40 results about "Circle fitting" patented technology

The invention belongs to the field of machine vision, and relates to a novel circle detection method in a complex environment. The method comprises the following steps: firstly, preprocessing an input color image, converting the color image into a grayscale image, then performing Gaussian blur processing, and applying a Canny edge detection algorithm to obtain an edge image; then, a findContours function of OpenCV is used for detecting a contour in the edge image, and traversal processing is carried out on the contour; secondly, circle detection is conducted on each contour through a findcircle () function, and circle fitting is conducted through a three-point circle determination method or a least square circle fitting method; performing accuracy verification on the fitted circle; and finally outputting the number and parameters of the identified circles, such as circle center coordinates and radiuses. The method is low in operand, can rapidly and accurately detect a circle in a complex environment with a weak light source and noise, does not need to occupy high computing resources, and has high detection speed and precision.

The invention discloses a wafer edge finding method and device, the method comprising: collecting an edge image of a wafer, the wafer being placed on a chuck table, the chuck table being movable along an X, Y and θ axis; obtaining arc feature points and notch feature points from the edge image; performing circle fitting on the arc feature points to obtain a first fitted circle; identifying and filtering out abnormal points in the arc feature points based on the first fitted circle and a first preset threshold; performing circle fitting on the remaining arc feature points again to obtain a second fitted circle; identifying and filtering out abnormal points in the remaining arc feature points based on the second fitted circle and a second preset threshold to obtain filtered arc feature points; determining the center deviation of the wafer based on the filtered arc feature points; moving the chuck table along one or more of the X, Y and θ axes to perform center compensation on the center deviation, during which the wafer and the chuck table are separated; determining the angular deviation of the wafer based on the notch feature points; rotating the chuck table around the center of the chuck table to perform rotation compensation on the angular deviation.

The invention discloses an underground mine pipeline type point cloud completion method based on axial slicing, which relates to the technical field of point cloud data processing, is used for performing data completion on pipeline type point clouds, and comprises the steps of axially slicing preprocessed pipeline point cloud data, performing dimension reduction on three-dimensional point clouds to two-dimensional plane processing, and calculating related geometric parameters of pipelines. The method comprises the following steps: extracting a pipeline center line based on improved DBSCAN clustering and least square circle fitting, constructing a skeleton model under geometric topology constraints, combining local geometric features and global topology constraints, realizing geometric reconstruction of a missing region through rotating surface generation and a local interpolation algorithm, and realizing robust repair of the missing region. According to the method, a convex hull and an RANSAC method are combined to extract a pipeline center line and geometric parameters, pipeline point cloud data complementation is realized through a continuous rotation correction method, and the pipeline point cloud complementation quality is remarkably improved.

The invention relates to the technical field of wafer detection, and provides a wafer positioning method, device and equipment and a storage medium, the method carries out circle fitting and straight line fitting through a plurality of contour point coordinates, the more the contour point coordinates participating in fitting are, the higher the positioning precision is, and parameter verification and correction can be carried out through multi-contour point fitting of a circle or a straight line. The precision of the fitting circle and the fitting straight line is higher; meanwhile, the image range for collecting the coordinates of the contour points can be very small, so that the image pixel precision is higher, the fitted circle center coordinates and positioning edge straight lines are more accurate, and the positioning precision and accuracy of the target wafer are improved.

The invention provides a multi-diameter-at-breast-height extraction method and device for a tree with branches, electronic equipment and a medium, and the method comprises the steps: constructing an octree based on a single tree segmentation result, carrying out the clustering analysis through the octree, and extracting point cloud clusters of a trunk and the branches; and then multilayer slicing and circle fitting are carried out based on the obtained point cloud cluster, effectiveness evaluation of a fitting circle is carried out, and finally the diameter at breast height of the trunk and the branches is determined based on an evaluation result. According to the method, tree branches are fully considered, the adaptive octree is adopted for processing, an effective result can be obtained without setting parameters, the scheme for extracting the trunk and the branches has a certain denoising capability, and the accuracy of extracting the diameters at breast height is improved while multi-diameter extraction of the trunk and the branches is realized. Meanwhile, according to the scheme, multi-layer slicing is carried out on effective point clouds of all clusters, circle fitting is carried out on all slices, and fitting result evaluation is carried out by using an effectiveness evaluation index, so that the precision of a diameter at breast height result is further improved.

The application discloses a point-circle distance visual measurement method based on weighted circle fitting and uncertainty evaluation, comprising the following steps: S10, initial circle estimation and local region of interest (ROI) definition; S20, adaptive weighted circle fitting based on measurement point guidance; S30, point-circle distance calculation and uncertainty evaluation. The application realizes higher point-circle distance measurement precision and robustness than traditional methods; significantly reduces measurement errors caused by edge occlusion, noise and non-ideal circle deformation; provides quantitative evaluation (uncertainty) of the reliability of each distance measurement result; while ensuring high precision, maintains or improves calculation efficiency, so that it is suitable for online detection.

The invention relates to the technical field of electrical engineering, in particular to a manual alignment identification method and device and a storage medium, and the scheme comprises the steps: obtaining an edge image of a to-be-aligned element; obtaining a plurality of key points according to the edge image; performing circle fitting processing according to the plurality of key points to obtain a first fitting circle; edge optimization processing is conducted on the first fitting circle, a target fitting circle is obtained, and the target fitting circle is used for determining positioning of the to-be-aligned element. According to the method, through multi-step processing of edge image acquisition, key point identification and circle fitting optimization, accurate positioning of the to-be-aligned element is realized, and the production efficiency and the product quality are improved.

This invention discloses a method for estimating the rotor position of a robot servo motor based on circle fitting. The method includes: in each control cycle of the robot servo motor, using a Hall sensor to detect the absolute position of the servo motor rotor in real time and outputting two Hall signals; using a fitted Taubin circle and its parameters to perform debiasing and normalization processing on the two Hall signals output in each control cycle, and calculating the corrected rotor position angle for each control cycle using an arctangent function; wherein the Taubin circle is constructed based on data digitization and robust fitting using the RANSAC algorithm. This invention improves the accuracy of robot joint motor position detection and control performance by fitting a Taubin circle based on data digitization and the RANSAC algorithm, correcting the Hall signals in real time, and calculating the rotor position angle.

The invention relates to the technical field of computer vision, in particular to an Adam high-precision two-dimensional circle fitting method, which comprises the following steps of: correcting a learning rate and a square gradient based on a circle center position and an initial radius momentum; and after each iteration, judging whether the current error and the updating amplitude meet a convergence condition or not, if the error is smaller than a preset threshold value or reaches the maximum number of iterations, stopping in advance and outputting the fitted circle center and radius, and if the error is not smaller than the preset threshold value or reaches the maximum number of iterations, continuing iteration. According to the method, a momentum and adaptive learning rate updating mechanism is introduced, so that the fitting process is more stable, the sensitivity to noise is effectively reduced, the calculation efficiency is remarkably improved, and the method particularly has excellent performance on asymmetric and noise point sets. The improvement not only improves the precision and stability of circle fitting, but also enables the algorithm to be more suitable for application in real-time and complex environments. Therefore, the problem of low fitting precision easily caused when noise data is processed or data distribution is not uniform by an existing fitting method is solved.

The invention discloses a target grid calligraphy practicing method based on a Chinese character circular structure model. The method comprises the following steps: a) extracting a Chinese character structure circle; b) constructing a target lattice; c) mapping strokes; the invention relates to the technical field of calligraphy teaching, by introducing a Chinese character circular structure model, the system breaks through the neglect of a traditional rectangular grid system on geometrical characteristics of Chinese characters, and by means of target grids constructed by golden proportion concentric circles and equally-divided radial lines, curvature, retraction and density changes of the Chinese characters can be quantified more accurately, so that the accuracy of calligraphy teaching is improved. The scientificity and aesthetic feeling of the writing composition are improved; an RANSAC circle fitting algorithm and an error quantification feedback mechanism are adopted, quantifiable deviation indexes are provided for teachers and students, subjective evaluation in the teaching process is reduced, and teaching efficiency and evaluation objectivity are improved; moreover, through a standardized target lattice template and an image registration technology, the problem that different teaching materials and teachers are inconsistent in definition of'gravity center 'and'middle palace' is solved.

This invention belongs to the field of integrated radar signal processing technology, specifically involving a two-stage clutter suppression method based on the space-time domain, which solves the problem of clutter suppression in complex low-altitude environments. First, the first stage, based on CLAM (Clear-and-Field Analysis), eliminates the dependence on the radial velocity difference between the target and clutter, directly and accurately shielding clutter from the physical space dimension, efficiently eliminating strong static ground object interference while preserving the energy of low-speed UAVs without loss. Second, the second stage, with its candidate angle traversal and circle fitting algorithm, accurately estimates and reduces the DC bias caused by residual static clutter, successfully overcoming the blind spot problem when the target and clutter spatial angles are close, enabling accurate extraction of weak, low-speed UAV targets at close range.

The invention discloses a centroid-offset-resistant multi-circle special-shaped target and a binocular vision positioning method thereof, and belongs to the technical field of industrial vision measurement and precise positioning, the target comprises a white background substrate and seven symmetrically distributed black circles, a large circle is arranged in the center, standard perfect circle small circles are arranged right above and right below respectively, and a large circle is arranged in the middle of the black circles. The four corners are respectively provided with special small circles which are designed according to a cylindrical surface nonlinear projection formula. The positioning method comprises the steps that a binocular camera collects a target image, and two-dimensional circle center coordinates are extracted; calculating a three-dimensional point cloud through stereo matching; extracting a cylindrical space axial vector and constructing a normal plane, and orthogonally projecting the three-dimensional feature points to the normal plane for two-dimensional circle fitting; and calculating the reference point coordinates of the internal anchoring column center and the surface highest axis through inverse coordinate transformation. According to the method, positioning errors caused by curvature deformation, space inclination and rotation around the axis of the cylinder are effectively overcome, and positioning robustness and universality under complex working conditions are remarkably improved.

The invention discloses a bolt and nut pose estimation method based on an image and a point cloud, and the method comprises the steps: carrying out the systematic collection of a bolt and nut image through a mechanical arm, constructing a high-quality data set, carrying out the training based on a YOLOv8 algorithm, and achieving the quick positioning of a bolt and a nut in a two-dimensional image; secondly, a target in the two-dimensional image is mapped to a three-dimensional point cloud through a camera internal reference matrix, point cloud data of the bolt and the nut are segmented, and outliers are removed through statistical filtering; aiming at the pose estimation of the bolt, innovatively using an RANSAC three-dimensional circle fitting algorithm to calculate the circle center and the normal vector of the upper surface of the bolt; for the nut, the plane of the nut is recognized through RANSAC plane fitting, and the pose of the nut is obtained in combination with a three-dimensional circle fitting algorithm; according to the method, the intelligent level and efficiency of overhead line system maintenance are remarkably improved, the risk and labor intensity of manual maintenance are reduced, and technical support is provided for intelligent operation and maintenance of electrified railways.

The present invention discloses a method, device, and storage medium for automatic recognition of image primitives, comprising the following steps: first, inputting image data containing closed contours and filtering the contours to remove noise; then, determining the contour type through eigenvalue calculation to distinguish between single circles and mixed primitives containing lines and arcs; if a single circle is determined to be present, directly performing circle fitting on it and outputting the circle parameters; if a mixed primitive is present, using a sliding window method to identify the straight line components, removing the straight line components, performing connected domain analysis on the remaining point set, and extracting the arc regions; finally, fitting the straight line and arc regions separately to obtain the parameters of the line and circle. The method of the present invention can automatically separate and recognize straight line and arc primitives in an image, reducing manual operations and improving recognition accuracy and efficiency.

The application discloses a circle fitting method and device and a storage medium. The circle fitting method comprises the following steps: performing edge detection processing on a to-be-fitted circular target in a target image to obtain edge detection points; selecting target detection points in the edge detection points to perform iterative fitting processing to obtain an iterative fitting circle; determining fitting weights corresponding to the target detection points according to the fitting matching degrees of the iterative fitting circle and the target detection points; and performing weighted iterative fitting processing according to the fitting weights and the target detection points to obtain target circular parameters of the to-be-fitted circular target. The above scheme can improve the circle fitting precision when the circular target is recognized.

The invention discloses a robot servo motor rotor position estimation method based on circle fitting, and the method comprises the steps: detecting the absolute position of a servo motor rotor in real time through employing a Hall sensor in each control period of a robot servo motor, and outputting two paths of Hall signals; performing debiasing and normalization processing on the two Hall signals output in each control period by using the fitted Taubin circle and the parameters thereof, and calculating the corrected rotor position angle in each control period through an arc tangent function; wherein the Taubin circle is constructed based on robust fitting of data centralization and an RANSAC (Random Sample Consensus) algorithm. Through the fitting Taubin circle based on data centralization and the RANSAC algorithm, the Hall signal is corrected in real time, the rotor position angle is calculated, and the robot joint motor position detection precision and the control performance are improved.

The invention provides a silicon wafer evaluation method and device, a manufacturing method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining the edge contour of a to-be-evaluated silicon wafer, and enabling the edge contour to comprise a first contour corresponding to the main surface of the to-be-evaluated silicon wafer; performing straight line fitting processing on the first contour to obtain a first straight line; clockwise rotating the first straight line by a target angle and performing translation processing to obtain a reference straight line of the edge contour, the target angle being greater than 0, and the reference straight line being not intersected with the edge contour; determining a position closest to the reference straight line in the edge contour as a target position, and intercepting contours on two sides of the target position in the edge contour to obtain intercepted contours; and performing circle fitting processing on the intercepted contour to obtain a fitted circle, and determining an evaluation result according to the radius of the fitted circle, the evaluation result being used for evaluating the edge shape of the cross section of the to-be-evaluated silicon wafer in the thickness direction. According to the invention, the edge shape of the silicon wafer can be effectively evaluated.

The application relates to a navigation information extraction method and system for optical autonomous navigation. The navigation information extraction method comprises the following steps: S1. edge detection is performed on a celestial body target image; S2. celestial body texture suppression is performed based on the edge detection result; and S3. a least square circle fitting method is used to extract a celestial body center position as navigation information. The application provides a center position information extraction method for a rich-texture celestial body target, can solve the false edges such as the morning and evening twilight lines and textures in the image processing process of the rich-texture celestial body target, is suitable for non-complete celestial body target images, has a high edge detection rate, has good edge continuity, and has a good contour fitting effect on a small-arc celestial body target.

The application provides a circle fitting and detection method and device, electronic equipment and readable storage medium, wherein the method comprises: collecting a plurality of edge points of a target object to be fitted in a target image; fitting a preset number of edge points in the plurality of edge points as a reference circle; calculating a distance difference between other edge points outside the fitted reference circle and the reference circle; fitting the edge points with a distance difference not higher than a distance threshold as a candidate circle; and determining a fitting circle of the target object to be fitted according to the candidate circle. After the reference circle is determined, the application determines outliers according to the distance difference between other edge points outside the fitted reference circle and the reference circle, and the outliers are excluded when the target object to be fitted is fitted, so that the interference of the outliers on the circle fitting result is eliminated, and the circle fitting accuracy is improved.

The invention discloses a vision measurement method based on STP model coordinate calibration, which comprises the following steps of: analyzing geometric features of an STP model to extract a measurement datum point and import tolerance information of the features, and then constructing a unified transformation relationship among an STP model coordinate system, a movement mechanism coordinate system and a camera coordinate system by adopting multi-point calibration, mapping from a model coordinate to an actual measurement coordinate and a measured feature under a camera pixel coordinate system is realized, and a detection path and a camera photographing pose are planned based on the model feature, so that automatic vision measurement of multiple features on a workpiece is realized; in the image processing stage, gray threshold segmentation is carried out by using the standard height of geometric features, the bottom surface and the feature surface of a workpiece are distinguished, the dimensions, heights and other parameters of template features are obtained by combining Blob region growth median feature extraction, circle fitting, plane fitting and other algorithms, and finally, the measurement result is compared with the standard tolerance of the model, so that the accuracy of the measurement result is improved. And outputting a detection report and deviation statistics.

The invention provides a method and device for detecting a cylinder in a point cloud and electronic equipment, and the method comprises the steps: projecting a three-dimensional point in the point cloud to a projection plane perpendicular to an axis through detecting the axis of the cylinder in the point cloud, and obtaining a projection point; and performing down-sampling processing on the projection points, and setting a mark number corresponding relation for each projection point after down-sampling. According to the invention, multiple circle fitting operations are executed, and each circle fitting is executed by using the projection point on the circle during the previous circle fitting, so that the precision of circle fitting is improved, and the precision of final cylinder detection is further improved. Besides, the mark number corresponding relation is established, so that the three-dimensional points before projection can be directly found based on the mark number corresponding relation under the condition that the circle is detected, the points on the cylindrical surface can be accurately positioned, the implementation process is more simplified, and the detection result is more accurate.

The invention relates to a rotating shaft calibration method and system for laser five-axis equipment, and the method comprises the steps: carrying out the detection of N azimuth positions of correction balls at different positions on a rotating shaft at different angles through a probe, so as to obtain the position coordinates of the corresponding correction balls, dividing the rotating shaft according to a preset equal interval angle, calculating a first sphere center position coordinate of a first correction sphere and a second sphere center position coordinate of a second correction sphere of the rotating shaft under each equant angle, performing circle fitting to obtain a first fitting circle and a second fitting circle, and calculating a rotation vector of the rotating shaft according to the circle centers of the two fitting circles, updating the current position coordinate of the machine tool according to the rotation vector and the current position coordinate of the rotating shaft, and correcting the current position coordinate of the rotating shaft according to the updated position coordinate of the machine tool, thereby realizing calibration based on the corrected position coordinate of the rotating shaft. Therefore, the calibration precision and efficiency of the rotating shaft are improved.

The invention discloses an automatic docking method based on point cloud registration visual servo, and the method comprises the steps: carrying out the automatic docking of a subject end and an object end of a circular docking port, generating a pin region mask at a docking part through fusing the features of an RGB image and an absolute phase diagram, and guiding the calculation of a structured light three-dimensional coordinate according to the pin region mask. Meanwhile, an edge sampling method based on spatial distribution and normal distribution is adopted to extract pin outer ring point cloud, and high-precision pose solving is achieved through an improved RANSAC spatial circle fitting method. The invention provides a feasible and efficient technical scheme for the practical application of the automatic docking technology.

This invention relates to the field of precision measurement technology, and more particularly to a method and system for measuring the diameter of a test tube. The method includes: acquiring point cloud data of the cross-sectional profile of the test tube and splitting it into a test tube surface point set and a label surface point set; calculating the diameter of the test tube after performing optimal circle fitting using an improved bee colony algorithm. The optimal circle fitting using the improved bee colony algorithm includes: A10, defining the objective function and initializing the food source population and parameters; A20, sequentially executing the hired bee stage and the observation bee stage, updating the food sources and their corresponding stagnation counts; A30, entering the scout bee stage, checking the stagnation count of each food source, initializing food sources with stagnation counts exceeding the abandonment threshold according to a mixing strategy, and updating the food source population; A40, incrementing the current iteration count by 1 and returning to step A20, until the iteration termination condition is met. This invention improves the accuracy of test tube diameter measurement.

The application discloses a multi-class circle special-shaped target resisting heart drift and a binocular vision positioning method thereof, and belongs to the technical field of industrial vision measurement and precision positioning. The target comprises a white background substrate and seven symmetrical black circles, wherein a large circle is arranged at the center, a standard normal small circle is arranged above and below the large circle respectively, and four specially-made class circles are arranged at four corners respectively. The specially-made class circles are designed according to a cylindrical surface nonlinear projection formula. The positioning method comprises the following steps: a binocular camera collects a target image and extracts two-dimensional circle center coordinates; three-dimensional point clouds are solved through stereo matching; a cylindrical space axial vector is extracted and a normal plane is constructed, and three-dimensional feature points are orthogonally projected to the normal plane for two-dimensional circle fitting; and the coordinates of an internal anchor cylinder center and a surface highest axial reference point are solved through coordinate inverse transformation. The application effectively overcomes positioning errors caused by cylindrical curvature deformation, space inclination and rotation around an axis, and significantly improves the positioning robustness and universality under complex working conditions.

The invention relates to a borehole video image expansion method and device, and the method comprises the steps: carrying out the denoising and edge enhancement processing of a borehole image through a deep learning model, and obtaining a processed image; performing circle fitting on the basis of the drilling hole edge data points in the processed image to obtain a fitting circle, and determining the circle center and the radius of the fitting circle; calculating the distance between the center of the fitting circle and each boundary of the processed image, and determining the minimum value of all the distances; the image expansion area is an annular area, namely the annular area with the radius as the inner diameter and the minimum value as the outer diameter; and converting each coordinate point in the annular region into a coordinate point corresponding to the rectangular expanded image, and determining the pixel value of the coordinate point corresponding to the rectangular expanded image according to the pixel value of each coordinate point in the annular region. According to the method, denoising and edge extraction are carried out on the drilling video image, and when drilling hole circle fitting is carried out, an accurate image expansion result can be obtained based on an interior point majority principle.

The invention relates to a multi-data alignment method for industrial robot paths, and belongs to the field of industrial robots, and the method comprises the steps: collecting the trajectory data of an industrial robot, and carrying out the path length calculation: employing a three-point circle fitting method for distinguishing to obtain a straight line segment and an arc line segment, calculating the distance between adjacent points of the straight line section by adopting an Euclidean distance calculation method, calculating the distance between adjacent points of the arc section by adopting an arc calculation method, and accumulating to obtain the total path length; normalizing the completed path length corresponding to each sampling point relative to the total path length, and mapping the time anchor point of the data of each sampling point to a path completion degree space in a [0, 1] interval; and performing alignment and matching on data of different data sources in the path completion degree space by adopting a hybrid interpolation method so as to realize alignment and matching of various data in the path completion degree space. The method provided by the invention can accurately identify and correct the trajectory error, thereby realizing trajectory tracking with higher precision.

The invention relates to a multi-arc-segment symmetric structural member measurement system, method and device and a storage medium. The system comprises an OCT image acquisition device, a contour extraction module, a curve analysis module and a circle fitting module, the OCT image acquisition device is used for acquiring an original tomographic image of a to-be-detected sample by utilizing an OCT imaging technology, and the contour extraction module is used for extracting surface contour features of the preprocessed image by adopting morphology and a connected region processing algorithm; the curve analysis module is used for performing curvature analysis and segmental arc identification on the surface contour features based on a differential geometry principle and a multi-scale analysis method, and the circle fitting module is used for performing geometric analysis on segmental arc segmentation results by combining algebraic fitting and geometric fitting algorithms, judging the opening direction of each segmental arc and generating circle fitting parameters. According to the invention, an end-to-end automatic measurement process is formed by using an integrated design, the operation cost and time consumption are reduced, and the measurement precision, efficiency and reliability are improved.

This invention relates to a method and system for extracting anchor drill hole contours based on contour geometric constraints. The method includes: acquiring an image of an anchor drill hole on a steel strip using a camera; preprocessing the image; determining the image edge information of the preprocessed anchor drill hole image using the Canny edge detection method; determining the upper and lower edge straight line information of the steel strip in the image based on the image edge information and using the Hough line detection method, and taking the upper and lower edge straight line information of the steel strip in the image as the region of interest; determining a circular contour within the region of interest using a circle fitting method; and determining the anchor drill hole contour based on the circular contour and contour geometric constraints. The contour geometric constraints are a functional relationship between the distance between the camera and the steel strip and the radius of the anchor drill hole. This invention can improve the accuracy of anchor drill hole contour extraction.

The application discloses an axial slice-based underground mine pipeline point cloud completion method, relates to the technical field of point cloud data processing, and is used for data completion of pipeline point cloud, and comprises the following steps: slicing a pipeline point cloud data after preprocessing along an axial direction, reducing three-dimensional point cloud to two-dimensional plane processing, calculating related geometric parameters of the pipeline, extracting a pipeline center line based on improved DBSCAN clustering and least square circle fitting, constructing a skeleton model under geometric topological constraints, combining local geometric features and global topological constraints, realizing geometric reconstruction of a missing area through a rotary surface generation and local interpolation algorithm, and realizing robust repair of the missing area. The application extracts the pipeline center line and geometric parameters in combination with a convex hull and a RANSAC method, realizes completion of the pipeline point cloud data through a continuous rotation correction method, and significantly improves the completion quality of the pipeline point cloud.