A high-precision binocular structured light measurement method using bipolar line acceleration

Abstract

The application discloses a high-precision binocular structured light measurement method using bipolar line acceleration, which comprises the following steps: firstly, after calibrating a binocular structured light system, a projector and a second camera are combined into a monocular structured light system, and high-efficiency and robust monocular structured light calibration is carried out based on an encoding calibration board guide; then, the intersection of the mapping epipolar line of a same point to the second camera in the monocular system and the mapping epipolar line of the same point to the second camera in the binocular system is calculated to obtain the matching initial value of two phase maps; finally, the phase corresponding points of the two phase maps are accurately searched; the high-efficiency and accurate matching of the phase corresponding points in two views of the binocular structured light is realized, and the method has the advantages of fast stereo matching speed and high three-dimensional reconstruction precision.

Description

Technical Field

[0001] This invention relates to the field of structured light three-dimensional measurement technology, and in particular to a high-precision binocular structured light measurement method using bipolar linear acceleration. Technical Background Structured light 3D measurement offers advantages such as non-contact operation, high precision, and full-field measurement. Common measurement schemes primarily involve monocular reconstruction and binocular reconstruction. A monocular reconstruction system consists of a projector and a camera. The camera captures the projected fringe pattern, and the phase encoding principle is used to directly calculate the projected pixel coordinates, obtaining the corresponding points between the camera and the projector, followed by 3D reconstruction. A binocular reconstruction system consists of a projector and two cameras. Both cameras simultaneously capture the projected fringe pattern, and then stereo matching of the phase patterns is performed.

[0002] In binocular reconstruction, commonly used phase stereo matching methods mainly include horizontal search and epipolar search after stereo correction. Stereo correction involves projecting the image and then resampling and interpolating it. When measuring surfaces with complex features and varying curvature, this can introduce non-negligible image interpolation errors, affecting matching accuracy. Epipolar search phase matching methods retrieve horizontal and vertical phase information from the original image one by one. In structured light, temporal phase encoding is completely independent in the spatial domain. Therefore, epipolar search can reduce the impact of complex curvature on phase information to some extent, which is beneficial to the accuracy of phase matching. For example, the paper "A Method for Measuring Surface Deformation Based on Reprojection and 3D-DIC" published on CNKI mentions that using more efficient image correction methods may introduce deviations. However, the epipolar search method requires calculating the epipolar line in the second view for each image coordinate in the first view and performing distortion processing on the pixels on the epipolar line. This computational load is large, limiting the matching and reconstruction speed. In stereo matching of binocular structured light using the epipolar search method, if an initial matching value can be given, the computational cost of searching for phase-corresponding points along the epipolar line can be greatly reduced, effectively improving the speed of phase stereo matching and increasing computational efficiency.

[0003] In summary, existing binocular structured light measurement schemes based on epipolar search involve a lot of redundant calculations during phase matching, making it necessary to investigate a new method for accelerating stereo phase matching in binocular structured light. Summary of the Invention

[0004] To overcome the shortcomings of the prior art, this invention proposes a high-precision binocular structured light measurement method using bipolar acceleration. The method solves the high-precision epipolar mapping of the phase coordinates in the projector in the second view by using the phase information of corresponding points, and obtains the image intersection point with the epipolar mapping in the binocular structured light system. This intersection point is used as the initial value for matching before performing precise phase search. This reduces the computational load of brute-force search methods and has the advantages of fast stereo matching speed and high 3D reconstruction accuracy.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A high-precision binocular structured light measurement method using bipolar linear acceleration includes the following steps: S1: The binocular structured light system consists of two cameras and a projector, wherein the projector and the second camera form a monocular structured light system; firstly, the binocular structured light system is calibrated using traditional methods, then the projector and the second camera are combined to form a monocular structured light system, and the monocular structured light system is calibrated based on the guidance of the coding calibration board; S2: In actual measurement, the projector projects two sets of horizontal and vertical stripes onto the object to be measured. The two cameras capture them simultaneously. The first camera captures the first view and the second camera captures the second view. The horizontal and vertical phases of the fringe patterns captured by the cameras are calculated using the traditional multi-frequency phase-shift heterodyne method. S3: Solve for the coordinates in the projector and the polar line l in the second view based on the phase-corresponding point p1 in the first view captured by the first camera. c Using the phase corresponding point p of the projection view in a monocular structured light system proj Solve for the epipolar line l in the second view captured by the second camera. proj And calculate the polar line l in the second view. proj With polar line l c intersection point p2 0 ; S4: At the intersection point p2 of the two polar lines 0 Define a neighborhood, accurately search for phase values, and perform 3D reconstruction to achieve matching of corresponding phase points.

[0006] In the binocular structured light system, the two cameras and the projector are arranged horizontally, with the focal points of the two cameras and the projector intersecting and falling on the surface of the object to be measured.

[0007] Step S1, which involves calibrating the monocular structured light system based on the guidance of the encoding calibration board, specifically includes the following steps: S1-1: A calibration board with a black background and white dots is used. The markings on the calibration board include coded points and non-coded points. Each coded point consists of a non-coded point and several arc-shaped marks surrounding the non-coded point, which are used for subsequent initial calibration values. Each arc-shaped mark is located on the same circumference. S1-2: During calibration, the calibration board is placed in different poses within the effective depth of field of the camera and the projector. A set of vertical and horizontal phase-shifted fringes is projected for each pose. Simultaneously, the second camera is used to acquire fringe images under multiple poses. S1-3: For the acquired horizontal and vertical fringe images of the calibration board in each pose, the phase values ​​are calculated using the traditional multi-frequency heterodyne method; then, a set of phase shift images are superimposed in a weighted manner to form an image of the marker points to be detected. In the formula, Ic is the pixel intensity of the marker to be detected; n is the phase shift step number; Ii is the pixel intensity of the stripe pattern to be measured, i is the phase shift number; k is the weighting coefficient, the size of which is defined according to the brightness of the stripe image; Then, based on the superimposed image of the marker to be detected, the center of the marker is detected to obtain the coordinates (u, v) of the center of the marker. S1-4: Interpolate the phase values ​​at nearby integer pixel coordinates based on the center coordinates (u, v) of the marker point to obtain the phase value (P) corresponding to the center coordinates (u, v). h , P v This refers to the phase value of the marker point in the image captured by the camera; S1-5: Based on the phase value ((P) obtained in step S1-4 h , P v This refers to the phase value of the marker point in the image captured by the camera; based on the phase encoding relationship of the projected fringes, the coordinates of the corresponding point in the projector are calculated using the phase value obtained from the second view. : In the formula, N is the fringe frequency. , These represent the horizontal and vertical pixel counts of the projector, respectively.

[0008] S1-6: Based on the coordinates of the center of the coordinate marker (u, v) and the coordinates of the corresponding point on the projector... The system calibration of the two cameras is carried out. The system calibration is divided into single-camera calibration and stereo calibration. First, the second camera and the projector are calibrated by using the coding correspondence of the coding points. The intrinsic parameters A, extrinsic parameters [R|T] and distortion parameters Δ of the second camera and the projector are calculated and nonlinear optimization is performed as the initial values ​​for the calibration of the second camera and the projector. S1-7: Based on the initial calibration values ​​in S1-6, recalculate the coordinates p of the non-coded object point W in the calibration board in the second camera or projector: Here, p is the actual point coordinate in the image of the second camera or projector, Δ is the distortion vector, A is the intrinsic parameter matrix, and [R|T] is the extrinsic parameter matrix; When all coded and non-coded points on the calibration board are known, the correspondence between the non-coded points on the second camera, the projector, and the calibration board is obtained respectively. S1-8: Based on the correspondence between the positions of all marker points in the second camera and projector and their positions on the calibration board obtained in step S1-7, perform stereo calibration of the monocular system again using all coded and non-coded points. At the same time, calculate all parameters of the second camera and projector and use them as the final calibration result.

[0009] Step S3, which calculates the intersection of the two polar lines in the second view, involves the following steps: S3-1: Calculate the polar line l in the second view based on the coordinates of the phase corresponding point p1 in the first view. c : In the formula, F 1-2 This is the fundamental matrix between the first camera and the second camera.

[0010] S3-2: Based on the phase information at the coordinates of the phase-corresponding points in the first view, the horizontal and vertical phase values ​​(P) obtained by solving the fringe image captured by the camera are used. h , P v Then, using the relationship between phase value and coordinates again, calculate the coordinates of the corresponding point in the projected view: S3-3: Based on the phase coordinates of the projected view Calculate the polar line l in the second view proj : In the formula, F p-2 This is the basic matrix between the projector and the second camera.

[0011] S3-4: Based on the polar constraint relationship: Combine the two polar lines above l c , l proj The parametric equations can be used to solve for the intersection point p2 of the two polar lines in the second view. 0 .

[0012] The specific steps of step S4 are as follows: S4-1: At the intersection point p2 of the two polar lines 0 The horizontal direction defines the pixel neighborhood range: (p2) 0 -Rl, p2 0 +Rr), S4-2: Based on the neighborhood range, perform phase matching according to the phase matching error threshold to obtain the initial phase matching value: In the formula, ph1, ph2, pv1, and pv2 are the horizontal phase values ​​in the first view, the horizontal phase values ​​in the second view, the vertical phase values ​​in the first view, and the vertical phase values ​​in the second view, respectively, and ε is the error threshold.

[0013] S4-3: Perform phase interpolation on the points in the second view that satisfy the initial phase matching value of the first view to obtain the precise phase corresponding point coordinates p2; S4-4: Solving for the coordinates of corresponding points in the phase of the projected view and achieving 3D reconstruction: In the formula, To find the coordinates of the three-dimensional point, These represent the pixel coordinates of the phase-corresponding point p1 in the first view and the pixel coordinates of the phase-corresponding point p2 in the second view, respectively. These are the calibration parameter matrices for the first camera and the second camera, respectively.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. In S3 of this invention, a phase stereo matching acceleration method is proposed for binocular structured light rapid measurement technology, which realizes efficient matching of stereo views, reduces invalid calculations, and improves the matching speed by more than 60% compared with the traditional epipolar search phase matching method while maintaining the same amount of reconstructed data.

[0015] 2. In S1 of this invention, a highly efficient and robust monocular structured light system calibration method based on coding point guidance is proposed to address the calibration technology problem of monocular structured light systems. This method enables efficient and robust corresponding point lookup for monocular structured light systems and obtains more accurate calibration results with stronger generalization ability. In a 150mm measurement field of view, the measurement accuracy can reach 0.03mm.

[0016] In summary, this invention utilizes a projector and a second camera in a binocular system to construct a monocular system. It accelerates the search for corresponding phase points in the binocular view by calculating the intersection of the epipolar lines of the second camera in the monocular system and the second camera in the binocular system, using this intersection as initial matching values. Initial calibration values ​​are calculated using coded points, followed by projection calculations to find non-coded points. Finally, all marker points are used to calculate the precise calibration values. This avoids the calibration failures caused by missing individual points in traditional point matrix calibration boards or checkerboard patterns, improving the robustness and generalization ability of the monocular system calibration, and contributing to increased accuracy and more precise epipolar equations. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the overall technical process of the present invention.

[0018] Figure 2This is a flowchart of the single-target positioning process guided by the coding point of the present invention.

[0019] Figure 3 This is a schematic diagram of the calibration board configuration of the present invention.

[0020] Figure 4 This is a schematic diagram illustrating the principle of finding the center and phase coordinates of the marker point in this invention.

[0021] Figure 5 This is a schematic diagram of the bipolar line intersection point of the present invention.

[0022] Figure 6 This is a schematic diagram illustrating the principle of precise phase correspondence point finding in this invention. Detailed Implementation

[0023] The present invention will now be described in detail with reference to the accompanying drawings.

[0024] Reference Figure 1 A high-precision binocular structured light measurement method using bipolar linear acceleration includes the following steps: S1: The binocular structured light system consists of two cameras and a projector, wherein the projector and the second camera form a monocular structured light system; firstly, the binocular structured light system is calibrated using a traditional method, then the projector and the second camera are combined to form a monocular structured light system, and the monocular structured light system is calibrated based on the guidance of the coding calibration board; Step S1 involves monocular structured cursor calibration guided by an encoding calibration board. The specific steps are as follows: Figure 2 As shown, S1-1: A calibration plate with a black background and white dots is used, such as... Figure 3 As shown, the markers on the calibration board include coded points and non-coded points. The calibration board has at least four circular coded points for subsequent initial calibration values. S1-2: During calibration, the calibration board is placed in different poses within the effective depth of field of the camera and the projector. A set of vertical and horizontal phase-shifted fringes is projected for each pose, and the camera is used to acquire fringe images under multiple poses simultaneously. S1-3: For the acquired horizontal and vertical fringe images of the calibration board in each pose, the phase values ​​are calculated using the traditional multi-frequency heterodyne method; then, a set of phase shift images are superimposed in a weighted manner to form an image of the marker points to be detected. In the formula, Ic is the pixel intensity of the marker to be detected; n is the phase shift step number; Ii is the pixel intensity of the stripe pattern to be measured, i is the phase shift number; k is the weighting coefficient, the size of which is defined according to the brightness of the stripe image; Then, based on the superimposed image of the marker to be detected, the center of the marker is detected to obtain the coordinates (u, v) of the center of the marker. S1-4: Interpolate the phase values ​​at nearby integer pixel coordinates based on the center coordinates (u, v) of the marker point, such as... Figure 4 As shown, the phase value (P) corresponding to the center coordinates (u, v) is obtained. h , P v ), Figure 4 In the diagram, u represents the horizontal pixel coordinate; v represents the vertical pixel coordinate; P... h Indicates the horizontal phase value; P v Indicates the vertical phase value; S1-5: The phase values ​​(Ph, Pv) obtained in step S1-4 are the phase values ​​of the marker points in the image captured by the camera; based on the phase encoding relationship of the projected fringes, the coordinates of the corresponding point in the projector are calculated using the phase values ​​obtained from the second view. : In the formula, N is the fringe frequency. , These represent the horizontal and vertical pixel counts of the projector, respectively.

[0025] S1-6: Based on the coordinates of the center of the coordinate marker (u, v) and the coordinates of the corresponding point on the projector... The system calibration of the two cameras is carried out. The system calibration is divided into single-camera calibration and stereo calibration. First, the second camera and the projector are calibrated by using the coding correspondence of the coding points. The intrinsic parameters A, extrinsic parameters [R|T] and distortion parameters Δ of the second camera and the projector are calculated and nonlinear optimization is performed as the initial values ​​for the calibration of the second camera and the projector. S1-7: Based on the initial calibration values ​​in S1-6, recalculate the coordinates p of the non-coded object point W in the calibration board in the second camera or projector: Here, p is the actual point coordinate in the image of the second camera or projector, Δ is the distortion vector, A is the intrinsic parameter matrix, and [R|T] is the extrinsic parameter matrix; When all coded and non-coded points on the calibration board are known, the correspondence between the non-coded points on the second camera, the projector, and the calibration board is obtained respectively. S1-8: After obtaining the correspondence between the positions of all marker points in the second camera and projector and their positions on the calibration board in step S1-7, perform stereo calibration of the monocular system again using all coded and non-coded points. At the same time, calculate all parameters of the second camera and projector and use them as the final calibration result.

[0026] The table below shows the diameter deviation of a standard sphere with a known diameter of 20 mm obtained from seven different measurements within the field of view: Table 2 Measurement Accuracy method Error / μm average value 17.5 Maximum value 27.8 Standard deviation 9.1 The structured light calibration method proposed in this step enables efficient and robust corresponding point finding for monocular structured light systems, and yields more accurate calibration results with stronger generalization ability. In a 150mm measurement field of view, the measurement accuracy can reach 0.03mm. S2: During actual measurement, the projector projects two sets of horizontal and vertical stripes onto the object to be measured. The two cameras capture the stripes synchronously and use the traditional multi-frequency phase-shift heterodyne method to calculate the horizontal and vertical phases of the fringe patterns captured by the cameras respectively. The first camera captures the first view and the second camera captures the second view.

[0027] S3: Solve for the coordinates in the projector and the polar line l in the second view based on the phase-corresponding point p1 in the first view captured by the first camera. c Using the phase corresponding point p of the projected view in a monocular system proj Solve for the polar line l in the second camera proj And calculate the intersection point p2 of the two polar lines in the second view. 0 ; Step S3 calculates the intersection of the two polar lines in the second view, such as... Figure 5 As shown, Figure 5 In the diagram, P represents a 3D point; p1 represents a phase-corresponding point in the first view; p2 represents a phase-corresponding point in the second view; p20 represents the intersection of the polar lines in the second view; pProj represents a phase-corresponding point in the projected view; C1 represents the first camera; C2 represents the second camera; Proj represents the projector; l proj The polar line representing the phase correspondence point in the projected view in the second view; c The phase corresponding point in the first view is represented by the polar line in the second view.

[0028] The specific steps are as follows: S3-1: Calculate the polar line l in the second view based on the coordinates of the corresponding point p1 in the first view. c : In the formula, F 1-2 This is the fundamental matrix between the first camera and the second camera.

[0029] S3-2: Based on the phase information at the coordinates of corresponding points in the first view, using the horizontal and vertical phase values ​​(Ph, Pv) obtained from the camera-captured image, and again using the relationship between the phase values ​​and coordinates, calculate the coordinates of the corresponding points in the projected view: S3-3: Based on the phase coordinates of the projected view Calculate the polar line l in the second view proj : In the formula, F p-2 This is the basic matrix between the projector and the second camera.

[0030] S3-4: Based on the polar constraint relationship: Combine the two polar lines above l c , l proj The parametric equations can be used to solve for the intersection point p2 of the two polar lines in the second view. 0 .

[0031] In step S3, efficient matching of stereo views is achieved by using binocular structured light rapid measurement technology, reducing invalid calculations. While maintaining the same amount of reconstructed data, the matching speed is improved by more than 60% compared to the traditional epipolar search phase matching method.

[0032] The table below shows the measurement time taken to generate a 2 million point cloud of a certain component using a 500W resolution binocular camera: Table 1 Measurement Accuracy method Time consumed / s Traditional methods 5.83 This method 3.54 .

[0033] S4: Define a neighborhood for the intersection of the two polar lines, accurately find the phase values ​​in the vicinity, and perform three-dimensional reconstruction.

[0034] The specific steps are as follows: S4-1: As Figure 6 As shown, based on the intersection point p2 obtained in S3-4 0 Define its nearest neighbor region, specifically at the intersection point p2 of the two polar lines. 0 The horizontal direction defines the pixel neighborhood range: (p2) 0 -Rl, p2 0 +Rr), and subsequent phase matching is performed in this neighborhood.

[0035] S4-2: Based on the neighborhood range, perform phase matching according to the phase matching error threshold to obtain the initial phase matching value: In the formula, ph1, ph2, pv1, and pv2 are the horizontal phase values ​​in the first view, the horizontal phase values ​​in the second view, the vertical phase values ​​in the first view, and the vertical phase values ​​in the second view, respectively, and ε is the error threshold.

[0036] S4-3: Perform phase interpolation on the points in the second view that satisfy the initial phase matching value of the first view to obtain the precise phase corresponding point coordinates p2; S4-4: Solving for the coordinates of corresponding points in the phase of the projected view and achieving 3D reconstruction: In the formula, To find the coordinates of the three-dimensional point, These represent the pixel coordinates of the phase-corresponding point p1 in the first view and the pixel coordinates of the phase-corresponding point p2 in the second view, respectively. These are the calibration parameter matrices for the first camera and the second camera, respectively.

[0037] In summary, this invention addresses the calibration problem of monocular structured light systems by proposing an efficient and robust calibration method based on coded points. First, the system is configured with a coded calibration board featuring black backgrounds and white dots. Then, horizontal and vertical stripes are projected onto the coded calibration board to encode the centers of the marker points. Next, a marker point detection image is rapidly synthesized using a phase-shifting diagram, and marker point center detection and encoding are performed. Phase calculation and sub-pixel interpolation are used to find the pixel mapping relationship between the camera and the projector. Then, preliminary calibration is performed using the coded points to obtain the initial calibration value of the monocular system. Finally, the initial calibration value is used to determine the correspondence between non-coded points on the calibration board and the camera and projector, and a second calibration is performed to obtain the calibration value of the monocular system. This achieves efficient and robust correspondence point finding for monocular structured light systems and yields more accurate calibration results with stronger generalization capabilities. In a 150mm measurement field of view, the measurement accuracy can reach 0.03mm.

[0038] Secondly, this invention proposes a phase stereo matching acceleration method for the field of binocular structured light rapid measurement technology. First, the coordinates in the projector view are solved using the phase information of the first camera. Then, the projection of the projected view onto the second camera view is obtained. Then, the intersection point of the epipolar line mapped from the same point in the monocular system to the second camera and the epipolar line mapped in the binocular system is used to obtain the initial matching value of the phase map of the first camera and the phase map of the second camera. Finally, the corresponding points between the phase maps of the first camera and the second camera are obtained through precise matching; This method achieves efficient matching of stereoscopic views, reduces unnecessary computation, and improves matching speed by more than double compared to traditional epipolar search phase matching methods while maintaining the same amount of reconstructed data.

Claims

1. A high-precision binocular structured light measurement method employing bipolar linear acceleration, characterized in that, Includes the following steps: S1: The binocular structured light system consists of two cameras and a projector, wherein the projector and the second camera form a monocular structured light system; firstly, the binocular structured light system is calibrated using traditional methods, then the projector and the second camera are combined to form a monocular structured light system, and the monocular structured light system is calibrated based on the guidance of the coding calibration board; S2: During actual measurement, the projector projects two sets of horizontal and vertical stripes onto the object to be measured, and the two cameras capture them simultaneously. The first camera captures the first view, and the second camera captures the second view. The horizontal and vertical phases of the fringe patterns captured by the cameras are calculated using the traditional multi-frequency phase-shift heterodyne method. S3: Solve for the coordinates in the projector and the polar line l in the second view based on the phase-corresponding point p1 in the first view captured by the first camera. c Using the phase corresponding point p of the projection view in a monocular structured light system proj Solve for the epipolar line l in the second view captured by the second camera. proj And calculate the polar line l in the second view. proj With polar line l c intersection point p2 0 ; S4: At the intersection point p2 of the two polar lines 0 Define a neighborhood, accurately search for phase values, and perform 3D reconstruction to achieve matching of corresponding phase points.

2. The high-precision binocular structured light measurement method using bipolar linear acceleration according to claim 1, characterized in that, In the binocular structured light system, the two cameras and the projector are arranged horizontally, with the optical axes of the two cameras intersecting the focal point of the projector and falling on the surface of the object to be measured.

3. The high-precision binocular structured light measurement method using bipolar linear acceleration according to claim 1, characterized in that, Step S1, which involves calibrating the monocular structured light system based on the guidance of the encoding calibration board, specifically includes the following steps: S1-1: A calibration board with a black background and white dots is used. The markings on the calibration board include coded points and non-coded points. Each coded point consists of a non-coded point and several arc-shaped marks surrounding the non-coded point, which are used for subsequent initial calibration values. Each arc-shaped mark is located on the same circumference. S1-2: During calibration, the calibration board is placed in different poses within the effective depth of field of the camera and the projector. A set of vertical and horizontal phase-shifted fringes is projected for each pose. Simultaneously, the second camera is used to acquire fringe images under multiple poses. S1-3: For the acquired horizontal and vertical fringe images of the calibration board in each pose, the phase values ​​are calculated using the traditional multi-frequency heterodyne method; then, a set of phase shift images are superimposed in a weighted manner to form an image of the marker points to be detected. In the formula, Ic is the pixel intensity of the marker to be detected; n is the phase shift step number; Ii is the pixel intensity of the stripe pattern to be measured, i is the phase shift number; k is the weighting coefficient, the size of which is defined according to the brightness of the stripe image; Then, based on the superimposed image of the marker to be detected, the center of the marker is detected to obtain the coordinates (u, v) of the center of the marker. S1-4: Interpolate the phase values ​​at nearby integer pixel coordinates based on the center coordinates (u, v) of the marker point to obtain the phase value (P) corresponding to the center coordinates (u, v). h , P v This refers to the phase value of the marker point in the image captured by the camera; S1-5: Based on the phase encoding relationship of the projected fringes, and using the phase value calculated from the second view, determine the coordinates of the corresponding point in the projector for that phase value. : In the formula, N is the fringe frequency. , These represent the horizontal and vertical pixel counts of the projector, respectively. S1-6: Based on the coordinates of the center of the coordinate marker (u, v) and the coordinates of the corresponding point on the projector... The system calibration of the two cameras is carried out. The system calibration is divided into single-camera calibration and stereo calibration. First, the second camera and the projector are calibrated by using the coding correspondence of the coding points. The intrinsic parameters A, extrinsic parameters [R|T] and distortion parameters Δ of the second camera and the projector are calculated and nonlinear optimization is performed as the initial values ​​for the calibration of the second camera and the projector. S1-7: Based on the initial calibration values ​​in S1-6, recalculate the coordinates p of the non-coded object point W in the calibration board in the second camera or projector: Where p is the actual point coordinate in the image of the second camera or projector, Δ is the distortion vector, A is the intrinsic parameter matrix, and [R|T] is the extrinsic parameter matrix; When all coded and non-coded points on the calibration board are known, the correspondence between the non-coded points on the second camera, the projector, and the calibration board is obtained respectively. S1-8: Based on the correspondence between the positions of all marker points in the second camera and projector and their positions on the calibration board obtained in step S1-7, perform stereo calibration of the monocular system again using all coded and non-coded points. At the same time, calculate all parameters of the second camera and projector and use them as the final calibration result.

4. The high-precision binocular structured light measurement method using bipolar linear acceleration according to claim 1, characterized in that, Step S3, which calculates the intersection of the two polar lines in the second view, involves the following steps: S3-1: Calculate the polar line l in the second view based on the coordinates of the phase corresponding point p1 in the first view. c : In the formula, F 1-2 This is the fundamental matrix between the first camera and the second camera; S3-2: Based on the phase information at the coordinates of the phase-corresponding point p1 in the first view, the horizontal and vertical phase values ​​(P1, P2, P3, P4, P5, P6, P7, P8, P9, P1, P1, P1, P2, P1, P2, P2, P3, P4, P5, P6, P7, P8, P9, P1 ... h , P v Then, using the relationship between phase value and coordinates again, calculate the coordinates of the corresponding point in the projected view: S3-3: Based on the phase coordinates of the projected view Calculate the polar line l in the second view proj : In the formula, F p-2 This forms the basic matrix between the projector and the second camera. S3-4: Based on the polar constraint relationship: Combine the two polar lines above l c , l proj The parametric equations can be used to solve for the intersection point p2 of the two polar lines in the second view. 0 .

5. The high-precision binocular structured light measurement method using bipolar linear acceleration according to claim 1, characterized in that, The specific steps of step S4 are as follows: S4-1: At the intersection point p2 of the two polar lines 0 The horizontal direction defines the pixel neighborhood range: (p2) 0 -Rl, p2 0 +Rr), S4-2: Based on the neighborhood range, perform phase matching according to the phase matching error threshold to obtain the initial phase matching value: In the formula, ph1, ph2, pv1, and pv2 are the horizontal phase values ​​in the first view, the horizontal phase values ​​in the second view, the vertical phase values ​​in the first view, and the vertical phase values ​​in the second view, respectively, and ε is the error threshold. S4-3: Perform phase interpolation on the second view to obtain the precise coordinates p2 of the phase-matching point that satisfies the initial phase matching value of the first view; S4-4: Solving for the coordinates of corresponding points in the phase of the projected view and achieving 3D reconstruction: In the formula, To find the coordinates of the three-dimensional point, These represent the pixel coordinates of the phase-corresponding point p1 in the first view and the pixel coordinates of the phase-corresponding point p2 in the second view, respectively. These are the calibration parameter matrices for the first camera and the second camera, respectively.

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