Line structured light plane calibration method based on offset reference plane principle

Abstract

The invention discloses a line structured light plane calibration method based on an offset reference plane principle. The method comprises the following steps: calibrating a camera of a scanner to obtain a camera internal reference matrix and distortion parameters; taking the checkerboard calibration plate as a target reference object to collect a calibration plate image with a light bar and a target image without the light bar; extracting feature points of the calibration plate image with the light bars under pixel coordinates, and determining the positions of the light bars in a camera coordinate system based on the feature points to obtain coordinate points under a plurality of camera coordinate systems; space plane equations are respectively constructed based on the plurality of coordinate points to obtain a space plane equation corresponding to the calibration plate image; image corner coordinates on the checkerboard calibration plate are extracted, space plane equations are constructed based on the multiple corner coordinates, and a space plane equation corresponding to the target image is obtained; and obtaining a light plane equation based on the space plane equations corresponding to the plurality of calibration plate images and the space plane equations corresponding to the plurality of target images.

Description

Technical Field

[0001] The invention belongs to the technical field of non-contact measurement, and in particular relates to a line structured light plane calibration method based on the offset reference plane principle. Background Art

[0002] Line structured light scanners have the advantages of non-contact, high speed and high precision, and are widely used in 3D measurement and reverse engineering. In the line structured light measurement system, the measurement accuracy depends on the accuracy of the system calibration, and the light plane calibration of the line structured light scanner is the key part of the system calibration.

[0003] Light plane calibration is the process of obtaining the parameters of the light plane equation in the line structured light model by combining the geometric constraints of the calibration target and the camera perspective principle. At present, line structured light light plane calibration often uses an article titled "Calibrating a Structured LightStripe System: A Novel Approach" published by Huynh et al. in the International Journal of Computer Vision, proposing a calibration method for obtaining light plane calibration points using the cross ratio invariance principle. The invention solves the intersection coordinates of the straight lines where the three collinear points on the chessboard calibration plate are located based on the cross ratio invariance principle, thereby obtaining high-precision punctuation points on the light plane calibration, which is mostly used for on-site calibration. However, this method requires the light strip projected by the line structured light to intersect with the chessboard, which is not conducive to the extraction of the center point and corner point of the line structured light, and the extracted feature points are relatively few; Cui Haihua et al. from Nanjing University of Aeronautics and Astronautics invented patent number CN113674360A "A Line Structured Light Light Plane Calibration Method Based on Covariance". A calibration scheme for solving the light plane equation by combining the Plüker matrix of light strips on the light plane is invented. The invention uses the Plüker matrix to solve the Plüker matrix of multiple light strips on the light plane, which requires combining three plane equations. The calculation process is relatively complicated and there is a matrix decomposition error. In view of the above problems such as difficulty in extracting light plane feature points and complex calculation of the calibration process, the present invention provides a new line structured light light plane calibration method. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes a line structured light light plane calibration method based on the offset reference plane principle to solve the above problems existing in the prior art.

[0005] To achieve the above object, the present invention provides a line structured light plane calibration method based on the offset reference plane principle, comprising:

[0006] Calibrate the scanner's camera to obtain the camera's intrinsic parameter matrix and distortion parameters;

[0007] Using the checkerboard calibration plate as a target reference, collect the calibration plate image with light stripes and the target image without light stripes;

[0008] Extracting feature points of the calibration plate image with the light strip in pixel coordinates, and determining the position of the light strip in the camera coordinate system based on the feature points to obtain a number of coordinate points in the camera coordinate system;

[0009] Based on the coordinate points, spatial plane equations are respectively constructed to obtain the spatial plane equations corresponding to the calibration plate image;

[0010] Extracting the coordinates of the image corner points on the checkerboard calibration plate, and constructing space plane equations based on the coordinates of several corner points to obtain the space plane equations corresponding to the target image;

[0011] The light plane equation is obtained based on the space plane equations corresponding to the plurality of calibration plate images and the space plane equations corresponding to the plurality of target images.

[0012] Optionally, the process of collecting the calibration plate image with light stripes and the target image without light stripes by using the checkerboard calibration plate as the target reference object includes:

[0013] Place the checkerboard calibration plate on the working platform of the scanner at an angle to control the stepping motion of the working platform;

[0014] When the working platform stops, the image of the calibration plate with light strips and the image of the target without light strips are collected;

[0015] The calibration plate image with the light stripes and the target image without the light stripes are subjected to dedistortion processing to obtain the dedistorted calibration plate image and the target image without the light stripes.

[0016] Optionally, after acquiring the image, the method further includes constructing a coordinate system;

[0017] Among them, the constructed coordinate system includes: establishing a camera coordinate system with the optical center of the camera as the origin; establishing an image pixel coordinate system with the upper left corner of the image as the origin; establishing an image physical coordinate system with the intersection of the camera optical center and the imaging plane as the origin; establishing a world coordinate system with the upper left corner of the plane calibration plate as the origin.

[0018] Optionally, the process of extracting feature points of the calibration plate image in pixel coordinates and obtaining coordinate points based on the feature points includes:

[0019] Based on the grayscale centroid algorithm, the feature points of the light strip center in the pixel coordinate system are extracted from the calibration plate image;

[0020] Determine a straight line passing through the center pixel coordinates of the laser stripes of the calibration plate image based on the feature points;

[0021] Based on the geometric relationship between the camera coordinate system and the image pixel coordinate system, the coordinate points on the line are calculated.

[0022] Optionally, the geometric relationship between the camera coordinate system and the image pixel coordinate system is:

[0023]

[0024] In the formula, a H is the vertical field of view of the camera, a v is the horizontal field of view of the camera, N and M represent the image M Li The pixel size is N×M, d p is the coordinate P qp The distance to offset along the z axis, x qp Represents the straight line l q (q=1,2…n) The distance of the coordinates on the x-axis, y qp Represents the straight line l q (q=1,2...n) represents the distance of the coordinates on the y-axis, (u,v) represents the pixel coordinates at the center of the laser stripe, (x qp ,y qp ) represents a point in the camera coordinate system.

[0025] Optionally, the process of calculating the spatial plane equation corresponding to the calibration plate image includes:

[0026] Based on the plurality of coordinate points, constructing a spatial plane equation where each coordinate point is located to obtain a plurality of spatial plane equations of the coordinate points;

[0027] Constructing a system of linear equations based on the coordinate point space plane equations;

[0028] After solving the linear equations, a spatial plane equation corresponding to the calibration plate image is obtained;

[0029] Among them, the spatial plane equation expression corresponding to the calibration plate image is:

[0030] a i1 x+b i1 y-z+c i1 =0

[0031] In the formula, a i1 ,b i1 ,c i1 , represents the plane equation of the camera coordinate system when the same calibration plate changes its pose for the i-th time.

[0032] Optionally, the process of calculating the space plane equation corresponding to the target image includes:

[0033] The image corner coordinates of the checkerboard calibration plate in the pixel coordinate system are extracted based on the corner coordinate extraction algorithm;

[0034] The image extrinsic parameter calibration method based on planar targets can obtain the extrinsic parameters of target images;

[0035] Converting the image corner coordinates to a world coordinate system based on the camera intrinsic parameter matrix, the distortion parameters, and the extrinsic parameters of the target image;

[0036] Establish the spatial plane equation corresponding to the coordinates of the image corner points based on the position in the world coordinate system;

[0037] Constructing a linear equation system based on the space plane equations corresponding to the coordinates of the corner points of the image;

[0038] After solving the linear equations, the spatial plane equation corresponding to the target image is obtained.

[0039] Optionally, the process of obtaining the light plane equation based on the space plane equations corresponding to the plurality of calibration plate images and the space plane equations corresponding to the plurality of target images includes:

[0040] Obtaining a plurality of intersection line equations based on the space plane equations corresponding to the plurality of calibration plate images and the space plane equations corresponding to the plurality of target images;

[0041] Performing light plane fitting on the plurality of intersection line equations to obtain a light plane equation;

[0042] The expression of the light plane equation is:

[0043] ax v +by v -z v +c=0

[0044] Where a, b, c represent the coefficients of the light plane equation, (x v ,y v ,z v ) represents the coordinates on the light plane.

[0045] Compared with the prior art, the present invention has the following advantages and technical effects:

[0046] The calibration method for line structured light scanner provided by the present invention only needs to control the calibration plate to make a translation movement once to complete the light plane calibration, requiring less manual adjustment and facilitating automation. The calibration method provided by the present invention uses a reference offset plane to obtain multiple characteristic straight line equations on the light plane, and then fits to obtain the light plane equation, so its calibration accuracy is higher than the traditional calibration method based on space transformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0048] Figure 1 It is a schematic diagram of the operation of the line structured light scanner calibration method according to an embodiment of the present invention;

[0049] Figure 2 Establishing a coordinate system for a calibration system according to an embodiment of the present invention;

[0050] Figure 3 The relationship between the pixels and the light of the captured image according to the embodiment of the present invention;

[0051] Figure 4 is the angle relationship between the pixel of the image and the light in the embodiment of the present invention;

[0052] Figure 5 The principle of reference plane displacement according to an embodiment of the present invention;

[0053] Figure 6 Extraction of corner points of the calibration plate according to an embodiment of the present invention;

[0054] Figure 7 is a flow chart of an embodiment of the present invention;

[0055] Marking instructions: 1. Workbench; 2. Connecting frame; 3. Housing; 4. Line laser; 5. Camera; 6. Lens; 7. Checkerboard calibration plate; 8. Pad. DETAILED DESCRIPTION

[0056] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0057] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0058] Embodiment 1

[0059] like Figure 7As shown, in this embodiment, a line structured light optical plane calibration method based on the offset reference plane principle is provided, comprising the following steps: calibrating the camera of the scanner to obtain the camera intrinsic parameter matrix and distortion parameters; using the checkerboard calibration plate as the target reference to collect the calibration plate image with light strips and the target image without light strips; extracting the feature points of the calibration plate image with light strips in the pixel coordinates, and determining the position of the light strips in the camera coordinate system based on the feature points to obtain several coordinate points in the camera coordinate system; constructing spatial plane equations based on the several coordinate points to obtain the spatial plane equations corresponding to the calibration plate image; extracting the image corner point coordinates on the checkerboard calibration plate, and constructing spatial plane equations based on the several corner point coordinates to obtain the spatial plane equations corresponding to the target image; obtaining the light plane equations based on the spatial plane equations corresponding to the several calibration plate images and the spatial plane equations corresponding to the several target images.

[0060] The specific implementation process is:

[0061] Step 1: Calibrate the camera intrinsic distortion coefficient of the scanner. Use the camera calibration method based on a planar target to obtain the camera intrinsic parameter matrix M and distortion parameters, and record the camera intrinsic parameter matrix as K.

[0062] Step 2: Use a high-precision checkerboard calibration plate 7 as a target reference, and project the line structured light onto the blank part of the checkerboard calibration plate 7 to ensure that the light stripes do not intersect the chessboard. Control the checkerboard calibration plate 7 to make a set of translation movements, collect a series of calibration plate images and calibration images projected with laser stripes at the same position, and dedistort them. Figure 1 As shown, the checkerboard calibration plate 7 is placed on the workbench 1 of the scanner at an angle to ensure that the line laser can be projected onto the calibration plate and the camera 5 can capture the complete calibration plate image. The workbench 1 is controlled to move in steps. After each movement stops, the external light source is turned on and the camera 5 is controlled to capture the calibration plate image. Then the external light source is turned off and the line laser 4 is turned on to capture the calibration plate image with the light strip projected at the same position. The above image is captured at least at two positions. The captured calibration plate image group with the light strip projected is denoted as M. L , the target image group without light strip is recorded as M B , M L 、M B The number of images in M ​​is (n>4), L The i-th light strip image in is denoted as M Li , the target image in the same position is denoted as M Bi , and then all the captured images are subjected to dedistortion processing; Figure 2 As shown, the camera coordinate system O is established with the optical center of the camera as the origin. C -X C Y C Z C , establish the image pixel coordinate system O with the upper left corner of the image as the originO -uv, establish the image physical coordinate system O1-x y with the intersection of the camera optical center and the imaging plane as the origin, and establish the world coordinate system O1-x y with the upper left corner of the plane calibration plate as the origin W -X W Y W Z W .

[0063] Step 3: Extract the feature points in the pixel coordinate system of the center of the light strip from a series of calibration plate images projected with light strips. Use the grayscale centroid algorithm to extract M Li The feature point P0(u, v) of the center of the light strip in the image in the pixel coordinate system.

[0064] Step 4: Using the offset reference plane principle, we can calculate a series of coordinate points in the camera coordinate system on the straight line (through the camera optical center and the feature point) where the feature point in step 3 is located. Figure 2 As shown, q (q=1,2...n)(n>4) represents the image M in the camera coordinate system Li The center pixel coordinates of the laser stripe and the camera optical center O C The straight line, point P qp (x qp ,y qp ,z qp )(p=1,2...m)(m>20) is the straight line l q The pth coordinate point on (q=1,2...n). Figure 3 As shown, let U = tanθ and V = tanφ / cosθ, according to the geometric relationship, we can get:

[0065]

[0066] In the formula, a H is the vertical field of view of the camera, a v is the horizontal field of view of the camera, N and M represent the image M Li The pixel size is N×M, and (u,v) represents the pixel coordinates of the center of the laser stripe.

[0067] Further Figure 4-Figure 5 As shown, using formula (3) we can calculate the straight line l q P on (q=1,2...n) qp (x qp ,y qp ,d p )coordinate:

[0068]

[0069] Where, d p is the coordinate P qpThe distance offset to the z axis (d p =10,20...10m).

[0070] According to formula (3), the straight line l can be calculated q The coordinate points in the m camera coordinate system on (q=1, 2...n).

[0071] Step 5: Perform spatial plane fitting on the coordinate points of all camera coordinate systems at the single position and pose of the checkerboard calibration plate. Detailed process: Because the straight line l q (q=1,2...n) There are m coordinate points in the camera coordinate system, then the straight lines l1,l2,...l n There are h1 = m × n point coordinates in the camera coordinate system; record the light bar image M Li The middle straight line l1,l2,...l n The coordinates of the points h1=m×n on the camera coordinate system are the equation of the plane in the space π i1 The general expression of is:

[0072] A i1 x+B i1 y+C i1 z+D i1 =0(C i1 ≠0) (4)

[0073] Among them, A i1 , B i1 , C i1 , D i1 Represents the light bar image M Li The middle straight line l1,l2,...l n Constant coefficients of the equation of the plane.

[0074] Transform it into the following form

[0075]

[0076] make

[0077]

[0078] Given the equation of the plane in space π i1 The values ​​of the h1 feature points above are recorded as:

[0079] Q r =(x r ,y r ,z r )(r=1,2,...h1) (7)

[0080] So we have:

[0081]

[0082] In order to minimize S, it is required

[0083]

[0084] Click Q r Substituting into formula (9) we have

[0085]

[0086] Simplified:

[0087]

[0088] Write equation (11) in matrix form:

[0089]

[0090] So let

[0091]

[0092] According to equations (13) to (15), the linear equation system can be expressed as

[0093] A I X I =b I (16)

[0094] Using the characteristics of the solution of the linear equation system, we can find the vector X I .

[0095] So we can solve the plane equation π i1 The expression is:

[0096] a i1 x+b i1 y-z+c i1 =0 (17)

[0097] Repeat step 5 to get the light stripe image M. L1 ,M L2 ,...M Ln The corresponding space plane equations are π 11 ,π 21 ,...π n1 .

[0098] Step 6: Calculate the spatial plane equation of the corner points on the checkerboard calibration plate in the camera coordinate system. Figure 6 As shown in the figure, the image-based corner point coordinate extraction algorithm can extract the image corner point coordinates (u b ,v b). Given the camera intrinsic parameters and distortion coefficients, the image M can be obtained by the image extrinsic calibration method based on the planar target. Bi The external parameter is the rotation matrix R of the world coordinate system relative to the camera coordinate system. i With the translation matrix T i The image corner coordinates (u b ,v b ) is converted to the world coordinate system:

[0099]

[0100] Where s is the scale factor, (X W ,Y W ,Z W ) represents the image M in the calibration plate Li The coordinates of the laser stripes in the world coordinate system, (u0, v0) represents the coordinates of the origin of the image physical coordinate system in the pixel coordinate system, and f x With f y Indicates the horizontal and vertical scale factors of the image. Due to the definition of the world coordinate system, we know that Z W =0, according to the rigid body transformation relationship between the world coordinate system and the camera coordinate system:

[0101]

[0102] In the formula, (X ci ,Y ci ,Z ci ) is the image M Bi The coordinates of the corner points on R are expressed in the camera coordinate system; i and T i Respectively expressed as:

[0103]

[0104] In the formula, r B1 ,r B2 ,r B3 ,...,r B9 Represents a constant.

[0105]

[0106] Where, t B1 ,t B2 ,t B3 Represents a constant.

[0107] The coordinates of the corner points of the calibration plate in the camera coordinate system can be obtained by combining equations (18) to (21):

[0108]

[0109] Note that the target image M Bi The coordinates of the corner points on the camera coordinate system are the equations of the plane in the space where they are located π i2 The general expression of is:

[0110] A i2 x l +B i2 y l +C i2 z l +D i2 =0(C i2 ≠0) (23)

[0111] Among them, A i2 , B i2 , C i2 , D i2 Represents image M Bi The space plane equation π i2 The constant coefficient of (x l ,y l ,z l ) represents the space plane equation π i2 The coordinate points on .

[0112] Transform it into the following form

[0113]

[0114] make

[0115]

[0116] According to formula (22), we can know that image M Bi The value of the upper corner point coordinates in the camera coordinate system is a constant t (t>7). These coordinate points are recorded as:

[0117] Q j =(X j ,Y j ,Z j )(j=1,2...t) (26)

[0118] So we have:

[0119]

[0120] In order to make S l Minimum, required

[0121]

[0122] Click Q j Substituting into formula (28) we have:

[0123]

[0124] Simplified:

[0125]

[0126] Write equation (30) in matrix form:

[0127]

[0128] So let

[0129]

[0130] Equations (31) to (33) can represent the linear equation system

[0131] A II X II =b II (35)

[0132] Using the characteristics of the solution of the linear equation system, we can find the vector X II So we can solve the plane equation π i2 The expression is:

[0133] a i2 x l +b i2 y l -z l +c i2 =0 (36)

[0134] Repeat step 6 to obtain the target image M B1 ,M B2 ,...M Bn The coordinates of the upper corner point in the camera coordinate system and the equations of the plane in the space where it is located are π 12 ,π 22 ,...π n2 .

[0135] Step 7: Find the intersection of the spatial plane equations obtained in steps 5 and 6. Find the plane equation π 11 ,π 21 ,...π n1 and the plane equation π 12 ,π 22 ,...π n2 Let π 11 With π 12 , π 21 With π 22 ,…,π n1 With π n2 The straight line equations of the intersection lines are L1, L2, ...L n . Let image M beLi The plane π i1 With image M Bi The plane π i2 The intersection line is L i (1,2...n), so L i The straight line expression is:

[0136]

[0137] Where D xi , D yi , D zi The straight line L i Direction vector The weight of a is a parameter representing the position along the intersection line; D 0i (x 0i ,y 0i ,z 0i ) is the straight line L i A certain point.

[0138] According to equations (17) and (36), we know that plane π i1 With plane π i2 The plane equations of , then their normal vectors are:

[0139] Intersection line L i Direction vector Vector and The cross product is:

[0140]

[0141] Because D 0i For plane π i1 With plane π i2 For the convenience of calculation, let z 0i = 0, point D 0i Substituting into equation (17) and equation (36) we can find its value. According to equation (38) and point D 0i The intersection line L can be obtained i (i=1,2,...,n) is the equation of a straight line.

[0142] Repeat step 7 to find the equations of the lines L1, L2, ...L n .

[0143] Step 8: The straight lines L1, L2, L3, ... L obtained in step 7 n Perform light plane fitting, detailed process: on the straight line L iSelect 200×n coordinate points on (i=1,2,...,n), so the n straight lines have h2=200×n 2 (n>4) coordinate points, these coordinate points are recorded as:

[0144] Q k =(x k ,y k ,z k )(k=1,2...h2)(39)

[0145] The general expression of the light plane equation π in the camera coordinate system is:

[0146] Ax v +By v +Cz v +D=0(C≠0) (40)

[0147] Among them, A, B, C, D represent the constant coefficients of the light plane equation π, (x v ,y v ,z v ) represents the coordinate point on the light plane equation π.

[0148] Transform it into the following form

[0149]

[0150] make

[0151]

[0152] So we have:

[0153]

[0154] In order to minimize S, it is required

[0155]

[0156] Click Q k Substituting into formula (44) we have:

[0157]

[0158] Simplified:

[0159]

[0160] Write equation (46) in matrix form:

[0161]

[0162] So let

[0163]

[0164] Equations (48) to (50) can represent the linear equation system

[0165] A III X III =b III (51)

[0166] Using the characteristics of the solution of the linear equation system, we can find the vector X III .

[0167] So the expression of the light plane equation π can be obtained as:

[0168] ax v +by v -z v +c=0 (52)

[0169] The light plane calibration is now complete.

[0170] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A line structured light plane calibration method based on the offset reference plane principle, characterized in that: include: Calibrate the scanner's camera to obtain the camera's intrinsic parameter matrix and distortion parameters; Using the checkerboard calibration plate as a target reference, collect the calibration plate image with light stripes and the target image without light stripes; Extracting feature points of the calibration plate image with the light strip in pixel coordinates, and determining the position of the light strip in the camera coordinate system based on the feature points to obtain a number of coordinate points in the camera coordinate system; Based on the coordinate points, spatial plane equations are respectively constructed to obtain the spatial plane equations corresponding to the calibration plate image; Extracting the coordinates of the image corner points on the checkerboard calibration plate, and constructing space plane equations based on the coordinates of several corner points to obtain the space plane equations corresponding to the target image; The light plane equation is obtained based on the space plane equations corresponding to the plurality of calibration plate images and the space plane equations corresponding to the plurality of target images.

2. The line structured light plane calibration method based on the offset reference plane principle according to claim 1 is characterized in that: The process of collecting the calibration plate image with light stripes and the target image without light stripes using the checkerboard calibration plate as the target reference includes: Place the checkerboard calibration plate on the working platform of the scanner at an angle to control the stepping motion of the working platform; When the working platform stops, the image of the calibration plate with light strips and the image of the target without light strips are collected; The calibration plate image with the light stripes and the target image without the light stripes are subjected to dedistortion processing to obtain the dedistorted calibration plate image and the target image without the light stripes.

3. The method for calibrating a line structured light plane based on the offset reference plane principle according to claim 2, characterized in that: After acquiring the image, it also includes constructing a coordinate system; Among them, the constructed coordinate system includes: establishing a camera coordinate system with the optical center of the camera as the origin; establishing an image pixel coordinate system with the upper left corner of the image as the origin; establishing an image physical coordinate system with the intersection of the camera optical center and the imaging plane as the origin; establishing a world coordinate system with the upper left corner of the plane calibration plate as the origin.

4. The method for calibrating a line structured light plane based on the offset reference plane principle according to claim 3, characterized in that: The process of extracting feature points of the calibration plate image in pixel coordinates and obtaining coordinate points based on the feature points includes: Based on the grayscale centroid algorithm, the feature points of the light strip center in the pixel coordinate system are extracted from the calibration plate image; Determine a straight line passing through the center pixel coordinates of the laser stripes of the calibration plate image based on the feature points; Based on the geometric relationship between the camera coordinate system and the image pixel coordinate system, the coordinate points on the line are calculated.

5. The line structured light plane calibration method based on the offset reference plane principle according to claim 4 is characterized in that: The geometric relationship between the camera coordinate system and the image pixel coordinate system is: In the formula, a H is the vertical field of view of the camera, a v is the horizontal field of view of the camera, N and M represent the image M Li The pixel size is N×M, d p is the coordinate P qp The distance to offset along the z axis, x qp Represents the straight line l q (q=1,2…n) The distance of the coordinates on the x-axis, y qp Represents the straight line l q (q=1,2…n) represents the distance of the coordinates on the y-axis, (u,v) represents the pixel coordinates at the center of the laser stripe, (x qp ,y qp ) represents a point in the camera coordinate system.

6. The method for calibrating a line structured light plane based on the offset reference plane principle according to claim 4, characterized in that: The process of calculating the spatial plane equation corresponding to the calibration plate image includes: Based on the plurality of coordinate points, constructing a spatial plane equation where each coordinate point is located to obtain a plurality of spatial plane equations of the coordinate points; Constructing a system of linear equations based on the coordinate point space plane equations; After solving the linear equations, a spatial plane equation corresponding to the calibration plate image is obtained; Among them, the spatial plane equation expression corresponding to the calibration plate image is: a i1 x+b i1 y-z+c i1 =0 In the formula, a i1 ,b i1 ,c i1 , represents the plane equation of the camera coordinate system when the same calibration plate changes its pose for the i-th time.

7. The line structured light plane calibration method based on the offset reference plane principle according to claim 1, characterized in that: The process of calculating the spatial plane equation corresponding to the target image includes: The image corner coordinates of the checkerboard calibration plate in the pixel coordinate system are extracted based on the corner coordinate extraction algorithm; The image extrinsic parameter calibration method based on planar targets can obtain the extrinsic parameters of target images; Converting the image corner coordinates to a world coordinate system based on the camera intrinsic parameter matrix, the distortion parameters, and the extrinsic parameters of the target image; Establish the spatial plane equation corresponding to the coordinates of the image corner points based on the position in the world coordinate system; Constructing a linear equation system based on the space plane equations corresponding to the coordinates of the corner points of the image; After solving the linear equations, the spatial plane equation corresponding to the target image is obtained.

8. The line structured light plane calibration method based on the offset reference plane principle according to claim 1, characterized in that: The process of obtaining the light plane equation based on the space plane equations corresponding to the plurality of calibration plate images and the space plane equations corresponding to the plurality of target images includes: Obtaining a plurality of intersection line equations based on the space plane equations corresponding to the plurality of calibration plate images and the space plane equations corresponding to the plurality of target images; Performing light plane fitting on the plurality of intersection line equations to obtain a light plane equation; The expression of the light plane equation is: ax v +by v -z v +c=0 Where a, b, c represent the coefficients of the light plane equation, (x v ,y v ,z v ) represents the coordinates on the light plane.

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