A monocular single-projection structured light 3D camera fast calibration method, system, computer readable storage medium and computer program product

Abstract

The application relates to the technical field of structured light three-dimensional measurement, and discloses a fast calibration method, system, computer readable storage medium and computer program product of a monocular single-projection structured light 3D camera, the method comprising the following steps: extracting an angle point coordinate set of a modulation chart, and calculating conversion coefficients from pixel coordinates to three-dimensional world coordinates; obtaining a projection matrix of the structured light 3D camera through direct linear transformation, and extracting internal and external parameters of the structured light 3D camera from the projection matrix; and establishing a rational polynomial mapping relationship from pixel coordinates and absolute phase to working height according to an absolute phase image. The conversion coefficients from pixel coordinates to three-dimensional world coordinates are calculated through the angle point coordinates of the modulation chart, the mapping from pixel coordinates and absolute phase to working height is realized by adopting rational polynomial mapping, the coordinate systems of different height data are unified, complex pose estimation is not needed, and fast conversion from image coordinates to world coordinates is realized.

Description

Technical Field

[0001] This invention relates to the field of structured light 3D measurement technology, and in particular to a rapid calibration method, system, computer-readable storage medium, and computer program product for a monocular single-projection structured light 3D camera. Background Technology

[0002] Structured light 3D measurement technology is a measurement technique that projects specifically coded light stripes onto the object being measured, captures images of the deformed stripes using a camera, and then calculates the object's 3D coordinates based on calibration parameters. In this measurement technique, system calibration is a crucial step, and its accuracy directly affects the measurement results.

[0003] Existing calibration methods mainly have the following problems: (1) High accuracy requirements for calibration board position: Traditional methods require precise control of the orientation of the calibration board at multiple positions, which is complex to implement and prone to introducing errors.

[0004] (2) Low reconstruction efficiency: The complex coordinate transformation model increases the computational burden and affects the real-time performance of 3D reconstruction.

[0005] (3) Low efficiency in solving camera intrinsic and extrinsic parameters: Existing methods mostly use Zhang's calibration method, which requires multiple iterations for optimization, resulting in high computational complexity and sensitivity to initial values.

[0006] (4) The calibration process is cumbersome: it requires manual adjustment of the calibration plate position and taking a large number of images, and the calibration process is not automated enough.

[0007] In summary, this field requires a novel structural beam calibration method that can simplify the calibration process, improve calibration accuracy, enhance distortion compensation capabilities, and increase reconstruction efficiency. Summary of the Invention

[0008] The purpose of this invention is to provide a rapid calibration method, system, computer-readable storage medium, and computer program product for a monocular single-projection structured light 3D camera, so as to solve or at least partially solve the technical problems mentioned in the background art.

[0009] To achieve this objective, the present invention adopts the following technical solution: In a first aspect, the present invention provides a rapid calibration method for a monocular single-projection structured light 3D camera, comprising: Images of the front and back of the checkerboard calibration board at several different working heights within the effective working distance range of the structured light 3D camera were acquired respectively. Calculate the modulation image corresponding to the front plate image and the absolute phase image corresponding to the back plate image, respectively. Extract the set of corner coordinates from the modulated image and calculate the conversion coefficient from pixel coordinates to three-dimensional world coordinates; The projection matrix of the structured light 3D camera is obtained by direct linear transformation, and the intrinsic and extrinsic parameters of the structured light 3D camera are extracted from the projection matrix. Based on the absolute phase image, establish a rational polynomial mapping relationship between pixel coordinates and absolute phase to working height.

[0010] Optionally, the acquisition of front and back images of the checkerboard calibration board at several different working heights within the effective working distance range of the structured light 3D camera specifically includes: Place the checkerboard calibration plate on the lifting platform, ensuring that the direction of movement of the lifting platform is perpendicular to the calibration plate; The control platform moves gradually from the near working position of the structured light 3D camera to its far working position, or from the far working position of the structured light 3D camera to its near working position, according to a preset step size △z. Let the initial working height of the lifting platform be z0, then the working height corresponding to the i-th step movement of the lifting platform is z. i =z0+i△z, at each working height, several coded stripe patterns are projected onto the checkerboard calibration board, and the front and back images of the checkerboard calibration board are acquired simultaneously to obtain multiple sets of front and back images. The coded stripe pattern includes: a phase-shift coded pattern, a Gray code coded pattern, and a line-shift coded pattern.

[0011] Optionally, the step of calculating the modulation image corresponding to the front image and the absolute phase image corresponding to the back image specifically includes: Calculate the modulation image corresponding to each group of positive images and the absolute phase image corresponding to each group of back images.

[0012] Optionally, the step of extracting the set of corner coordinates of the modulated image and calculating the conversion coefficient from pixel coordinates to three-dimensional world coordinates specifically includes: Corner detection is performed using regulated images, corner coordinate sets are extracted, and corresponding initial 3D world coordinate sets are established. Find the corner point closest to the center of the modulation image as the center reference point, calculate the offset based on the center reference point, and update the world coordinates of other corner points in the modulation image: Using the updated 3D world coordinates and corner coordinates, calculate the conversion coefficients from pixel coordinates to 3D world coordinates in images captured by a structured light 3D camera.

[0013] Optionally, the step of using a modulated image to perform corner detection, extracting a set of corner coordinates, and establishing a corresponding initial set of three-dimensional world coordinates specifically includes: Corner detection is performed using a modulated image, and the set of corner coordinates is extracted. The method is as follows: Set M layers of shooting positions within the effective working distance range of the structured light 3D camera, with each layer shooting position corresponding to a modulation image; Extract the set of corner coordinates of the i-th modulation image: i = 1, 2, 3, ..., M-1; Where i represents the layer index corresponding to the modulation image, j is the corner index, and K i Let be the total number of corner points in the i-th tone image; Let J be the pixel coordinates of the j-th corner point of the i-th modulation image; Establish the corresponding initial set of 3D world coordinates: , for The corresponding corner points' XY coordinates in the three-dimensional world coordinate system; Among them, Z i The working height coordinates of the chessboard calibration board.

[0014] Optionally, finding the corner point closest to the center of the modulation image as the center reference point, and calculating the offset based on the center reference point to update the world coordinates of other corner points in the modulation image, specifically includes: Let the coordinates of the image center C be: Then the index s of the central reference point is: ; Let j be the coordinates of the j-th corner point of the i-th modulation image; The method for calculating world coordinate offset based on the central reference point is as follows: ; , t represents the XY coordinates of the corner point closest to the central reference point in the three-dimensional world coordinate system, and t is the index of the corner point closest to the central reference point. , The XY coordinates of the central reference point in the three-dimensional world coordinate system; Update the world coordinates of all corner points of the i-th modulation image as follows: .

[0015] Optionally, the method for obtaining the projection matrix of the structured light 3D camera through direct linear transformation is as follows: The camera imaging process can be described as a perspective projection transformation from three-dimensional world coordinates to pixel coordinates of a two-dimensional image. Let the world coordinate point be... The corresponding image coordinates are The projection transformation relationship can be expressed as: , , ; Where K is the camera intrinsic parameter. For camera external parameters, and This is the equivalent focal length in pixel coordinates. The projection relationship can then be expressed as: , ; Construct a direct linear transformation equation, let: L0=m 11 L1=m 12 L2=m 13 L3=m 14 L4=m 21 L5=m 22 L6=m 23 L7=m 24 L8=m 31 L9=m 32 L 10 =m 33 L 11 =m 34 ; Normalized L 11 =1, then the equation becomes: , ; The system of equations for direct linear transformation is obtained by rearranging the equations as follows: ; Solving the system of equations for the direct linear transformation yields the projection matrix L: .

[0016] Optionally, the method for extracting the intrinsic and extrinsic parameters of the structured light 3D camera from the projection matrix is ​​as follows: The coordinates of the principal point of the camera's intrinsic parameters are: , ; Define the normalization factor: ; Calculate the equivalent focal length and To obtain the camera's intrinsic parameters; and The formula for calculation is: , ; Finally, based on the obtained camera intrinsic parameters, the camera extrinsic parameters are calculated.

[0017] Optionally, establishing a rational polynomial mapping relationship between pixel coordinates and absolute phase to working height based on the absolute phase image specifically includes: A multi-parameter rational polynomial model is used to achieve accurate mapping of pixel coordinates and phase to working height: The rational polynomial model is constructed as follows: , It is the absolute phase of the absolute phase image; The numerator polynomial is: ; The denominator polynomial is: .

[0018] Optionally, the search method for the corner point closest to the central reference point is as follows: In the set Find the index t of the corresponding corner point; Where R is the radius of the search region, calculated as follows: .

[0019] Secondly, the present invention provides a rapid calibration system for a monocular single-projection structured light 3D camera, characterized in that it comprises: The image acquisition module is used to acquire front and back images of the checkerboard calibration board at several different working heights within the effective working distance range of the structured light 3D camera. The image preprocessing module, electrically connected to the image acquisition module, is used to calculate the modulation image corresponding to the front image and the absolute phase image corresponding to the back image, respectively. The conversion coefficient calculation module is electrically connected to the image preprocessing module and is used to extract the set of corner coordinates of the modulated image and calculate the conversion coefficient from pixel coordinates to three-dimensional world coordinates. The camera calibration module is electrically connected to the conversion coefficient calculation module and is used to obtain the projection matrix of the structured light 3D camera through direct linear transformation, and to extract the intrinsic and extrinsic parameters of the structured light 3D camera from the projection matrix. The coordinate mapping module is electrically connected to the camera calibration module and is used to establish a rational polynomial mapping relationship between pixel coordinates and absolute phase to working height based on the absolute phase image.

[0020] Optionally, the rapid calibration system further includes a lifting platform for placing the checkerboard calibration plate, the lifting platform moving in a direction perpendicular to the calibration plate; The lifting platform can be controlled to move gradually from the near working position of the structured light 3D camera to its far working position, or from the far working position of the structured light 3D camera to its near working position, according to a preset step size △z. Let the initial working height of the lifting platform be z0, then the working height corresponding to the i-th step movement of the lifting platform is z. i =z0+i△z; The image acquisition module is specifically used to project several coded stripe patterns onto the checkerboard calibration board at each working height, and simultaneously acquire the front and back images of the checkerboard calibration board to obtain multiple sets of front and back images. The coded stripe pattern includes: a phase-shift coded pattern, a Gray code coded pattern, and a line-shift coded pattern.

[0021] Optionally, the image preprocessing module is specifically used to: calculate the modulation image corresponding to each group of positive images and the absolute phase image corresponding to each group of back images.

[0022] Optionally, the conversion coefficient calculation module is specifically used for: Corner detection is performed using regulated images, corner coordinate sets are extracted, and corresponding initial 3D world coordinate sets are established. Find the corner point closest to the center of the modulation image as the center reference point, calculate the offset based on the center reference point, and update the world coordinates of other corner points in the modulation image: Using the updated 3D world coordinates and corner coordinates, calculate the conversion coefficients from pixel coordinates to 3D world coordinates in images captured by a structured light 3D camera.

[0023] Optionally, the step of using a modulated image to perform corner detection, extracting a set of corner coordinates, and establishing a corresponding initial set of three-dimensional world coordinates specifically includes: Corner detection is performed using a modulated image, and the set of corner coordinates is extracted. The method is as follows: Set M layers of shooting positions within the effective working distance range of the structured light 3D camera, with each layer shooting position corresponding to a modulation image; Extract the set of corner coordinates of the i-th modulation image: i = 1, 2, 3, ..., M-1; Where i represents the layer index corresponding to the modulation image, j is the corner index, and K i Let be the total number of corner points in the i-th tone image; Let J be the pixel coordinates of the j-th corner point of the i-th modulation image; Establish the corresponding initial set of 3D world coordinates: , for The corresponding corner points' XY coordinates in the three-dimensional world coordinate system; Among them, Z i The working height coordinates of the chessboard calibration board.

[0024] Optionally, finding the corner point closest to the center of the modulation image as the center reference point, and calculating the offset based on the center reference point to update the world coordinates of other corner points in the modulation image, specifically includes: Let the coordinates of the image center C be: Then the index s of the central reference point is: ; Let j be the coordinates of the j-th corner point of the i-th modulation image; The method for calculating world coordinate offset based on the central reference point is as follows: ; , t represents the XY coordinates of the corner point closest to the central reference point in the three-dimensional world coordinate system, and t is the index of the corner point closest to the central reference point. , The XY coordinates of the central reference point in the three-dimensional world coordinate system; Update the world coordinates of all corner points of the i-th modulation image as follows: .

[0025] Optionally, the method for obtaining the projection matrix of the structured light 3D camera through direct linear transformation is as follows: The camera imaging process can be described as a perspective projection transformation from three-dimensional world coordinates to pixel coordinates of a two-dimensional image. Let the world coordinate point be... The corresponding image coordinates are The projection transformation relationship can be expressed as: , , ; Where K is the camera intrinsic parameter. For camera external parameters, and This is the equivalent focal length in pixel coordinates. The projection relationship can then be expressed as: , ; Construct a direct linear transformation equation, let: L0=m 11 L1=m 12 L2=m 13L3=m 14 L4=m 21 L5=m 22 L6=m 23 L7=m 24 L8=m 31 L9=m 32 L 10 =m 33 L 11 =m 34 ; Normalized L 11 =1, then the equation becomes: , ; The system of equations for direct linear transformation is obtained by rearranging the equations as follows: ; Solving the system of equations for the direct linear transformation yields the projection matrix L: .

[0026] Optionally, the method for extracting the intrinsic and extrinsic parameters of the structured light 3D camera from the projection matrix is ​​as follows: The coordinates of the principal point of the camera's intrinsic parameters are: , ; Define the normalization factor: ; Calculate the equivalent focal length and To obtain the camera's intrinsic parameters; and The formula for calculation is: , ; Finally, based on the obtained camera intrinsic parameters, the camera extrinsic parameters are calculated.

[0027] Optionally, the coordinate mapping module is specifically used for: A multi-parameter rational polynomial model is used to achieve accurate mapping of pixel coordinates and phase to working height: The rational polynomial model is constructed as follows: , It is the absolute phase of the absolute phase image; The numerator polynomial is: ; The denominator polynomial is: .

[0028] Optionally, the search method for the corner point closest to the central reference point is as follows: In the set Find the index t of the corresponding corner point; Where R is the radius of the search region, calculated as follows: .

[0029] Thirdly, the present invention provides a computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to implement a rapid calibration method for a monocular single-projection structured light 3D camera as described above.

[0030] Fourthly, the present invention also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements a rapid calibration method for a monocular single-projection structured light 3D camera as described above.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows: This application calculates the conversion coefficient from pixel coordinates to 3D world coordinates by using the corner coordinates of the modulated image. It uses rational polynomial mapping to realize the mapping of pixel coordinates and absolute phase to working height, achieving coordinate system unification for data of different heights. It eliminates the need for complex pose estimation, realizes rapid conversion from image coordinates to world coordinates, has high computational efficiency, significantly improves calibration accuracy, and is suitable for real-time 3D reconstruction. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a flowchart illustrating a rapid calibration method for a monocular, single-projection structured light 3D camera, as provided in an embodiment of the present invention.

[0034] Figure 2 This is a modulation image provided in an embodiment of the present invention.

[0035] Figure 3 An absolute phase image is provided for an embodiment of the present invention.

[0036] Figure 4 This is an architecture diagram of a rapid calibration system for a monocular single-projection structured light 3D camera provided in an embodiment of the present invention. Detailed Implementation

[0037] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0038] Example 1: Please refer to Figure 1 , Figure 1 A flowchart illustrating a rapid calibration method for a monocular single-projection structured light 3D camera provided in an embodiment of the present invention is shown. The method specifically includes: Step 110: Collect front and back images of the checkerboard calibration board at several different working heights within the effective working distance range of the structured light 3D camera.

[0039] Step 110 specifically includes: Step 111: Place the checkerboard calibration plate on the lifting platform, ensuring that the direction of movement of the lifting platform is perpendicular to the calibration plate.

[0040] Step 112: Control the lifting platform to move gradually from the near working position of the structured light 3D camera to its far working position, or from the far working position of the structured light 3D camera to its near working position, according to the preset step length △z. Let the initial working height of the lifting platform be z0, then the working height corresponding to the i-th step movement of the lifting platform is z. i =z0+i△z.

[0041] Step 113: At each working height, project several coded stripe patterns onto the checkerboard calibration board, and simultaneously acquire the front and back images of the checkerboard calibration board to obtain multiple sets of front and back images.

[0042] In step 113, at each location, a front image (a front image with black and white checkerboard) and a back image (the calibration board is flipped over and photographed again, and the projected encoded image is the same) of the checkerboard calibration board are taken. The encoded stripe pattern includes, but is not limited to: phase shift encoded pattern, Gray code encoded pattern and line shift encoded pattern.

[0043] Step 120: Calculate the modulation image corresponding to the positive image and the absolute phase image corresponding to the back image, respectively.

[0044] Specifically, after obtaining multiple sets of positive and backplane images, the modulation image corresponding to each set of positive images and the absolute phase image corresponding to each set of backplane images are calculated, such as... Figure 2 and Figure 3As shown.

[0045] It is understood that the calculation methods for modulation images and absolute phase images are conventional techniques in this field, so their principles and calculation processes will not be elaborated in this embodiment.

[0046] Step 130: Extract the set of corner coordinates of the modulation image and calculate the conversion coefficient from pixel coordinates to three-dimensional world coordinates.

[0047] Step 130 specifically includes: Step 131: Use the modulation image to detect corner points, extract the set of corner point coordinates, and establish the corresponding initial three-dimensional world coordinate set.

[0048] Specifically, corner detection is performed using a modulated image to extract the set of corner coordinates. The method is as follows: Set M layers of shooting positions within the effective working distance range of the structured light 3D camera, with each layer shooting position corresponding to a modulation image; Extract the set of corner coordinates of the i-th modulation image: i = 1, 2, 3, ..., M-1; Where i represents the layer index corresponding to the modulation image, j is the corner index, and K i Let be the total number of corner points in the i-th tone image; Let J be the pixel coordinates of the j-th corner point of the i-th modulation image; Establish the corresponding initial set of 3D world coordinates: , for The corresponding corner points' XY coordinates in the three-dimensional world coordinate system; Among them, Z i The working height coordinates of the chessboard calibration board.

[0049] Step 132: Find the corner point closest to the center of the modulation image as the center reference point, calculate the offset based on the center reference point, and update the world coordinates of other corner points in the modulation image.

[0050] Let the coordinates of the image center C be: Then the index s of the central reference point is: ; Let j be the coordinates of the j-th corner point of the i-th modulation image; The method for calculating world coordinate offset based on the central reference point is as follows: ; , t represents the XY coordinates of the corner point closest to the central reference point in the three-dimensional world coordinate system, and t is the index of the corner point closest to the central reference point. , The XY coordinates of the central reference point in the three-dimensional world coordinate system; Update the world coordinates of all corner points of the i-th modulation image as follows: .

[0051] The method for finding the corner point closest to the central reference point is as follows: In the set Find the index t of the corresponding corner point; Where R is the radius of the search region, calculated as follows: .

[0052] Step 133: Using the updated 3D world coordinates and corner coordinates, calculate the conversion coefficient from pixel coordinates to 3D world coordinates of the image captured by the structured light 3D camera.

[0053] Step 140: Obtain the projection matrix of the structured light 3D camera through direct linear transformation, and extract the intrinsic and extrinsic parameters of the structured light 3D camera from the projection matrix.

[0054] Specifically, the method for obtaining the projection matrix is ​​as follows: The camera imaging process can be described as a perspective projection transformation from three-dimensional world coordinates to pixel coordinates of a two-dimensional image. Let the world coordinate point be... The corresponding image coordinates are The projection transformation relationship can be expressed as: , , ; here K is the scale factor, and K is the camera intrinsic parameter. For camera external parameters, and This is the equivalent focal length in pixel coordinates. The projection relationship can then be expressed as: , ; Construct a direct linear transformation equation, let: L0=m 11 L1=m 12 L2=m 13 L3=m 14 L4=m 21 L5=m 22 L6=m 23 L7=m 24L8=m 31 L9=m 32 L 10 =m 33 L 11 =m 34 ; Normalized L 11 =1, then the equation becomes: , ; The system of equations for direct linear transformation is obtained by rearranging the equations as follows: ; Solving the system of equations for the direct linear transformation yields the projection matrix L: .

[0055] Furthermore, for ease of understanding, the specific methods for constructing and solving overdetermined systems of equations are as follows: Construct coefficient matrix A 2N*11 and observation vector U 2N*1 ,make ; Where A is a 2N*11 coefficient matrix, N is the total number of corner points in all layers (A contains the world coordinates and pixel coordinates of all corner points); U is a 2N*1 observation vector containing the pixel coordinates of all corner points; The projection matrix is ​​obtained by solving using the least squares method.

[0056] The calculation method for the intrinsic and extrinsic parameters of a structured light 3D camera is as follows: The coordinates of the principal point of the camera's intrinsic parameters are: , ; Define the normalization factor: ; Calculate the equivalent focal length and To obtain the camera's intrinsic parameters; and The formula for calculation is: , ; Finally, based on the obtained camera intrinsic parameters, the camera extrinsic parameters are calculated: .

[0057] Step 150: Based on the absolute phase image, establish a rational polynomial mapping relationship between pixel coordinates and absolute phase to working height.

[0058] Based on the absolute phase of each layer, establish a rational polynomial mapping relationship between pixel coordinates and absolute phase to working height Z: A multi-parameter rational polynomial model is used to achieve accurate mapping of pixel coordinates and phase to working height: The rational polynomial model is constructed as follows: , It is the absolute phase of the absolute phase image; The numerator polynomial is: ; The denominator polynomial is: .

[0059] Compared with existing technologies, this method has the following significant advantages: (1) The calibration operation is simple. By utilizing the precise vertical displacement characteristics of the lifting platform, there is no need to precisely control the horizontal position and attitude of the calibration plate, making the operation simple and easy, and facilitating the automation of the entire calibration process; (2) Automatic coordinate system alignment By using a center reference point search and offset compensation algorithm, coordinate system unification for data at different heights is automatically achieved without the need for complex pose estimation. (3) High reconstruction efficiency A linear mapping model is used to achieve a fast conversion from image coordinates to world coordinates, which is computationally efficient and suitable for real-time 3D reconstruction. (4) High calibration accuracy Multi-layer data fusion and block optimization strategies significantly improve calibration accuracy.

[0060] Example 2: Please refer to Figure 4 , Figure 4 for Figure 4 This is an architectural diagram of a rapid calibration system for a monocular single-projection structured light 3D camera provided in an embodiment of the present invention. The system specifically includes: Image acquisition module 20 is used to acquire front and back images of the checkerboard calibration board at several different working heights within the effective working distance range of the structured light 3D camera. The image preprocessing module 30 is electrically connected to the image acquisition module 20 and is used to calculate the modulation image corresponding to the front plate image and the absolute phase image corresponding to the back plate image, respectively. The conversion coefficient calculation module 40 and the image preprocessing module 30 are electrically connected to extract the set of corner coordinates of the modulated image and calculate the conversion coefficient from pixel coordinates to three-dimensional world coordinates. The camera calibration module 50 and the electrical connection conversion coefficient calculation module 40 are used to obtain the projection matrix of the structured light 3D camera through direct linear transformation, and to extract the intrinsic and extrinsic parameters of the structured light 3D camera from the projection matrix. The coordinate mapping module 60 is electrically connected to the camera calibration module 50 and is used to establish a rational polynomial mapping relationship between pixel coordinates and absolute phase to working height based on the absolute phase image.

[0061] Furthermore, the system also includes a lifting platform 10 for placing the chessboard calibration plate, the movement direction of the lifting platform 10 being perpendicular to the chessboard calibration plate; The lifting platform 10 can be controlled to move gradually from the near working position of the structured light 3D camera to its far working position, or from the far working position of the structured light 3D camera to its near working position, according to a preset step length △z. Let the initial working height of the lifting platform be z0, then the working height corresponding to the i-th step movement of the lifting platform is z. i =z0+i△z; The image acquisition module is specifically used to project several coded stripe patterns onto the checkerboard calibration board at each working height, and simultaneously acquire the front and back images of the checkerboard calibration board to obtain multiple sets of front and back images. The coded stripe patterns include: phase-shift coded patterns, Gray code coded patterns, and line-shift coded patterns.

[0062] Since the rapid calibration method for a monocular single-projection structured light 3D camera has been described in detail in Embodiment 1, it will not be repeated in this embodiment.

[0063] Example 3: This embodiment also provides a computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to implement a rapid calibration method for a monocular single-projection structured light 3D camera as described in Embodiment 1.

[0064] Since the rapid calibration method for a monocular single-projection structured light 3D camera has been described in detail in Embodiment 1, it will not be repeated in this embodiment.

[0065] Example 4: The present invention also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements a rapid calibration method for a monocular single-projection structured light 3D camera as described in Embodiment 1.

[0066] Since the rapid calibration method for a monocular single-projection structured light 3D camera has been described in detail in Embodiment 1, it will not be repeated in this embodiment.

[0067] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware, or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0068] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0069] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A rapid calibration method for a monocular single-projection structured light 3D camera, characterized in that, include: Images of the front and back of the checkerboard calibration board at several different working heights within the effective working distance range of the structured light 3D camera were acquired respectively. Calculate the modulation image corresponding to the front plate image and the absolute phase image corresponding to the back plate image, respectively. Extract the set of corner coordinates from the modulated image and calculate the conversion coefficient from pixel coordinates to three-dimensional world coordinates; The projection matrix of the structured light 3D camera is obtained by direct linear transformation, and the intrinsic and extrinsic parameters of the structured light 3D camera are extracted from the projection matrix. Based on the absolute phase image, establish a rational polynomial mapping relationship between pixel coordinates and absolute phase to working height.

2. The rapid calibration method for a monocular single-projection structured light 3D camera according to claim 1, characterized in that, The acquisition of front and back images of the checkerboard calibration board at several different working heights within the effective working distance range of the structured light 3D camera specifically includes: Place the chessboard calibration plate on the lifting platform, ensuring that the direction of movement of the lifting platform is perpendicular to the chessboard calibration plate; The control platform moves gradually from the near working position of the structured light 3D camera to its far working position, or from the far working position of the structured light 3D camera to its near working position, according to a preset step size △z. Let the initial position of the lifting platform be the working height z0, then the working height corresponding to the i-th step of the lifting platform is z i =z0+i△z, at each working height, a number of encoding stripe images are projected onto the checkerboard calibration plate, and the front and back plate images of the checkerboard calibration plate are synchronously collected to obtain multiple groups of front plate images and back plate images; The coded stripe pattern includes: a phase-shift coded pattern, a Gray code coded pattern, and a line-shift coded pattern.

3. The rapid calibration method for a monocular single-projection structured light 3D camera according to claim 2, characterized in that, The calculation of the modulation image corresponding to the positive image and the absolute phase image corresponding to the back image specifically includes: Calculate the modulation image corresponding to each group of positive images and the absolute phase image corresponding to each group of back images.

4. The rapid calibration method for a monocular single-projection structured light 3D camera according to claim 2, characterized in that, The extraction of the set of corner coordinates from the modulated image and the calculation of the conversion coefficient from pixel coordinates to three-dimensional world coordinates specifically include: Corner detection is performed using regulated images, corner coordinate sets are extracted, and corresponding initial 3D world coordinate sets are established. Find the corner point closest to the center of the modulation image as the center reference point, calculate the offset based on the center reference point, and update the world coordinates of other corner points in the modulation image: Using the updated 3D world coordinates and corner coordinates, calculate the conversion coefficients from pixel coordinates to 3D world coordinates in images captured by a structured light 3D camera.

5. A rapid calibration method for a monocular single-projection structured light 3D camera according to claim 4, characterized in that, The process of using modulated images for corner detection, extracting a set of corner coordinates, and establishing a corresponding initial set of 3D world coordinates specifically includes: Corner detection is performed using a modulated image, and the set of corner coordinates is extracted. The method is as follows: Set M layers of shooting positions within the effective working distance range of the structured light 3D camera, with each layer shooting position corresponding to a modulation image; Extract the set of corner coordinates of the i-th modulation image: ,i=1,2,3,...,M-1; Where i represents the layer index corresponding to the modulation image, j is the corner index, and K i Let be the total number of corner points in the i-th tone image; Let J be the pixel coordinates of the j-th corner point of the i-th modulation image; Establish the corresponding initial set of 3D world coordinates: , for The corresponding corner points' XY coordinates in the three-dimensional world coordinate system; wherein Z i is the working height coordinate of the checkerboard calibration plate.

6. A rapid calibration method for a monocular single-projection structured light 3D camera according to claim 5, characterized in that, The process of finding the corner point closest to the center of the modulation image as the center reference point, and calculating the offset based on the center reference point to update the world coordinates of other corner points in the modulation image, specifically includes: Let the coordinates of the image center C be: Then the index s of the central reference point is: ; Let j be the coordinates of the j-th corner point of the i-th modulation image; The method for calculating world coordinate offset based on the central reference point is as follows: ； , t represents the XY coordinates of the corner point closest to the central reference point in the three-dimensional world coordinate system, and t is the index of the corner point closest to the central reference point. , The XY coordinates of the central reference point in the three-dimensional world coordinate system; Update the world coordinates of all corner points of the i-th modulation image as follows: 。 7. A rapid calibration method for a monocular single-projection structured light 3D camera according to claim 6, characterized in that, The method for obtaining the projection matrix of the structured light 3D camera through direct linear transformation is as follows: The camera imaging process can be described as a perspective projection transformation from three-dimensional world coordinates to pixel coordinates of a two-dimensional image. Let the world coordinate point be... The corresponding image coordinates are The projection transformation relationship can be expressed as: ， ， ； Where K is the camera intrinsic parameter. For camera external parameters, and This is the equivalent focal length in pixel coordinates. The projection relationship can then be expressed as: ， ； Construct a direct linear transformation equation, let: L0=m 11 L1=m 12 L2=m 13 L3=m 14 L4=m 21 L5=m 22 L6=m 23 L7=m 24 L8=m 31 L9=m 32 L 10 =m 33 L 11 =m 34 ; Normalized L 11 =1, then the equation becomes: ， ； The system of equations for direct linear transformation is obtained by rearranging the equations as follows: ； Solving the system of equations for the direct linear transformation yields the projection matrix L: 。 8. A rapid calibration method for a monocular single-projection structured light 3D camera according to claim 7, characterized in that, The method for extracting the intrinsic and extrinsic parameters of the structured light 3D camera from the projection matrix is ​​as follows: The coordinates of the principal point of the camera's intrinsic parameters are: ， ； Define the normalization factor: ； Calculate the equivalent focal length and To obtain the camera's intrinsic parameters; and The formula for calculation is: ， ； Finally, based on the obtained camera intrinsic parameters, the camera extrinsic parameters are calculated.

9. A rapid calibration method for a monocular single-projection structured light 3D camera according to claim 8, characterized in that, The step of establishing a rational polynomial mapping relationship between pixel coordinates and absolute phase to working height based on the absolute phase image specifically includes: A multi-parameter rational polynomial model is used to achieve accurate mapping of pixel coordinates and phase to working height: The rational polynomial model is constructed as follows: , It is the absolute phase of the absolute phase image; The numerator polynomial is: ； The denominator polynomial is: .

10. A rapid calibration method for a monocular single-projection structured light 3D camera according to claim 6, characterized in that, The method for finding the corner point closest to the central reference point is as follows: In the set Find the index t of the corresponding corner point; Where R is the radius of the search region, calculated as follows: 。 11. A rapid calibration system for a monocular single-projection structured light 3D camera, characterized in that, include: The image acquisition module is used to acquire front and back images of the checkerboard calibration board at several different working heights within the effective working distance range of the structured light 3D camera. The image preprocessing module, electrically connected to the image acquisition module, is used to calculate the modulation image corresponding to the front image and the absolute phase image corresponding to the back image, respectively. The conversion coefficient calculation module is electrically connected to the image preprocessing module and is used to extract the set of corner coordinates of the modulated image and calculate the conversion coefficient from pixel coordinates to three-dimensional world coordinates. The camera calibration module is electrically connected to the conversion coefficient calculation module and is used to obtain the projection matrix of the structured light 3D camera through direct linear transformation, and to extract the intrinsic and extrinsic parameters of the structured light 3D camera from the projection matrix. The coordinate mapping module is electrically connected to the camera calibration module and is used to establish a rational polynomial mapping relationship between pixel coordinates and absolute phase to working height based on the absolute phase image.

12. A rapid calibration system for a monocular single-projection structured light 3D camera according to claim 11, characterized in that, It also includes a lifting platform for placing the chessboard calibration plate, the lifting platform moving in a direction perpendicular to the chessboard calibration plate; The lifting platform can be controlled to move gradually from the near working position of the structured light 3D camera to its far working position, or from the far working position of the structured light 3D camera to its near working position, according to a preset step size △z. Let the initial working height of the lifting platform be z0, then the working height corresponding to the i-th step movement of the lifting platform is z. i =z0+i△z; The image acquisition module is specifically used to project several coded stripe patterns onto the checkerboard calibration board at each working height, and simultaneously acquire the front and back images of the checkerboard calibration board to obtain multiple sets of front and back images. The coded stripe pattern includes: a phase-shift coded pattern, a Gray code coded pattern, and a line-shift coded pattern.

13. A rapid calibration system for a monocular single-projection structured light 3D camera according to claim 12, characterized in that, The image preprocessing module is specifically used to: calculate the modulation image corresponding to each group of front images and the absolute phase image corresponding to each group of back images.

14. A rapid calibration system for a monocular single-projection structured light 3D camera according to claim 12, characterized in that, The conversion coefficient calculation module is specifically used for: Corner detection is performed using regulated images, corner coordinate sets are extracted, and corresponding initial 3D world coordinate sets are established. Find the corner point closest to the center of the modulation image as the center reference point, calculate the offset based on the center reference point, and update the world coordinates of other corner points in the modulation image: Using the updated 3D world coordinates and corner coordinates, calculate the conversion coefficients from pixel coordinates to 3D world coordinates in images captured by a structured light 3D camera.

15. A rapid calibration system for a monocular single-projection structured light 3D camera according to claim 14, characterized in that, The process of using modulated images for corner detection, extracting a set of corner coordinates, and establishing a corresponding initial set of 3D world coordinates specifically includes: Corner detection is performed using a modulated image, and the set of corner coordinates is extracted. The method is as follows: Set M layers of shooting positions within the effective working distance range of the structured light 3D camera, with each layer shooting position corresponding to a modulation image; Extract the set of corner coordinates of the i-th modulation image: ,i=1,2,3,...,M-1; Where i represents the layer index corresponding to the modulation image, j is the corner index, and K i Let be the total number of corner points in the i-th tone image; Let J be the pixel coordinates of the j-th corner point of the i-th modulation image; Establish the corresponding initial set of 3D world coordinates: , for The corresponding corner points' XY coordinates in the three-dimensional world coordinate system; Among them, Z i The working height coordinates of the chessboard calibration board.

16. A rapid calibration system for a monocular single-projection structured light 3D camera according to claim 15, characterized in that, The process of finding the corner point closest to the center of the modulation image as the center reference point, and calculating the offset based on the center reference point to update the world coordinates of other corner points in the modulation image, specifically includes: Let the coordinates of the image center C be: Then the index s of the central reference point is: ; Let j be the coordinates of the j-th corner point of the i-th modulation image; The method for calculating world coordinate offset based on the central reference point is as follows: ； , t represents the XY coordinates of the corner point closest to the central reference point in the three-dimensional world coordinate system, and t is the index of the corner point closest to the central reference point. , The XY coordinates of the central reference point in the three-dimensional world coordinate system; Update the world coordinates of all corner points of the i-th modulation image as follows: 。 17. A rapid calibration system for a monocular single-projection structured light 3D camera according to claim 16, characterized in that, The method for obtaining the projection matrix of the structured light 3D camera through direct linear transformation is as follows: The camera imaging process can be described as a perspective projection transformation from three-dimensional world coordinates to pixel coordinates of a two-dimensional image. Let the world coordinate point be... The corresponding image coordinates are The projection transformation relationship can be expressed as: ， ， ； Where K is the camera intrinsic parameter. For camera external parameters, and This is the equivalent focal length in pixel coordinates. The projection relationship can then be expressed as: ， ； Construct a direct linear transformation equation, let: L0=m 11 L1=m 12 L2=m 13 L3=m 14 L4=m 21 L5=m 22 L6=m 23 L7=m 24 L8=m 31 L9=m 32 L 10 =m 33 L 11 =m 34 ; Normalized L 11 =1, then the equation becomes: ， ； The system of equations for direct linear transformation is obtained by rearranging the equations as follows: ； Solving the system of equations for the direct linear transformation yields the projection matrix L: 。 18. A rapid calibration system for a monocular single-projection structured light 3D camera according to claim 17, characterized in that, The method for extracting the intrinsic and extrinsic parameters of the structured light 3D camera from the projection matrix is ​​as follows: The coordinates of the principal point of the camera's intrinsic parameters are: ， ； Define the normalization factor: ； Calculate the equivalent focal length and To obtain the camera's intrinsic parameters; and The formula for calculation is: ， ； Finally, based on the obtained camera intrinsic parameters, the camera extrinsic parameters are calculated.

19. A rapid calibration system for a monocular single-projection structured light 3D camera according to claim 18, characterized in that, The coordinate mapping module is specifically used for: A multi-parameter rational polynomial model is used to achieve accurate mapping of pixel coordinates and phase to working height: The rational polynomial model is constructed as follows: , It is the absolute phase of the absolute phase image; The numerator polynomial is: ； The denominator polynomial is: .

20. A rapid calibration system for a monocular single-projection structured light 3D camera according to claim 16, characterized in that, The method for finding the corner point closest to the central reference point is as follows: In the set Find the index t of the corresponding corner point; Where R is the radius of the search region, calculated as follows: 。 21. A computer-readable storage medium storing at least one instruction, characterized in that, The instructions are loaded and executed by the processor to implement a rapid calibration method for a monocular single-projection structured light 3D camera as described in any one of claims 1-10.

22. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, a rapid calibration method for a monocular single-projection structured light 3D camera as described in any one of claims 1-10 is implemented.

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