96 results about "Angular point" patented technology

The invention discloses a hand-eye calibration method, device and equipment for a mechanical arm and a storage medium. The method comprises the steps that a calibration plate is fixed to the tail end of a mechanical arm, and the mechanical arm is controlled to move along a preset track, so that the calibration plate is always located in the view field of a camera; under at least three different postures of the mechanical arm, the calibration plate image is collected, and meanwhile the pose of the calibration plate at the tail end of the mechanical arm under a mechanical arm coordinate system is recorded; calculating the pose of the calibration plate in the camera coordinate system through calibration plate angular points in the calibration plate image; and according to the pose of the corresponding calibration plate in the mechanical arm coordinate system and the pose of the corresponding calibration plate in the camera coordinate system, calculating a rotation matrix and a translation vector between the mechanical arm coordinate system and the camera coordinate system so as to complete hand-eye calibration. According to the technical scheme, high-precision hand-eye calibration is achieved, and the stability of automatic application of the robot is remarkably improved.

The invention discloses a projection single attitude calibration method, system and device and a medium, and relates to the technical field of computer vision and projection interaction.The method comprises the steps that a plurality of calibration patterns are generated and projected to a calibration plane, gray level images are collected, corner point detection and sub-pixel refinement processing are carried out, and a projection single attitude calibration result is obtained. The method comprises the following steps: acquiring an angular point corresponding relation between a projector image and a camera image, carrying out iterative solution on a projection matrix of a projector and a projection matrix of a camera, separating an internal parameter matrix and an external parameter matrix, calculating a basic matrix and an essential matrix, and decomposing to obtain a rotation matrix and a translation vector of the camera relative to the projector; camera imaging distortion is estimated, a distortion correction coefficient is obtained, and distortion correction is carried out; and counting a re-projection error generated in the correction process, and adjusting parameters of the projector and the camera until the error meets a preset precision requirement. Projector parameter calculation is completed through projection single posture calibration, posture adjustment is not needed in the calibration process, the automation degree is improved, and meanwhile manual intervention is reduced.

The invention discloses a laser radar-camera fusion calibration method and system, and belongs to the field of calibration. According to the method, after a target is shot through a laser radar and a camera, multiple pairs of corresponding three-dimensional point clouds and two-dimensional images are obtained; angular point coordinates in the phase unwrapped image are obtained through the phase unwrapped image and the two-dimensional real image, three-dimensional angular point coordinates in the three-dimensional point cloud are further obtained, the two-dimensional angular point coordinates and the three-dimensional angular point coordinates are input into an external parameter calibration program of the laser radar and the camera, a rigid matrix between two sensor coordinate systems is obtained, and calibration is completed. According to the method, a fast inversion method of angular points on a phase unwrapped graph based on a Gaussian elimination method is designed, a calculation strategy of laser radar point cloud-phase unwrapped graph-angular point detection-angular point three-dimensional coordinates is provided, after three-dimensional point cloud and two-dimensional images of a target are collected, data can be imported into a calibration program for automatic calculation, and the accuracy of calibration is improved. The method has the advantages of less human intervention, high automation degree, fast operation and high efficiency.

The invention discloses a micro-sensing trapezoidal method, device and equipment based on Aruco recognition and a medium, and relates to the field of computer vision. The method comprises the following steps: S1, projecting an Aruco grid and collecting an image, and extracting marked angular points to construct a position set; s2, calculating a trapezoid tension factor based on the trapezoid area and the opposite side distance, and quantifying local deformation; s3, fusing multi-labeled spatial parallax and tension information, constructing a continuous tension equilibrium domain, and generating a final mapping position through gradient correction basic inverse projection mapping and boundary disturbance compensation; and S4, outputting an inverse perspective matrix based on a fusion result, and estimating a microscopic pose offset parameter for fine adjustment of the projector. And through tension factor and spatial parallax modeling, adaptive correction of a distortion region is realized, the edge consistency and overall symmetry of the image are improved, and the stability and precision of the projected image are enhanced.

The invention provides a three-dimensional calibration method using a speckle image as a calibration object and combining weight parameters. The method comprises the following steps: acquiring a standard grid image and the speckle image through a camera; determining angular point positions in the standard grid image through an angular point detection algorithm; calibrating the stereoscopic vision system by using the obtained angular points to obtain an initial calibration result; calculating 3D coordinates of the camera calibration board in the world by using the disparity map; determining a subset of the reference image corresponding to the checkerboard angular points in the target image through a digital image cross-correlation algorithm; calculating a weight parameter of each calibration point based on the re-projection error; solving internal and external parameters of the camera by using the weight parameters, radial alignment constraint and a least square method; optimizing the main point of the camera by using the weight parameters; and if the re-projection error or the number of iterations does not meet the requirement, repeatedly calculating the weight parameter of the calibration point and the subsequent steps, otherwise, obtaining a camera calibration result, and obtaining the distortion curved surface of the camera lens.

The invention relates to the technical field of deburring, in particular to deburring equipment of a tool jig and an automatic burr positioning method. The method comprises the following steps: acquiring a plurality of monitoring images of a to-be-deburred tool jig under each view angle; performing Gaussian pyramid scale transformation on each monitoring image, performing angular point detection, and dividing the angular points in each monitoring image into two categories according to the presentation condition of the angular points in a scale image; obtaining a texture expression value of each angular point in the scale image by combining the relative distance between each angular point and other angular points in the corresponding scale image of each monitoring image and the edge change condition; and obtaining a texture feature value of each angular point in the monitoring image by combining the texture representation value of each angular point in the corresponding scale image in all the monitoring images under the same visual angle, and further dividing and screening a burr region for each category. According to the invention, the positioning accuracy of the burr area and the burr removal effect are improved.

The invention relates to the technical field of object recognition based on image and point cloud fusion, and discloses a machine vision-based obstacle detection method and system in a container moving process, and the method comprises the steps: obtaining three-dimensional point cloud data through a laser radar installed on container carrying equipment, and obtaining a two-dimensional image through an industrial camera; performing terrain reference correction on the three-dimensional point cloud data, and establishing an inclined coordinate system matched with the ground gradient; performing perspective distortion correction on the two-dimensional image based on the inclined coordinate system to obtain a corrected two-dimensional image; extracting edge features, angular point features and semantic features from the corrected two-dimensional image; extracting geometric features and reflection intensity features of the three-dimensional point cloud data under the inclined coordinate system; performing cross-modal fusion on the edge features, the angular point features, the semantic features, the geometric features and the reflection intensity features to generate fusion features; and the obstacle type is identified based on the fusion feature, and the obstacle sensing reliability in the complex industrial environment is improved.

The invention relates to the technical field of robots, and discloses an obstacle detection method, a robot, equipment and a storage medium. The method comprises the steps that a current frame image containing an obstacle and the moving speed of the robot are obtained through the robot, an object detection frame corresponding to the obstacle is generated in the current frame image, and the depth of the obstacle is calculated according to the position of the object detection frame in the current frame image. The method comprises the steps of obtaining an object detection frame of an obstacle, distributing a plurality of target angular points in the object detection frame, predicting a predicted angular point position in a next frame of image through a tracking algorithm according to the depth and the moving speed, generating a predicted object detection frame according to the predicted angular point position, and determining a predicted position of the obstacle according to the predicted object detection frame. According to the embodiment of the invention, the calculation burden of obstacle detection by the robot can be reduced, and the robot can update obstacle information at a higher frequency.

The invention relates to the field of computer vision, and provides a primitive rasterization method and device, electronic equipment and a storage medium. The method comprises the steps of determining an equation and a type of each edge of a primitive according to coordinates of vertexes of the primitive; searching a coefficient adjustment mode of the equation of each edge according to a preset rasterization mode and the type of each edge, and adjusting the coefficient of the equation of each edge according to the coefficient adjustment mode; determining a pixel coverage judgment condition of the primitive according to a preset rasterization mode; according to the coordinate of the angular point of each pixel and the new equation of each edge, whether each pixel meets the pixel coverage judgment condition of the primitive or not is judged, and when any pixel meets the pixel coverage judgment condition of the primitive, it is determined that the pixel is the pixel obtained through primitive rasterization. According to the method, the correctness of conservative rasterization function realization is ensured, and the cost of conservative rasterization is lower, so that conservative rasterization is simply and efficiently completed.

The invention relates to the technical field of SLAM, in particular to a dynamic environment robust positioning method based on improved ORB-SLAM2, and the method comprises the steps: obtaining RGB-D scene data containing an indoor moving object, and extracting ORB feature points described by FAST angular points and BRIEF descriptors; extracting feature points with unreliable heights according to geometric features of ORB feature points of adjacent frames; pixel analysis is carried out on the RGB-D scene data based on a Fast-SAM instance segmentation model, and a mask matrix containing environmental object space boundary information is generated; performing point-prompt extraction on the height unreliable feature points and the mask matrix to obtain a dynamic object mask; removing ORB feature points existing in the dynamic object mask to obtain a reliable feature point set; and calculating matching point pairs in the reliable feature point set to obtain an essential matrix and a corresponding rotation matrix and translation vector, and refining the pose based on a nonlinear optimization method.

The invention discloses a camera calibration method and device, equipment and a storage medium. The method comprises the following steps: acquiring a first image acquired by shooting a calibration plate by a camera; wherein the calibration plate comprises a plurality of angular points; performing inverse perspective transformation on the first image based on the internal reference and the initial external reference of the camera to obtain a second image; detecting angular points in the second image to obtain a first angular point detection result; based on the first corner detection result, the first image and the internal reference, solving to obtain a target external reference of the camera; and calculating an error parameter based on the target external parameter, the internal parameter and the first image, and when the error parameter satisfies a preset condition, determining that camera calibration is completed. According to the technical scheme of the invention, the inverse perspective transformation is carried out on the first image shot and collected by the calibration plate, so that the influence of partial camera distortion can be eliminated, the accuracy of angular point detection is improved, and the success rate and accuracy of camera calibration can be improved.

Systems and methods are described relating to pose and shape estimation of objects. In some examples, a camera generates images depicting an object from different viewpoints. Within the images, a system identifies corners of the object, and the system uses these corners to generate lines that are projected from different viewpoints through the corners. Points may be identified by intersecting lines such that the points may be used to generate estimations of the object. The estimation with the highest score may be used to place the object in a location different from where the object was located.

The invention discloses an article grabbing and positioning method, system and device and a medium, and relates to the technical field of visual recognition. The method comprises the steps that a two-dimensional image, collected through a monocular camera, of an object to be grabbed is acquired; the types and the number of the to-be-grabbed articles in the two-dimensional image are recognized, and standard physical sizes corresponding to the types are determined; if the object is a single object, the object serves as a target to-be-grabbed object, the top face corner pixel coordinates of the object are detected, and the three-dimensional pose is solved through the PnP algorithm by combining the physical size and the internal reference of the monocular camera; if the number of the objects is multiple, all candidate corner points are detected, quadrilateral corner point sets of all the objects are screened out through clustering and geometric constraint analysis, then candidate three-dimensional poses of all candidate objects to be grabbed are calculated through a PnP algorithm, and then a target object to be grabbed is selected according to the candidate three-dimensional poses; and finally outputting the three-dimensional pose information of the target to-be-grabbed object. According to the invention, accurate positioning of a single article and three-dimensional pose recognition in a multi-article stacking scene are realized only by means of the monocular camera.

The present invention discloses a method and device for extrinsic parameter calibration based on a calibration template, comprising: collecting an RGB image and a depth map of the calibration template; aligning the RGB image and the depth map, and extracting inner corners of the RGB image based on a corner extraction algorithm; obtaining depth information corresponding to each inner corner point extracted from the RGB image on the depth map, and calculating the coordinates of each inner corner point in the camera coordinate system based on each inner corner point and its corresponding depth information; obtaining the coordinates of each inner corner point in the forklift coordinate system based on the relationship that the projection of a preset inner corner line of the calibration template coincides with the origin of the forklift coordinate system; and calculating the calibration extrinsic parameters of the camera based on the coordinates of each inner corner point in the camera coordinate system and the coordinates in the forklift coordinate system. The present invention solves the technical problems in the prior art of the complex calibration process of the calibration template and the low accuracy and robustness of the extrinsic parameter calibration.

The invention provides a vSLAM and display screen coordinate system alignment method and system based on a two-dimensional code, and the method comprises the steps: controlling a display screen to synchronously display a two-dimensional code with a known physical size and a known position parameter under a display screen coordinate system, collecting an image frame containing the two-dimensional code, and obtaining a camera pose synchronized with the image frame in time; identifying the two-dimensional code, extracting the coordinate of the angular point image, and calculating the spatial pose of the two-dimensional code in a vSLAM world coordinate system in combination with the physical size of the two-dimensional code participated in the camera; establishing a coplanar consistency constraint based on a plurality of two-dimensional code space poses, jointly estimating a display screen world pose of the display screen in a vSLAM world coordinate system, and calculating a deformation parameter used for representing a non-ideal plane state of the display screen; and further constructing a coordinate system mapping relation between a display screen coordinate system and a vSLAM world coordinate system, realizing accurate mapping from a screen coordinate to a world coordinate, and performing verification and exception processing on an alignment result.

The application relates to an object positioning method, device, system, readable storage medium and program product. The method comprises the following steps: acquiring an object angle range and an object edge direction vector of a target object; extracting at least one candidate corner point and at least one candidate edge line segment combination from a shooting image corresponding to the target object; extracting at least one candidate geometric feature combination from all candidate corner points and all candidate edge line segment combinations according to the object angle range and the object edge direction vector; screening a target object shape from a candidate object shape corresponding to each candidate geometric feature combination, and positioning the target object according to the target object shape. The method can accurately position the object.

The present invention discloses a method for extracting key points from a lateral cephalogram, including: S1, collecting a plurality of lateral cephalograms; S2, performing conditional screening on the collected plurality of lateral cephalograms; S3, preprocessing the plurality of lateral cephalograms to obtain a grayscale image of the lateral cephalogram; S4, calculating the probability density of the image using a Gaussian probability density function to obtain the foreground region and the background region in the image; S5, using a corner feature method to extract the dynamic points among the key points of the head in the foreground region; S6, taking the FH plane on the head in the foreground region as the abscissa and the plane perpendicular to the FH plane as the ordinate to construct a two-dimensional rectangular coordinate system; S7, extracting the coordinate information of the dynamic points among the multiple key points of the head obtained in step S5. Compared with the traditional manual positioning, the present invention is faster and more efficient. Compared with the traditional software-assisted positioning, the present invention has high accuracy and is more convenient, fast and easy to operate.

The application provides a kind of slope surface displacement monitoring method, device, medium and equipment, comprising: collecting multiple image data of target slope;By analyzing multiple image data, determine multiple target targets and get the area code and pixel coordinates corresponding to the target target;Get the spatial coordinates of the four corner points of each target target in multiple target targets and the centroid coordinates of each target target;Respectively for each target target in multiple target targets, according to the spatial coordinates and centroid coordinates of the target target, the diagonal vector of each target target is calculated, the direction vector of the plane of each target target is obtained, and the direction vector has 3 direction degrees of freedom;The target slope is monitored by pixel coordinates, spatial coordinates, centroid coordinates and direction vector, and the monitoring result is obtained;Compared with the prior art, 3 displacement degrees of freedom + 3 direction degrees of freedom monitoring of the target slope is realized, and the precision of slope monitoring is improved.

The invention is suitable for the technical field of lasers, and provides a distortion correction method and device for an ultra-wide-angle camera and electronic equipment, and the method comprises the steps: obtaining a to-be-corrected image corresponding to a to-be-engraved material collected by the ultra-wide-angle camera in a laser engraving machine; distortion correction parameters corresponding to the ultra-wide-angle camera are obtained, the distortion correction parameters comprise a distortion coordinate matrix and a standard coordinate matrix corresponding to each angular point in a reference image, and the reference image is a calibration plate image collected by the ultra-wide-angle camera; and correcting the to-be-corrected image according to the distortion coordinate matrix and the standard coordinate matrix to generate a corrected image corresponding to the to-be-engraved material. Therefore, each pixel point in the to-be-corrected image is corrected to the correct position according to the pre-stored distortion correction matrix and the standard coordinate matrix, and image distortion generated during shooting of the ultra-wide-angle camera is eliminated, so that the image quality of the engraving breadth is improved, and the engraving precision of the laser engraving machine is improved.

The invention provides a label foot warping detection method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining an image of a to-be-detected label, and enabling the to-be-detected label to comprise a plurality of corner points; extracting an edge line in the image of the to-be-detected label; according to the edge line, determining an ideal coordinate of each angular point of the to-be-detected label in a label coordinate system; wherein the label coordinate system is a coordinate system under the image of the label to be detected; taking the ideal coordinate position of each angular point as a center to obtain a region of interest of each angular point; determining an image of each angular point according to the image of the to-be-detected label and the region of interest of each angular point; angular point features of the image of each angular point are extracted; according to the angular point features, determining actual coordinates of each angular point in the label coordinate system; and according to the ideal coordinate and the actual coordinate of each angular point, judging whether the to-be-detected label has a warped foot or not.

The invention discloses a camera calibration method, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining a plurality of target poses corresponding to a calibration plate, and determining a target pixel coordinate corresponding to an angular point under each target pose based on the angular points on the calibration plate and the image size of a camera; acquiring a current image of the calibration plate under a current pose acquired by the camera, determining a current pixel coordinate corresponding to an angular point in the current image, adjusting the calibration plate from the current pose to a corresponding target pose based on the current pixel coordinate corresponding to the angular point and the target pixel coordinate, and acquiring a target image corresponding to the calibration plate by using the camera; calibrating the camera by using the target images under the plurality of target poses to obtain a plurality of groups of candidate camera internal parameters; and acquiring a verification image corresponding to the verification plate by using the camera, and obtaining a target camera internal reference from the multiple groups of candidate camera internal references based on a distortion removal effect of each group of candidate camera internal references on the verification image. According to the scheme, the convenience and precision of camera calibration can be improved.

This application relates to the field of video processing, and particularly to a method and system for improving the tracking accuracy of a camera. The method includes: obtaining the motion data of the camera, where the motion data includes a first translation vector and a first Euler angle; based on the first translation vector, the first Euler angle, and a conversion formula, obtaining the first motion pose of the camera based on the world coordinate system, where the conversion formula is a formula for converting the first Euler angle into a first rotation matrix; obtaining the video stream collected by the camera, and obtaining the coordinate matrix of each corner point of the Aruco code in the video stream; based on the coordinate matrix and the camera internal parameter matrix, obtaining the second motion pose of the camera; and performing weighted fusion on the first motion pose and the second motion pose to obtain the target motion pose of the camera. This application can improve the tracking accuracy of the camera, ensure the accuracy and continuity of the tracking data, and at the same time reduce the input cost.

The present invention discloses a chip pin measurement method and device based on an adaptive rectangular frame, wherein the method includes: obtaining an image of the chip to be measured; based on the obtained image of the chip to be measured, determining a first region of interest and solving the minimum bounding rectangle of the first region of interest; calculating the four corner points of the minimum bounding rectangle and sequentially sorting the four corner points, wherein the pins on any side of the first region of interest correspond to two of the sorted four corner points; selecting all target pins on any side of the first region of interest, and drawing an adaptive measurement rectangular frame for the target pins based on the positions of the two corner points corresponding to the target pins and the reference parameter values ​​of the target pins; based on the adaptive measurement rectangular frame, determining a second region of interest and solving the pin edges within the second region of interest; and obtaining data of the target pins based on the pin edges. This method can reduce measurement difficulty, reduce calculation complexity, and improve the reliability and stability of measurement results.

The embodiment of the invention relates to the field of displacement monitoring and data processing, and provides a real-time displacement acquisition method based on machine vision and a related device, and the method comprises the steps: obtaining a first image of a reference point and n target monitoring points at a t moment, and obtaining a first image set; according to the initial parameter information set and the first image set, target center corner sub-pixel-level position information corresponding to the reference point and the n target monitoring points is determined, and target center corner sub-pixel-level position information corresponding to the reference point and a target center corner sub-pixel-level position information set corresponding to the n target monitoring points are obtained; determining a first relative position information set according to the sub-pixel-level position information set of the central angular points of the n target monitoring point targets and the sub-pixel-level position information of the central angular points of the reference point targets; acquiring a second relative position information set of the n target monitoring points at the t-1 moment; according to the first relative position information set and the second relative position information set, the displacement variations corresponding to the n target monitoring points are determined, and the accuracy and accuracy of the displacement variations are improved.

Systems and methods are described relating to pose and shape estimation of objects. In some examples, a camera generates images depicting an object from different viewpoints. Within the images, a system identifies corners of the object, and the system uses these corners to generate lines that are projected from different viewpoints through the corners. Points may be identified by intersecting lines such that the points may be used to generate estimations of the object. The estimation with the highest score may be used to place the object in a location different from where the object was located.

The invention relates to the technical field of mechanical arm control, in particular to a collision detection and pose adjustment method and system for picking in a mechanical arm box. The method comprises the following steps: firstly, projecting a three-dimensional point cloud of a box body to a two-dimensional table-board coordinate system, matching to obtain an initial relative pose, performing iterative registration on the three-dimensional point cloud of the box body and a three-dimensional template point cloud according to an initial relative pose relationship, and obtaining coordinates of inner and outer angular points of the box body; then, the three-dimensional point cloud of the box body is converted into a box body coordinate system according to the coordinates of the inner and outer angular points of the box body, and a space plane equation of each side wall of the box body is obtained; then, judging whether the collision risk of the box body occurs or not by calculating the intersection point distance between the pose ray of the sorting point and the side wall of the box body; if so, generating an execution vector; otherwise, pose point optimization is carried out, sorting task execution information is generated according to the pose point optimization, it is ensured that the mechanical arm does not collide with the side wall when grabbing in the box body, and the operation safety and reliability are improved.

The invention discloses a lens distortion detection method and device, and the method comprises the steps: A, controlling a camera to shoot an image of a target, and obtaining a to-be-calibrated image; then executing the step B; step B, selecting a group of to-be-fitted angular points from the to-be-calibrated image, and performing fitting processing on the group of to-be-fitted angular points to obtain a distortion evaluation value; then executing the step C; and step C, detecting the distortion condition of the lens based on the distortion evaluation value so as to distinguish different lenses. In conclusion, the distortion detection precision of different lenses is improved.

The invention relates to a marker (400), in particular a two-dimensional marker, which is optically detectable and has a polygonal, in particular rectangular, marker base shape (402) with corners (404), wherein the marker has at one or more of the corners (404) a teardrop-shaped extension (406) located outside the marker base shape (402), which creates a saddle point at the respective corner. The invention also relates to an object with such a marker and to a method for determining the position of the saddle points.

The invention relates to an electronic equipment parameter calibration method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: in response to a triggered calibration starting operation, obtaining a corner image containing a target calibration pattern and distance information; performing angular point extraction on the angular point image to obtain image coordinates of each angular point in the angular point image; on the basis of the image coordinates of all the angular points, the internal parameters and distortion parameters of the rearview mirror lens and the world coordinates of all the angular points, the calibration external parameters of the rearview mirror lens are determined; wherein the world coordinate of each angular point is determined based on the distance information; and determining a calibration result of the calibration external parameter based on the precision value of the calibration external parameter. By adopting the method, the parameter calibration accuracy of the electronic equipment can be ensured, and the parameter calibration efficiency of the electronic equipment can be effectively improved.

The invention relates to a camera pose determination method and device, a medium, electronic equipment and a program product, and the method comprises the steps: obtaining an RGB image and a depth image which are shot by a camera and are used for describing an inverse color calibration board, and the inverse color calibration board is obtained through the inversion of the color of the calibration board; according to the target image, the depth image and the camera internal reference, determining a first three-dimensional coordinate of a target feature point in the target image in a camera coordinate system, the target image being an image obtained by performing color inversion processing on the RGB image, and the target feature point being an angular point of a black square block or a central point of the black square block in the target image; performing point cloud matching on the first three-dimensional coordinate and a second three-dimensional coordinate of the target feature point in a calibration plate coordinate system to obtain an initial camera pose; according to the camera internal reference, the second three-dimensional coordinate, the pixel coordinate of the target feature point and the initial camera pose, the target camera pose is determined, and the estimation precision of the target camera pose determined by depending on the initial camera pose is improved.