Camera calibration method, system and device based on image processing

Abstract

The invention discloses a camera calibration method, system and device based on image processing, and the method comprises the steps: obtaining a calibration plate image at multiple angles, and carrying out the image preprocessing, and obtaining a calibration plate coordinate; performing distortion removal and coordinate transformation on the calibration plate coordinates to obtain first calibration plate coordinates and second calibration plate coordinates, further obtaining calibration plate attitude transformation data, and obtaining first coordinates in a coordinate system of the image acquisition device through coordinate transformation; the translation amount of the calibration plate is obtained, a fitting plane and a fitting transformation matrix are obtained through fitting, the first coordinates are projected to the horizontal plane and fitted, the circle center coordinates of the horizontal circle face are obtained, and then the fitting circle center coordinates are obtained; obtaining a normal vector of a fitting plane, and combining the fitting circle center coordinate to obtain a rotating shaft linear equation; and based on the rotating shaft linear equation and the fitting plane, obtaining the motion radius and the height of the image acquisition device. Through the image processing technology, the accuracy of camera calibration is improved, and the working efficiency and the data reliability are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to a camera calibration method, system and device based on image processing. Background Art

[0002] Camera calibration is the basic link of machine vision applications such as visual measurement and 3D reconstruction. It is widely used in machine vision systems, advanced robot navigation, industrial inspection, and complex historical building digitization projects. It is an important tool in modern industry, scientific research, and cultural heritage protection. Machine vision applications rely on high-precision imaging and accurate geometric data acquisition, and camera calibration plays a key role. The accuracy and precision of the camera calibration results directly determine whether the machine vision system can work normally and accurately.

[0003] Traditional camera calibration relies on manual angle and position adjustment, which is not only time-consuming but also easily affected by the operator's subjective influence. In addition, environmental factors such as light changes, reflections, and object occlusions will greatly affect the accuracy of camera calibration. When information such as the camera position changes, manual calibration is required again. The process is cumbersome and wastes a lot of human resources, affecting the efficiency of the camera calibration method. In addition, due to the randomness and uncertainty of manual angle adjustment, it is difficult to fit the trajectory of the calibration plate, affecting the accuracy of camera calibration.

[0004] With the development of science and technology, camera calibration technology has gradually been realized through image processing and other technologies, and has achieved remarkable results. However, due to the inaccuracy of some processing steps in the image acquisition and calibration process, there are still large errors that lead to inaccurate calibration results. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a camera calibration method, system and device based on image processing.

[0006] In order to solve the above technical problems, the present invention is solved by the following technical solutions: A camera calibration method based on image processing comprises the following steps: The calibration plate is driven to rotate by the turntable with the rotation axis as the rotation center, and the calibration plate images containing the calibration points under multiple angles are acquired by the image acquisition device, and the calibration plate images are preprocessed to obtain the calibration plate coordinates, wherein the image acquisition device includes an image acquisition device, a rotation axis and a turntable, and the rotation axis is perpendicular to the turntable, and the calibration plate is preset with the calibration points and the calibration plate is placed vertically on the turntable; Obtaining distortion parameters and internal parameters of the image acquisition device, dedistorting and standardizing the calibration plate coordinates using the distortion parameters and internal parameters of the image acquisition device, obtaining the first calibration plate coordinates and performing coordinate transformation to obtain the second calibration plate coordinates; Performing posture analysis on the calibration plate based on the first calibration plate coordinates and the second calibration plate coordinates to obtain calibration plate posture transformation data, and performing coordinate transformation on the first calibration plate coordinates based on the calibration plate posture transformation data to obtain a first coordinate in the image acquisition device coordinate system; Based on the calibration plate posture transformation data, the position of the calibration plate translated in the image acquisition device coordinate system is analyzed to obtain the calibration plate translation amount and perform fitting to obtain a fitting plane and a fitting transformation matrix; based on the fitting transformation matrix, the first coordinate is projected onto the horizontal plane and performed fitting to obtain the center coordinate of the horizontal circular plane; the center coordinate of the horizontal circular plane is reversely projected onto the fitting plane through the fitting transformation matrix to obtain the fitting center coordinate; Obtain the normal vector of the fitting plane, and obtain the equation of the rotation axis line based on the normal vector of the fitting plane and the coordinates of the center of the fitting circle; Based on the origin of the image acquisition device coordinate system, the fitting plane and the straight line equation of the rotation axis, the movement radius of the image acquisition device and the height of the image acquisition device are obtained.

[0007] As an implementable method, performing image preprocessing on the calibration plate image to obtain the calibration plate coordinates includes the following steps: Performing grayscale processing on the calibration plate image to obtain a calibration plate grayscale image, and performing downsampling processing on the calibration plate grayscale image to obtain a calibration plate downsampled image; Based on the downsampled image of the calibration plate, the calibration points are identified and marked to obtain the coordinates of the calibration points in the calibration plate; The calibration point coordinates are screened and sorted by the relevant parameters of the calibration plate to obtain the position coordinates of the calibration plate; The calibration plate position coordinates are mapped to the calibration plate grayscale image to obtain the calibration plate mapping coordinates, and the calibration plate mapping coordinates are sub-pixel detected to obtain the calibration plate coordinates.

[0008] As an implementable embodiment, the first calibration plate coordinates and the second calibration plate coordinates are obtained by the following steps: De-distorting the calibration plate coordinates based on the distortion parameters to obtain de-distorted calibration plate coordinates; Based on the internal parameters of the image acquisition device, the coordinates of the dedistorted calibration plate are transformed into a normalized coordinate system to obtain the coordinates of the first calibration plate; A calibration plate coordinate system is established based on the calibration plate position, and the calibration plate coordinates are converted to the calibration plate coordinate system to obtain the second calibration plate coordinates.

[0009] As an implementable method, the step of obtaining the first coordinate in the image acquisition device coordinate system includes the following steps: Based on the coordinates of the first calibration plate and the corresponding coordinates of the second calibration plate, the rotation transformation and translation transformation of the calibration plate in the coordinate system of the image acquisition device are analyzed by direct linear transformation to obtain initial calibration plate posture transformation data; Based on the initial calibration plate posture transformation data and optimizing the reprojection error, the calibration plate posture transformation data is obtained, wherein the calibration plate posture transformation data includes the calibration plate posture rotation data and the calibration plate posture translation data, and the reprojection error represents the error between the second calibration plate coordinates and the first calibration plate coordinates after being projected to the image coordinate system through the initial calibration plate posture transformation data; The first calibration plate coordinates are rotated and translated by the calibration plate posture rotation data and the calibration plate posture translation data, and the first calibration plate coordinates are converted to the image acquisition device coordinate system to obtain the first coordinates.

[0010] As an implementable method, obtaining the fitting plane and the fitting transformation matrix includes the following steps: Construct the design matrix and target vector, which are expressed as follows:

[0011]

[0012] Based on the design matrix and the target vector, the least square method is used to solve the parameters, and the fitting plane is constructed. The fitting plane is projected onto the horizontal plane to obtain the fitting transformation matrix, which is expressed as follows:

[0013]

[0014] in, represents the design matrix, represents the target vector, represents the fitting plane parameters, represents the horizontal axis, represents the vertical coordinate, represents the vertical coordinate, Represents the coefficient.

[0015] As an implementable method, the coordinates of the fitting circle center are obtained by the following steps: Based on the fitting transformation matrix, the first coordinate is projected onto the horizontal plane to obtain the horizontal coordinate of the first coordinate, and the horizontal design matrix and horizontal target vector are constructed, which are expressed as follows:

[0016]

[0017] Based on the horizontal design matrix and the horizontal target vector, the parameters are solved, and the horizontal coordinates of the first coordinate are fitted to obtain the coordinates of the center of the horizontal circular surface. The parameter solution is expressed as follows:

[0018] Based on the fitting transformation matrix, the center coordinates of the horizontal circular surface are reversely projected to obtain the fitting center coordinates; in, represents the horizontal design matrix, represents the horizontal target vector, Represents the parameters of the horizontal circular surface, represents the horizontal axis, represents the vertical coordinate, Indicates the vertical coordinate.

[0019] As an implementable method, based on the positional relationship between the rotating shaft and the calibration plate, the straight line equation of the rotating shaft is obtained by fitting the normal vector of the plane and the coordinates of the center of the circle, which is expressed as follows:

[0020] in, represents the horizontal coordinate of the center of the fitted circle, represents the ordinate of the center of the fitted circle, represents the vertical coordinate of the center of the fitted circle, represents the normal vector of the fitted plane, represents the horizontal axis, represents the vertical coordinate, Indicates the vertical coordinate.

[0021] As an implementable method, obtaining the image acquisition device movement radius and the image acquisition device height based on the origin of the image acquisition device coordinate system, the fitting plane and the rotation axis straight line equation includes the following steps: Based on the image acquisition device coordinate system and the axis straight line equation, the distance between the origin of the image acquisition device coordinate system and the axis straight line equation is calculated to obtain the image acquisition device motion radius, which is expressed as follows:

[0022] Based on the image acquisition device coordinate system and the fitting plane, the distance from the origin of the image acquisition device coordinate system to the fitting plane is calculated to obtain the height of the image acquisition device, which is expressed as follows:

[0023] in, represents the motion radius of the image acquisition device, represents the normal vector of the fitted plane, represents the coordinates of the center of the fitting circle, Indicates the height of the image acquisition device, Represents the parameters of the fitted plane.

[0024] A camera calibration system based on image processing, comprising an image preprocessing module, a data processing module, a data transformation module, a data fitting module, a fitting analysis module and a data calculation module; The image preprocessing module uses the rotating shaft as the rotation center, drives the calibration plate to rotate through the turntable, obtains the calibration plate image containing the calibration points at multiple angles through the image acquisition device, performs image preprocessing on the calibration plate image, and obtains the calibration plate coordinates, wherein the image acquisition device includes an image acquisition device, a rotating shaft and a turntable, and the rotating shaft is perpendicular to the turntable, the calibration plate is preset with the calibration points, and the calibration plate is placed vertically on the turntable; The data processing module obtains the distortion parameters and the internal parameters of the image acquisition device, performs dedistortion and coordinate standardization processing on the calibration plate coordinates by using the distortion parameters and the internal parameters of the image acquisition device, obtains the first calibration plate coordinates, performs coordinate transformation, and obtains the second calibration plate coordinates; The data transformation module performs posture analysis on the calibration plate based on the first calibration plate coordinates and the second calibration plate coordinates to obtain calibration plate posture transformation data, and performs coordinate transformation on the first calibration plate coordinates based on the calibration plate posture transformation data to obtain a first coordinate in the image acquisition device coordinate system; The data fitting module analyzes the position of the calibration plate translated in the coordinate system of the image acquisition device based on the calibration plate posture transformation data, obtains the calibration plate translation amount and performs fitting, obtains the fitting plane and the fitting transformation matrix, projects the first coordinate to the horizontal plane based on the fitting transformation matrix and performs fitting, obtains the center coordinate of the horizontal circular plane, and reversely projects the center coordinate of the horizontal circular plane to the fitting plane through the fitting transformation matrix to obtain the fitting center coordinate; The fitting analysis module obtains the normal vector of the fitting plane, and obtains the straight line equation of the rotation axis based on the normal vector of the fitting plane and the coordinates of the center of the fitting circle; The data calculation module obtains the motion radius and height of the image acquisition device based on the origin of the image acquisition device coordinate system, the fitting plane and the straight line equation of the rotation axis.

[0025] As an implementable embodiment, the data fitting module is configured as follows: Construct the design matrix and target vector, which are expressed as follows:

[0026]

[0027] Based on the design matrix and the target vector, the least square method is used to solve the parameters, and the fitting plane is constructed. The fitting plane is projected onto the horizontal plane to obtain the fitting transformation matrix, which is expressed as follows:

[0028]

[0029] in, represents the design matrix, represents the target vector, represents the fitting plane parameters, represents the horizontal axis, represents the vertical coordinate, represents the vertical coordinate, represents the coefficient; The coordinates of the center of the fitting circle are obtained by the following steps: Based on the fitting transformation matrix, the first coordinate is projected onto the horizontal plane to obtain the horizontal coordinate of the first coordinate, and the horizontal design matrix and horizontal target vector are constructed, which are expressed as follows:

[0030]

[0031] Based on the horizontal design matrix and the horizontal target vector, the parameters are solved, and the horizontal coordinates of the first coordinate are fitted to obtain the coordinates of the center of the horizontal circular surface. The parameter solution is expressed as follows:

[0032] Based on the fitting transformation matrix, the center coordinates of the horizontal circular surface are reversely projected to obtain the fitting center coordinates; in, represents the horizontal design matrix, represents the horizontal target vector, Represents the parameters of the horizontal circular surface, represents the horizontal axis, represents the vertical coordinate, Indicates the vertical coordinate.

[0033] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following method is implemented: The calibration plate is driven to rotate by the turntable with the rotation axis as the rotation center, and the calibration plate images containing the calibration points under multiple angles are acquired by the image acquisition device, and the calibration plate images are preprocessed to obtain the calibration plate coordinates, wherein the image acquisition device includes an image acquisition device, a rotation axis and a turntable, and the rotation axis is perpendicular to the turntable, and the calibration plate is preset with the calibration points and the calibration plate is placed vertically on the turntable; Obtaining distortion parameters and internal parameters of the image acquisition device, dedistorting and standardizing the calibration plate coordinates using the distortion parameters and internal parameters of the image acquisition device, obtaining the first calibration plate coordinates and performing coordinate transformation to obtain the second calibration plate coordinates; Performing posture analysis on the calibration plate based on the first calibration plate coordinates and the second calibration plate coordinates to obtain calibration plate posture transformation data, and performing coordinate transformation on the first calibration plate coordinates based on the calibration plate posture transformation data to obtain a first coordinate in the image acquisition device coordinate system; Based on the calibration plate posture transformation data, the position of the calibration plate translated in the image acquisition device coordinate system is analyzed to obtain the calibration plate translation amount and perform fitting to obtain a fitting plane and a fitting transformation matrix; based on the fitting transformation matrix, the first coordinate is projected onto the horizontal plane and performed fitting to obtain the center coordinate of the horizontal circular plane; the center coordinate of the horizontal circular plane is reversely projected onto the fitting plane through the fitting transformation matrix to obtain the fitting center coordinate; Obtain the normal vector of the fitting plane, and obtain the equation of the rotation axis line based on the normal vector of the fitting plane and the coordinates of the center of the fitting circle; Based on the origin of the image acquisition device coordinate system, the fitting plane and the straight line equation of the rotation axis, the movement radius of the image acquisition device and the height of the image acquisition device are obtained.

[0034] A camera calibration device based on image processing includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the following method when executing the computer program: The calibration plate is driven to rotate by the turntable with the rotation axis as the rotation center, and the calibration plate images containing the calibration points under multiple angles are acquired by the image acquisition device, and the calibration plate images are preprocessed to obtain the calibration plate coordinates, wherein the image acquisition device includes an image acquisition device, a rotation axis and a turntable, and the rotation axis is perpendicular to the turntable, and the calibration plate is preset with the calibration points and the calibration plate is placed vertically on the turntable; Obtaining distortion parameters and internal parameters of the image acquisition device, dedistorting and standardizing the calibration plate coordinates using the distortion parameters and internal parameters of the image acquisition device, obtaining the first calibration plate coordinates and performing coordinate transformation to obtain the second calibration plate coordinates; Performing posture analysis on the calibration plate based on the first calibration plate coordinates and the second calibration plate coordinates to obtain calibration plate posture transformation data, and performing coordinate transformation on the first calibration plate coordinates based on the calibration plate posture transformation data to obtain a first coordinate in the image acquisition device coordinate system; Based on the calibration plate posture transformation data, the position of the calibration plate translated in the image acquisition device coordinate system is analyzed to obtain the calibration plate translation amount and perform fitting to obtain a fitting plane and a fitting transformation matrix; based on the fitting transformation matrix, the first coordinate is projected onto the horizontal plane and performed fitting to obtain the center coordinate of the horizontal circular plane; the center coordinate of the horizontal circular plane is reversely projected onto the fitting plane through the fitting transformation matrix to obtain the fitting center coordinate; Obtain the normal vector of the fitting plane, and obtain the equation of the rotation axis line based on the normal vector of the fitting plane and the coordinates of the center of the fitting circle; Based on the origin of the image acquisition device coordinate system, the fitting plane and the straight line equation of the rotation axis, the movement radius of the image acquisition device and the height of the image acquisition device are obtained.

[0035] The present invention has significant technical effects due to the adoption of the above technical solution: The present invention obtains calibration plate images containing calibration points at multiple angles through an image acquisition device, and obtains parameters of the image acquisition device by detecting and analyzing the calibration plate images through coordinate fitting. This realizes efficient automatic acquisition and analysis of images. At the same time, this method is based on fitting based on the coordinate data of multiple calibration plates, effectively improving the efficiency and reliability of the image acquisition device calibration method. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0037] Figure 1 It is a schematic flow diagram of the method of the present invention; Figure 2 It is an overall schematic diagram of the system of the present invention; Figure 3 is a schematic diagram of an image acquisition device in the method of the present invention; Figure 4 It is a schematic diagram of the image preprocessing process of the present invention; Figure 5 It is a schematic diagram of a fitting circle in the method of the present invention; Figure 6 It is a schematic diagram of parameter calculation of the present invention. DETAILED DESCRIPTION

[0038] The present invention is further described in detail below in conjunction with embodiments. The following embodiments are for explanation of the present invention but the present invention is not limited to the following embodiments.

[0039] Embodiment 1: A camera calibration method based on image processing, such as Figure 1 As shown, the following steps are included: S100, with the rotating shaft as the rotation center, the calibration plate is driven to rotate by the turntable, and the calibration plate images containing the calibration points under multiple angles are acquired by the image acquisition device, and the calibration plate images are image preprocessed to obtain the calibration plate coordinates, wherein the image acquisition device includes an image acquisition device, a rotating shaft and a turntable, and the rotating shaft is perpendicular to the turntable, and the calibration plate is preset with the calibration points and the calibration plate is placed vertically on the turntable; S200, obtaining distortion parameters and internal parameters of the image acquisition device, performing dedistortion and coordinate standardization processing on the calibration plate coordinates by using the distortion parameters and the internal parameters of the image acquisition device, obtaining the first calibration plate coordinates, and performing coordinate transformation to obtain the second calibration plate coordinates; S300, performing posture analysis on the calibration plate based on the first calibration plate coordinates and the second calibration plate coordinates to obtain calibration plate posture transformation data, and performing coordinate transformation on the first calibration plate coordinates based on the calibration plate posture transformation data to obtain a first coordinate in the image acquisition device coordinate system; S400, analyzing the position of the calibration plate translated in the coordinate system of the image acquisition device based on the calibration plate posture transformation data, obtaining the calibration plate translation amount and performing fitting, obtaining a fitting plane and a fitting transformation matrix, projecting the first coordinate onto a horizontal plane based on the fitting transformation matrix and performing fitting, obtaining the center coordinate of the horizontal circular plane, and reversely projecting the center coordinate of the horizontal circular plane onto the fitting plane through the fitting transformation matrix to obtain the fitting center coordinate; S500, obtaining a normal vector of the fitting plane, and obtaining a straight line equation of the rotation axis based on the normal vector of the fitting plane and the coordinates of the center of the fitting circle; S600: Based on the origin of the image acquisition device coordinate system, the fitting plane and the straight line equation of the rotation axis, the movement radius of the image acquisition device and the height of the image acquisition device are obtained.

[0040] The present invention adopts a high-resolution image acquisition device, and realizes efficient capture of multi-view images of a calibration plate through automated image acquisition. The coordinates of the calibration plate in the coordinate system of the image acquisition device are obtained by automated image processing and coordinate analysis of the calibration plate image, thereby locating the relative position of the image acquisition device and the calibration plate. At the same time, circular plane fitting is performed based on the coordinate data of multiple calibration plates to complete the calibration of the image acquisition device. This process further optimizes the calibration process of the image acquisition device.

[0041] This embodiment provides an image acquisition device, wherein the image acquisition device is a camera, and the image acquisition device is as follows: Figure 3As shown, it includes a calibration plate, a rotating shaft, a turntable, a motor and a camera. In applications such as machine vision, image measurement, photogrammetry, and 3D reconstruction, the calibration plate is used to correct lens distortion; determine the conversion relationship between physical size and pixels; and determine the relationship between the 3D geometric position of a point on the surface of a space object and its corresponding point in the image. It is necessary to establish a geometric model of camera imaging. The flat plate with a fixed-pitch pattern array is the calibration plate. The fixed-pitch pattern array here can be understood as a preset calibration point. Among them, the motor is connected to the rotating shaft or the motor acts on the rotating shaft, the turntable is driven to rotate by the rotating shaft, the calibration plate is placed above the turntable and perpendicular to the turntable, and during the image acquisition process, the turntable is driven by the motor to rotate the calibration plate, the camera is placed on one side of the turntable through a fixed mounting structure or a tripod, the camera is aimed at the turntable area, ensuring that the camera can fully observe the turntable and the objects on the turntable, adjust the camera focal length and aperture and calibrate the camera, place the calibration plate of known specifications vertically on the turntable surface, and ensure that the calibration plate is away from the center of the rotating shaft of the turntable, so as to achieve the purpose of obtaining a larger calibration plate trajectory circle and improve the accuracy of the fitting trajectory circle.

[0042] This method does not limit the rotation angle of the calibration plate during image acquisition. In this embodiment, an image acquisition method is provided. When acquiring images through an image acquisition device, first, the motor speed and the camera acquisition frequency are adjusted. For example, if the motor rotates once in 30 seconds, the camera takes about 60 images of the calibration plate. In this embodiment, the rotation angle of the calibration plate is 360°. The number of calibration plate images that can be taken by the camera when the motor rotates once per unit time is calculated, and the camera and the motor are triggered synchronously to screen the acquired images to ensure that the images taken by the camera do not have ghosting, blurring, and other problems. About 15 complete and clear calibration plate images taken by the camera are obtained, and the equivalent motor rotation angle is about 90°.

[0043] The image preprocessing is performed on the calibration plate image obtained after being collected and screened by the image acquisition device, including the following steps: Step 1: Collect the calibration plate image Perform grayscale processing to obtain the grayscale image of the calibration plate ; Step 2: Downsample the grayscale image of the calibration plate to improve the efficiency of calibration plate recognition and feature detection, and obtain the downsampled image of the calibration plate. ; Step 3: In this embodiment, the calibration plate downsampled image is identified by corner point detection, all possible corner points in the calibration plate downsampled image are preliminarily detected, the detected calibration plate corner points are marked, the calibration plate corner points are screened based on the actual structure information of the calibration plate, and the calibration plate position coordinates are output in order from left to right and from top to bottom; Step 4: Map the calibration plate position coordinates to the calibration plate grayscale image through coordinates, perform an iterative search in the neighborhood of the high-resolution feature coordinates according to the grayscale centroid theory, perform sub-pixel detection on the calibration plate position coordinates mapped to the calibration plate grayscale image, and obtain the calibration plate coordinates; The image preprocessing flowchart is as follows Figure 4 As shown, the high-resolution image represents the grayscale image of the calibration plate, the low-resolution image feature point detection in this embodiment means corner point detection on the downsampled image of the calibration plate, and the high-resolution image feature point detection means mapping the position coordinates of the calibration plate to the grayscale image of the calibration plate and performing sub-pixel detection.

[0044] The pseudo code for the image preprocessing step is as follows: 1 function processCalibrationBoardImages(ImageSet) 2for each Image in ImageSet 3I_gray = convertToGrayScale(Image) 4I_resize = downSample(I_gray) 5if detectCalibrationBoard(I_resize) 6p_2d = detectFeaturePoints(I_resize) 7p_subpixel = mapAndSubpixelDetect(p_2d, I_gray) 8store p_subpixel in Results 9return Results 10 function convertToGrayScale(Image) 11return grayscale version of Image 12 function downSample(I_gray) 13return lower resolution version of I_gray for efficiency 14 function detectCalibrationBoard(I_resize) 15if calibration board found in I_resize 16return true 17else 18return false 19 function detectFeaturePoints(I_resize) 20return list of feature point coordinates in I_resize 21 function mapAndSubpixelDetect(p_2d, I_gray) 22p_highRes = mapCoordinatesToHighRes(p_2d, I_gray) 23return subpixelAccuracyDetection(p_highRes, I_gray) 24 function mapCoordinatesToHighRes(p_2d, I_gray) 25calculate high resolution coordinates from p_2d based on I_graydimensions 26return high resolution coordinates 27 function subpixelAccuracyDetection(p_highRes, I_gray) 28perform subpixel refinement on p_highRes using I_gray 29return subpixel refined coordinates in, represents the input calibration plate image set, represents the calibration plate image, represents the grayscale image of the calibration plate, represents the downsampled image of the calibration plate, Indicates the position coordinates of the calibration plate, represents the coordinates of the calibration plate, represents the result set of each processing step, Represents the calibration plate position coordinates mapped back to the calibration plate grayscale image, Represents the main function, which is used to process the calibration plate image set and detect the calibration plate and calibration points. Represents a function that converts the input image into a grayscale image. represents the downsampling function, which reduces the image size to improve processing efficiency. Represents the calibration plate function in the detection calibration plate image, Indicates detecting the calibration plate image and performing calibration plate detection. Indicates mapping the feature point coordinates to the grayscale image of the calibration plate and performing sub-pixel detection. Indicates mapping the feature point coordinates to the grayscale image of the calibration plate. It indicates that sub-pixel level calibration point accuracy detection is performed on the grayscale image of the calibration plate.

[0045] In step S200, the distortion parameters and the internal parameters of the image acquisition device are obtained, and the calibration plate coordinates are dedistorted and the coordinates are standardized by the distortion parameters and the internal parameters of the image acquisition device to obtain the first calibration plate coordinates and perform coordinate transformation to obtain the second calibration plate coordinates, including the following steps: S210: Initialize based on the image acquisition device to obtain distortion parameters And image acquisition device internal parameters ; The distortion parameters are used to eliminate the error caused by the deviation of pixel points from their ideal positions due to system design, production and assembly in the image acquisition device. The distortion includes radial distortion and tangential distortion. The radial distortion is caused by the fact that light is more bent away from the center of the image acquisition device than near the center, and the tangential distortion is caused by the fact that the image acquisition device is not completely parallel to the image plane. The internal parameters of the image acquisition device are parameters that describe the internal properties of the image acquisition device, including the actual physical value represented by the horizontal pixel, the actual physical value represented by the vertical pixel, the number of horizontal pixels between the image center pixel coordinates and the origin coordinates, the number of vertical pixels between the image center pixel coordinates and the origin coordinates, the focal length of the image acquisition device, and the distance from the pixel point to the image center point. S220: De-distorting the calibration plate coordinates by using the distortion parameters to eliminate the influence of the image acquisition device on the calibration plate image, thereby obtaining de-distorted calibration plate coordinates; S230: Based on the coordinates of the dedistortion calibration plate and the internal parameters of the image acquisition device , normalize the coordinates of the dedistorted calibration plate, wherein the normalization process means converting the coordinates of the calibration plate to the normalized coordinate system of the image acquisition device to obtain the first calibration plate coordinates ,The normalized coordinate system of the image acquisition device refers to a special form of the coordinate system of the image acquisition device, which removes the depth information and only retains the direction information; S240: In this embodiment, define any point where the calibration plate contacts the turntable as the origin of the calibration plate coordinate system. , convert the calibration plate coordinates obtained by detection into the calibration plate coordinate system to obtain the second calibration plate coordinates .

[0046] In step S300, the calibration plate is subjected to posture analysis based on the first calibration plate coordinates and the second calibration plate coordinates to obtain calibration plate posture transformation data, and the first calibration plate coordinates are subjected to coordinate transformation based on the calibration plate posture transformation data to obtain the first coordinates in the image acquisition device coordinate system, including the following steps: S310: In this embodiment, the posture transformation of the calibration plate in the image acquisition device coordinate system is analyzed by direct linear transformation. The posture transformation includes rotation transformation and translation transformation. The initial calibration plate posture transformation data is obtained. The initial calibration plate posture transformation data is optimized by using an optimization algorithm. In this embodiment, the initial calibration plate posture transformation data is optimized by minimizing the reprojection error. The reprojection error represents the error between the coordinates of the second calibration plate after being projected to the image coordinate system through the initial calibration plate posture transformation data and the coordinates of the first calibration plate. Fine adjustment of the rotation transformation and the translation transformation is achieved to obtain the calibration plate posture transformation data; S320: performing rotation transformation and translation transformation on the first calibration plate coordinates according to the calibration plate posture rotation data and the calibration plate posture translation data in the calibration plate posture transformation data, so as to obtain the first coordinates in the image acquisition device coordinate system.

[0047] In step S400, the position of the calibration plate translated in the coordinate system of the image acquisition device is analyzed based on the calibration plate posture transformation data, the calibration plate translation amount is obtained and fitted, a fitting plane and a fitting transformation matrix are obtained, the first coordinate is projected onto the horizontal plane based on the fitting transformation matrix and fitted, the center coordinate of the horizontal circular plane is obtained, and the center coordinate of the horizontal circular plane is reversely projected onto the fitting plane through the fitting transformation matrix to obtain the fitting center coordinate, including the following steps: S410: based on the calibration plate posture transformation data, obtaining the translation position data of the calibration plate in the image acquisition device coordinate system, obtaining the calibration plate translation amount, and performing fitting based on the calibration plate translation amount, including the following steps: Step 1: Assume that the equation of the fitting plane is For the convenience of calculation, the fitting plane equation is equivalent to ,in, For the parameters to be solved, construct the design matrix and target vector, which are expressed as follows:

[0048]

[0049] Step 2: Based on the design matrix and target vector, the least square method is used to solve the parameters, and the fitting plane is constructed. The fitting plane is projected onto the horizontal plane to obtain the fitting transformation matrix, which is expressed as follows:

[0050] S420: Based on the fitting transformation matrix, the first coordinate is converted into a horizontal plane coordinate system to obtain the horizontal coordinate of the first coordinate, and a horizontal design matrix and a horizontal target vector are constructed, which are expressed as follows:

[0051]

[0052] S430: Solve the parameters of the horizontal design matrix and the horizontal target vector by the least square method to obtain the center coordinates of the horizontal circular surface , the center coordinates of the horizontal circular surface are reversely projected based on the fitting transformation matrix to obtain the fitting center coordinates. The schematic diagram of the fitting plane and the center position is shown in Figure 5 As shown, the parameter solution is expressed as follows:

[0053] Based on the fitting transformation matrix, the center coordinates of the horizontal circular surface are reversely projected to obtain the fitting center coordinates; in, represents the design matrix, represents the target vector, represents the parameters of the fitting plane, represents the horizontal design matrix, represents the horizontal target vector, Represents the parameters of the horizontal circular surface, represents the horizontal axis, represents the vertical coordinate, Indicates the vertical coordinate.

[0054] In step S500, the normal vector of the fitting plane is obtained, and based on the normal vector of the fitting plane and the coordinates of the fitting center, the equation of the rotation axis line is obtained, which is expressed as follows: Get the normal vector of the fitted plane based on the equation of the fitted plane , through the structure of the image acquisition device in this embodiment, based on the normal vector of the fitting plane and the coordinates of the fitting center of the circle, the equation of the rotation axis line is obtained, which is expressed as follows:

[0055] in, represents the horizontal coordinate of the center of the fitted circle, represents the ordinate of the center of the fitted circle, represents the vertical coordinate of the center of the fitted circle, represents the normal vector of the fitted plane, represents the horizontal axis, represents the vertical coordinate, Indicates the vertical coordinate.

[0056] In step S600, based on the origin of the image acquisition device coordinate system, the fitting plane and the axis straight line equation, the image acquisition device movement radius and the image acquisition device height are obtained. The image acquisition device parameter calculation schematic diagram is shown in FIG. Figure 6 As shown, the following steps are included: S610: Calculate the origin of the image acquisition device coordinate system based on the image acquisition device coordinate system and the axis straight line equation The distance between the linear equation of the rotating axis and the moving radius of the image acquisition device is obtained, which is expressed as follows:

[0057] S620: Based on the image acquisition device coordinate system and the fitting plane, calculate the distance from the origin of the image acquisition device coordinate system to the fitting plane to obtain the height of the image acquisition device, which is expressed as follows:

[0058] in, represents the motion radius of the image acquisition device, represents the normal vector of the fitted plane, represents the coordinates of the center of the fitting circle, Indicates the height of the image acquisition device, Represents the parameters of the fitted plane.

[0059] The above process can obtain the relative position of the image acquisition device and the calibration plate, optimize the calibration process of the image acquisition device, and accurately obtain the movement radius and height of the image acquisition device.

[0060] Embodiment 2: A camera calibration system based on image processing, such as Figure 2 As shown, it includes an image preprocessing module 100, a data processing module 200, a data transformation module 300, a data fitting module 400, a fitting analysis module 500 and a data calculation module 600; The image preprocessing module 100 uses the rotating shaft as the rotation center, drives the calibration plate to rotate through the turntable, obtains the calibration plate image containing the calibration points at multiple angles through the image acquisition device, performs image preprocessing on the calibration plate image, and obtains the calibration plate coordinates, wherein the image acquisition device includes an image acquisition device, a rotating shaft and a turntable, and the rotating shaft is perpendicular to the turntable, the calibration plate is preset with the calibration points, and the calibration plate is placed vertically on the turntable; The data processing module 200 obtains distortion parameters and internal parameters of the image acquisition device, performs dedistortion and coordinate standardization processing on the calibration plate coordinates by using the distortion parameters and internal parameters of the image acquisition device, obtains the first calibration plate coordinates, and performs coordinate transformation to obtain the second calibration plate coordinates; The data transformation module 300 performs posture analysis on the calibration plate based on the first calibration plate coordinates and the second calibration plate coordinates to obtain calibration plate posture transformation data, and performs coordinate transformation on the first calibration plate coordinates based on the calibration plate posture transformation data to obtain a first coordinate in the image acquisition device coordinate system; The data fitting module 400 analyzes the position of the calibration plate translated in the coordinate system of the image acquisition device based on the calibration plate posture transformation data, obtains the calibration plate translation amount and performs fitting, obtains the fitting plane and the fitting transformation matrix, projects the first coordinate to the horizontal plane based on the fitting transformation matrix and performs fitting, obtains the center coordinate of the horizontal circular plane, and reversely projects the center coordinate of the horizontal circular plane to the fitting plane through the fitting transformation matrix to obtain the fitting center coordinate; The fitting analysis module 500 obtains the normal vector of the fitting plane, and obtains the straight line equation of the rotation axis based on the normal vector of the fitting plane and the coordinates of the fitting circle center; The data calculation module 600 obtains the image acquisition device movement radius and the image acquisition device height based on the origin of the image acquisition device coordinate system, the fitting plane and the rotation axis straight line equation.

[0061] Specifically, the data fitting module 400 is configured as follows: Construct the design matrix and target vector, which are expressed as follows:

[0062]

[0063] Based on the design matrix and the target vector, the least square method is used to solve the parameters, and the fitting plane is constructed. The fitting plane is projected onto the horizontal plane to obtain the fitting transformation matrix, which is expressed as follows:

[0064]

[0065] in, represents the design matrix, represents the target vector, represents the fitting plane parameters, represents the horizontal axis, represents the vertical coordinate, represents the vertical coordinate, represents the coefficient; The coordinates of the center of the fitting circle are obtained by the following steps: Based on the fitting transformation matrix, the first coordinate is projected onto the horizontal plane to obtain the horizontal coordinate of the first coordinate, and the horizontal design matrix and horizontal target vector are constructed, which are expressed as follows:

[0066]

[0067] Based on the horizontal design matrix and the horizontal target vector, the parameters are solved, and the horizontal coordinates of the first coordinate are fitted to obtain the coordinates of the center of the horizontal circular surface. The parameter solution is expressed as follows:

[0068] Based on the fitting transformation matrix, the center coordinates of the horizontal circular surface are reversely projected to obtain the fitting center coordinates; in, represents the horizontal design matrix, represents the horizontal target vector, Represents the parameters of the horizontal circular surface, represents the horizontal axis, represents the vertical coordinate, Indicates the vertical coordinate.

[0069] Various changes and modifications can be made without departing from the spirit and scope of the present invention, and all equivalent technical solutions also belong to the scope of the present invention.

[0070] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0071] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0072] The present invention is described with reference to the flowcharts and / or block diagrams of the method, terminal device (system), and computer program product according to the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0073] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0074] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0075] It should be noted that: The "one embodiment" or "embodiment" mentioned in the specification means that the specific features, structures or characteristics described in conjunction with the embodiment are included in at least one embodiment of the present invention. Therefore, the phrases "one embodiment" or "embodiment" appearing in various places throughout the specification do not necessarily refer to the same embodiment.

[0076] In addition, it should be noted that the shapes and names of the parts and components of the specific embodiments described in this specification may be different. Any equivalent or simple changes made based on the structure, features and principles described in the patent concept of the present invention are included in the protection scope of the patent of the present invention. The technicians in the technical field of the present invention can make various modifications or supplements to the specific embodiments described or replace them in a similar manner, as long as they do not deviate from the structure of the present invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A camera calibration method based on image processing, characterized in that: The following steps are involved: The calibration plate is driven to rotate by the turntable with the rotation axis as the rotation center, and the calibration plate images containing the calibration points under multiple angles are acquired by the image acquisition device, and the calibration plate images are preprocessed to obtain the calibration plate coordinates, wherein the image acquisition device includes an image acquisition device, a rotation axis and a turntable, and the rotation axis is perpendicular to the turntable, and the calibration plate is preset with the calibration points and the calibration plate is placed vertically on the turntable; Obtaining distortion parameters and internal parameters of the image acquisition device, dedistorting and standardizing the calibration plate coordinates using the distortion parameters and internal parameters of the image acquisition device, obtaining the first calibration plate coordinates and performing coordinate transformation to obtain the second calibration plate coordinates; Performing posture analysis on the calibration plate based on the first calibration plate coordinates and the second calibration plate coordinates to obtain calibration plate posture transformation data, and performing coordinate transformation on the first calibration plate coordinates based on the calibration plate posture transformation data to obtain a first coordinate in the image acquisition device coordinate system; Based on the calibration plate posture transformation data, the position of the calibration plate translated in the image acquisition device coordinate system is analyzed to obtain the calibration plate translation amount and perform fitting to obtain a fitting plane and a fitting transformation matrix; based on the fitting transformation matrix, the first coordinate is projected onto the horizontal plane and performed fitting to obtain the center coordinate of the horizontal circular plane; the center coordinate of the horizontal circular plane is reversely projected onto the fitting plane through the fitting transformation matrix to obtain the fitting center coordinate; Obtain the normal vector of the fitting plane, and obtain the equation of the rotation axis line based on the normal vector of the fitting plane and the coordinates of the center of the fitting circle; Based on the origin of the image acquisition device coordinate system, the fitting plane and the straight line equation of the rotation axis, the movement radius of the image acquisition device and the height of the image acquisition device are obtained.

2. The camera calibration method based on image processing according to claim 1, characterized in that: The image preprocessing of the calibration plate image to obtain the calibration plate coordinates comprises the following steps: Performing grayscale processing on the calibration plate image to obtain a calibration plate grayscale image, and performing downsampling processing on the calibration plate grayscale image to obtain a calibration plate downsampled image; Based on the downsampled image of the calibration plate, the calibration points are identified and marked to obtain the coordinates of the calibration points in the calibration plate; The calibration point coordinates are screened and sorted by the relevant parameters of the calibration plate to obtain the position coordinates of the calibration plate; The calibration plate position coordinates are mapped to the calibration plate grayscale image to obtain the calibration plate mapping coordinates, and the calibration plate mapping coordinates are sub-pixel detected to obtain the calibration plate coordinates.

3. The camera calibration method based on image processing according to claim 1, characterized in that: The first calibration plate coordinates and the second calibration plate coordinates are obtained by the following steps: De-distorting the calibration plate coordinates based on the distortion parameters to obtain de-distorted calibration plate coordinates; Based on the internal parameters of the image acquisition device, the coordinates of the dedistorted calibration plate are transformed into a normalized coordinate system to obtain the coordinates of the first calibration plate; A calibration plate coordinate system is established based on the calibration plate position, and the calibration plate coordinates are converted to the calibration plate coordinate system to obtain the second calibration plate coordinates.

4. The camera calibration method based on image processing according to claim 1, characterized in that: The step of obtaining the first coordinate in the image acquisition device coordinate system comprises the following steps: Based on the coordinates of the first calibration plate and the corresponding coordinates of the second calibration plate, the rotation transformation and translation transformation of the calibration plate in the coordinate system of the image acquisition device are analyzed by direct linear transformation to obtain initial calibration plate posture transformation data; Based on the initial calibration plate posture transformation data and optimizing the reprojection error, the calibration plate posture transformation data is obtained, wherein the calibration plate posture transformation data includes the calibration plate posture rotation data and the calibration plate posture translation data, and the reprojection error represents the error between the second calibration plate coordinates and the first calibration plate coordinates after being projected to the image coordinate system through the initial calibration plate posture transformation data; The first calibration plate coordinates are rotated and translated by the calibration plate posture rotation data and the calibration plate posture translation data, and the first calibration plate coordinates are converted to the image acquisition device coordinate system to obtain the first coordinates.

5. The camera calibration method based on image processing according to claim 1, characterized in that: The step of obtaining the fitting plane and the fitting transformation matrix comprises the following steps: Construct the design matrix and target vector, which are expressed as follows: Based on the design matrix and the target vector, the least square method is used to solve the parameters, and the fitting plane is constructed. The fitting plane is projected onto the horizontal plane to obtain the fitting transformation matrix, which is expressed as follows: in, represents the design matrix, represents the target vector, represents the fitting plane parameters, represents the horizontal axis, represents the vertical coordinate, represents the vertical coordinate, Represents the coefficient.

6. The camera calibration method based on image processing according to claim 1, characterized in that: The coordinates of the fitting circle center are obtained by the following steps: Based on the fitting transformation matrix, the first coordinate is projected onto the horizontal plane to obtain the horizontal coordinate of the first coordinate, and the horizontal design matrix and horizontal target vector are constructed, which are expressed as follows: Based on the horizontal design matrix and the horizontal target vector, the parameters are solved, and the horizontal coordinates of the first coordinate are fitted to obtain the coordinates of the center of the horizontal circular surface. The parameter solution is expressed as follows: Based on the fitting transformation matrix, the center coordinates of the horizontal circular surface are reversely projected to obtain the fitting center coordinates; in, represents the horizontal design matrix, represents the horizontal target vector, Represents the parameters of the horizontal circular surface, represents the horizontal axis, represents the vertical coordinate, Indicates the vertical coordinate.

7. The camera calibration method based on image processing according to claim 1, characterized in that: Based on the positional relationship between the rotation axis and the calibration plate, the rotation axis straight line equation is obtained by fitting the normal vector of the plane and the coordinates of the center of the circle, which is expressed as follows: in, represents the horizontal coordinate of the center of the fitted circle, represents the ordinate of the center of the fitted circle, represents the vertical coordinate of the center of the fitted circle, represents the normal vector of the fitted plane, represents the horizontal axis, represents the vertical coordinate, Indicates the vertical coordinate.

8. The camera calibration method based on image processing according to claim 1, characterized in that: The method of obtaining the motion radius and height of the image acquisition device based on the origin, the fitting plane and the straight line equation of the rotation axis of the image acquisition device coordinate system comprises the following steps: Based on the image acquisition device coordinate system and the axis straight line equation, the distance between the origin of the image acquisition device coordinate system and the axis straight line equation is calculated to obtain the image acquisition device motion radius, which is expressed as follows: Based on the image acquisition device coordinate system and the fitting plane, the distance from the origin of the image acquisition device coordinate system to the fitting plane is calculated to obtain the height of the image acquisition device, which is expressed as follows: in, represents the motion radius of the image acquisition device, represents the normal vector of the fitted plane, represents the coordinates of the center of the fitting circle, Indicates the height of the image acquisition device, Represents the parameters of the fitted plane.

9. A camera calibration system based on image processing, characterized in that: It includes an image preprocessing module, a data processing module, a data transformation module, a data fitting module, a fitting analysis module and a data calculation module; The image preprocessing module uses the rotating shaft as the rotation center, drives the calibration plate to rotate through the turntable, obtains the calibration plate image containing the calibration points at multiple angles through the image acquisition device, performs image preprocessing on the calibration plate image, and obtains the calibration plate coordinates, wherein the image acquisition device includes an image acquisition device, a rotating shaft and a turntable, and the rotating shaft is perpendicular to the turntable, the calibration plate is preset with the calibration points, and the calibration plate is placed vertically on the turntable; The data processing module obtains the distortion parameters and the internal parameters of the image acquisition device, performs dedistortion and coordinate standardization processing on the calibration plate coordinates by using the distortion parameters and the internal parameters of the image acquisition device, obtains the first calibration plate coordinates, performs coordinate transformation, and obtains the second calibration plate coordinates; The data transformation module performs posture analysis on the calibration plate based on the first calibration plate coordinates and the second calibration plate coordinates to obtain calibration plate posture transformation data, and performs coordinate transformation on the first calibration plate coordinates based on the calibration plate posture transformation data to obtain a first coordinate in the image acquisition device coordinate system; The data fitting module analyzes the position of the calibration plate translated in the coordinate system of the image acquisition device based on the calibration plate posture transformation data, obtains the calibration plate translation amount and performs fitting, obtains the fitting plane and the fitting transformation matrix, projects the first coordinate to the horizontal plane based on the fitting transformation matrix and performs fitting, obtains the center coordinate of the horizontal circular plane, and reversely projects the center coordinate of the horizontal circular plane to the fitting plane through the fitting transformation matrix to obtain the fitting center coordinate; The fitting analysis module obtains the normal vector of the fitting plane, and obtains the straight line equation of the rotation axis based on the normal vector of the fitting plane and the coordinates of the center of the fitting circle; The data calculation module obtains the motion radius and height of the image acquisition device based on the origin of the image acquisition device coordinate system, the fitting plane and the straight line equation of the rotation axis.

10. The camera calibration system based on image processing according to claim 9, characterized in that: The data fitting module is configured as follows: Construct the design matrix and target vector, which are expressed as follows: Based on the design matrix and the target vector, the least square method is used to solve the parameters, and the fitting plane is constructed. The fitting plane is projected onto the horizontal plane to obtain the fitting transformation matrix, which is expressed as follows: in, represents the design matrix, represents the target vector, represents the fitting plane parameters, represents the horizontal axis, represents the vertical coordinate, represents the vertical coordinate, represents the coefficient; The coordinates of the center of the fitting circle are obtained by the following steps: Based on the fitting transformation matrix, the first coordinate is projected onto the horizontal plane to obtain the horizontal coordinate of the first coordinate, and the horizontal design matrix and horizontal target vector are constructed, which are expressed as follows: Based on the horizontal design matrix and the horizontal target vector, the parameters are solved, and the horizontal coordinates of the first coordinate are fitted to obtain the coordinates of the center of the horizontal circular surface. The parameter solution is expressed as follows: Based on the fitting transformation matrix, the center coordinates of the horizontal circular surface are reversely projected to obtain the fitting center coordinates; in, represents the horizontal design matrix, represents the horizontal target vector, Represents the parameters of the horizontal circular surface, represents the horizontal axis, represents the vertical coordinate, Indicates the vertical coordinate.

11. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

12. A camera calibration device based on image processing, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

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