of ground textures is achieved due to the fact that the radius of the bottom face of the cylinder is large, points far away from the center can be compressed through vertex transformation of the spherical model, and therefore the problem that far ground points are seriously stretched is avoided, and the accuracy of ground texture alignment is improved. And the accuracy of the planetary view angle top view is improved.

The invention belongs to the field of multi-sensor fusion, and provides a lawn trimming robot environment sensing method and device based on vision and millimeter wave radar fusion. The method comprises the following steps: constructing a lawn data set, optimizing an activation function of a YOLOv11 instance segmentation model in a training stage, simultaneously adjusting and optimizing a model hyper-parameter and an optimizer to inhibit overfitting, and deploying the model to an AI chip end after conversion and quantification, so as to realize real-time visual reasoning of camera data; a DBSCAN algorithm is introduced at a millimeter wave radar end to cluster original point clouds so as to extract stable clustering center points, and the influence of stray points on the detection precision is significantly reduced; the system completes time synchronization of cross-sensor data by using a software timestamp in combination with linear interpolation, realizes spatial alignment through coordinate transformation, then projects a radar clustering center point to a visual detection plane, and performs position matching and decision-level information fusion through a geometrical relationship between the center point and a detection frame, so as to obtain a detection result. And the operation overhead is remarkably reduced while high-precision target positioning is ensured.

The invention provides a method for checking light leakage of a sun shield, which is used for effectively adjusting and optimally avoiding the conditions of upper light leakage or left light leakage of the sun shield, the sun shield, a ceiling boundary, an A column boundary and a front windshield black edge in the driving process of a driver and passengers. By taking the left limit point or the upper limit point of the left eye ellipse as a projection center, projecting a point on the sun shield onto the curved surface of the front windshield, projecting a point on the left A column onto the curved surface of the front windshield, and projecting a point on the ceiling onto the curved surface of the front windshield; and then processing the data. According to the method, the optimized result can be quantitatively presented, a model or an organizing person is not needed for review, and high efficiency and low cost are achieved.

The application relates to a rod-shaped object recognition method and device in an image, computer equipment, a storage medium and a computer program product. The method can be applied to the field of maps and comprises the following steps: based on initial recognition results of rod-shaped objects in multiple continuous images, determining at least two continuous images in which rod-shaped objects exist in the multiple continuous images; based on a fitting straight line of the initial recognition results of the rod-shaped objects in a reference image and the projection of a detection point closest to a reference surface in a previous image on the reference image, recognizing the same rod-shaped object in the reference image and the previous image, obtaining a matching result of the reference image and the previous image; projecting the detection point of the same rod-shaped object in the previous image to the reference image through epipolar line searching to obtain an epipolar line; and based on the matching points of the epipolar line and the fitting straight line, performing positioning processing on the rod-shaped object in the reference image to obtain the recognition result of the rod-shaped object in the reference image. The application can improve the accuracy of rod-shaped object recognition and positioning.

The application discloses a kind of unmanned aerial vehicle based on BIM and perceives house safety appraisal management system and method, it is related to data processing technical field;The application is generated by training U-Net++ model, based on three-dimensional BIM model of house, by space grid sampling algorithm is combined with convex hull optimization algorithm, generates preset track;Unmanned aerial vehicle carries dual-mode sensing pod and flies along preset track, collects image virtual list and metadata;Image sequence is carried out denoising enhancement processing, utilizes BIM feature point projection to guide SIFT feature bidirectional matching to realize precision alignment, after Euclidean distance threshold verification, input pre-training U-Net++ model generates crack binary mask, and is converted into physical crack parameter;Through SfM point cloud and ICP registration technology, the angle of inclination of wall is calculated;Integrate crack parameter, inclination angle and BIM attribute, and automatically trigger graded early warning through risk rule base;Realize the full-process automation from data acquisition, crack identification to risk assessment, significantly improve detection accuracy and efficiency, effectively reduce high-risk missed detection rate.

The application relates to a landmark point matching method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a scanning point cloud obtained by shooting a calibration object under a current scanning visual angle; the calibration object comprises a landmark point; matching the calibration object point cloud with the scanning point cloud to obtain a first matching point pair; the first matching point pair comprises a calibration object matching point and a matching scanning matching point; projecting the scanning matching point to an image coordinate system of a camera to obtain an image mapping point; obtaining a calibration object image obtained by shooting the calibration object by the camera; matching the image mapping point with the landmark point on the calibration object image to obtain a second matching point pair; the second matching point pair comprises a scanning matching point and a matching landmark point on the calibration object image; for the camera, determining a target matching point pair of the landmark point on the calibration object image and the landmark point on the calibration object based on the first matching point pair and the second matching point pair. The method can obtain more accurate target landmark point pairs and optimize unstable factors of the equipment.

A system for executing a three-dimensional (3D) intraoperative scan of a patient is disclosed. A 3D scanner controller projects the object points included onto a first image plane and the object points onto a second image plane. The 3D scanner controller determines first epipolar lines associated with the first image plane and second epipolar lines associated with the second image plane based on an epipolar plane that triangulates the object points included in the first 2D intraoperative image to the object points included in the second 2D intraoperative image. Each epipolar lines provides a depth of each object as projected onto the first image plane and the second image plane. The 3D scanner controller converts the first 2D intraoperative image and the second 2D intraoperative image to the 3D intraoperative scan of the patient based on the depth of each object point provided by each corresponding epipolar line.

The invention relates to a panoramic image splicing method and system based on the real-time attitude of a ship body, and the method comprises the steps: synchronously collecting an original image, a rolling angle data and a pitch angle data through arranging a plurality of fisheye cameras in the circumferential direction of the ship body in combination with inertial navigation equipment; hardware-level clock synchronization is realized by using a second pulse signal of a global positioning system, and alignment of an image and attitude data is completed through a timestamp matching algorithm; the method comprises the following steps: acquiring internal and external parameters of a camera by adopting a Zhang's calibration method, performing de-preprocessing on an image, constructing a rotation matrix based on a real-time attitude, projecting pixel points to a stable world coordinate system, and generating a projection image; for an overlapping region between adjacent projection images, dynamically calculating a fusion weight according to an attitude angle change rate, and realizing adaptive weighted splicing; and finally, a seamless panoramic image is generated and coded and output to a display terminal and a storage device, panoramic image splicing in a ship body shaking scene is realized, and real-time performance, robustness and environmental adaptability are considered.

Systems and techniques are described herein for occlusion detection. For instance, a method for occlusion detection is provided. The method may include generating a plurality of voxels in a voxel space based on a point-cloud representation of a scene; generating an annotation point in the voxel space based on sensor data representative of an object in the scene; projecting a ray from a sensor position in the voxel space to the annotation point; and determining whether the annotation point is occluded based on the ray and the plurality of voxels.

The invention provides a grabbing method and device based on an image segmentation result and electronic equipment, and the method comprises the steps: extracting a foreground region of a mask image containing a bearing object and a plurality of grabbing targets, carrying out the segmentation processing of the foreground mask image, and obtaining a sub-image containing each grabbing target; dividing a minimum circumscribed rotating rectangle of a captured target in the sub-images, determining a main shaft based on the minimum circumscribed rotating rectangle, performing pixel point projection on the captured target based on the main shaft, and determining a captured point based on density information of projection points. And on the basis of the grabbing points of all the grabbing targets, candidate grabbing targets without collisions are screened out, the multiple screened candidate grabbing targets are sorted to obtain a grabbing sequence, and the mechanical arm is controlled to execute grabbing according to the grabbing sequence and on the basis of the grabbing points of all the candidate grabbing targets. According to the scheme, the grabbing points of the grabbing targets can be accurately recognized, the grabbing feasible targets are determined in combination with collision detection, follow-up grabbing is executed based on the sorting of the grabbing feasible targets, and the system operation efficiency is greatly improved.

The application relates to the technical field of sports auxiliary equipment, and discloses a table tennis auxiliary training method, a storage medium, a device and terminal equipment, wherein the method comprises the following steps: acquiring table position information through a depth camera, and constructing a three-dimensional coordinate system according to calibration information of the depth camera and the table position information; acquiring a first table tennis movement image through the depth camera; obtaining table tennis coordinate values based on the three-dimensional coordinate system and the first table tennis movement image; obtaining a table tennis movement trajectory and a landing point according to the table tennis coordinate values; and projecting the table tennis movement trajectory and the landing point onto a table through a projector. The application is a table tennis auxiliary training system integrating intelligence, data and information, and can simultaneously capture a table tennis movement trajectory and action information of a player. The table tennis movement trajectory can be projected onto the table, and the player's action can be scored and guided through projection and an AI model. The efficiency and quality of table tennis training are effectively improved.

The application is a method for installing, measuring, controlling and checking large-curvature pipe sections, which comprises checking the posture of the immersed tube during the installation of the immersed tube pipe sections and checking the through measurement accuracy after the installation of the immersed tube pipe sections; the checking the posture of the immersed tube during the installation of the immersed tube pipe sections specifically comprises: GPS-RTK accuracy comparison, total station synchronous monitoring, pulling and closing systems, and diving and pulling measurement; the checking the through measurement accuracy after the installation of the immersed tube pipe sections specifically comprises: combined cavity tooth measurement and point projection measurement. The application can be applied to the installation, measurement, control and checking of large-curvature pipe sections, the accuracy of the measurement and control system is verified through diving, pulling and closing and RTK, the initial posture measurement of the pipe sections is verified through combined cavity measurement and manhole point projection measurement, the accuracy of the measurement and control system and the through measurement is verified from multiple angles, the risk of pipe section docking is reduced, and data basis is provided for subsequent pipe section linear control.

The application discloses a projection figure distortion prediction compensation correction method of a laser scanning projection system, and comprises the following steps: carrying out laser scanning projection system projection; acquiring projection figure distortion data, establishing a neural network training data set and a test data set; establishing an initial topological structure, weights and thresholds of a BP neural network; optimizing the weights and thresholds of the BP neural network based on a particle swarm optimization algorithm; carrying out deviation compensation on the coordinate positions of each projection point according to the training output of the PSO-BP neural network; selecting feature points in each part of a to-be-projected plane; projecting the feature points by using a distortion deviation correction projector based on the PSO-BP neural network; acquiring feature point projection coordinate values; subtracting the ideal projection point coordinates without distortion from the corrected feature point projection coordinates; judging whether the difference value meets an error interval; if yes, it is determined that the projection coordinate value distortion error has been corrected and compensated; if no, returning to step three for feedback type multiple iterations until the difference value meets the error interval.

The invention relates to a method for measuring the penetration track of a closed multi-layer target, which is used for solving the technical problem that the penetration track in the closed multi-layer target cannot be obtained by the existing method for recording the penetration track of a projectile body on the side surface of a multi-layer target plate by using a camera. The interior of the closed multi-layer target is scanned through the laser radar, the original point cloud data of the bullet hole and the color panoramic image in the bullet hole can be rapidly obtained, the overall penetration situation in the target can be observed, and a macroscopic view angle is provided for researching the penetration effect of the bullet body. According to the invention, the three-dimensional edge points of each layer of bullet hole are projected into the two-dimensional convex polygon, so that the contour and the area of each layer of bullet hole are accurately measured, and the safety risk of manual measurement is reduced.

The present application belongs to the technical field of target real-time decoding positioning, and provides a kind of encoding target real-time decoding positioning method of slit measurement system, its steps include: S1 the layout of encoding target of slit detection point;S2 for the binary coding of encoding target image shot at large inclination angle, and the center position of encoding area and positioning area is obtained as the initial point of compression transformation;S3 adopts single direction wide edge detection to combine edge projection method, and is compressed to project transformation to encoding target point;S4 encoding target decoding;S5 subpixel positioning of encoding target edge pixel optimization, the present application provides edge projection benchmark using single direction wide edge detection, reduces the influence of compression projection transformation by large inclination angle shooting, realizes the compression target point projection transformation using edge projection, and the edge of positioning area is combined with the edge of encoding target, reduces the edge mis-extraction rate, improves the subpixel positioning precision, while having the characteristics of fast and real-time, suitable for long slit multi-point detection.