A mobile projection type three-dimensional measurement method and device

Abstract

The application relates to the field of mobile projection type three-dimensional measurement, in particular to a mobile projection type three-dimensional measurement method and device, the mobile projection type three-dimensional measurement method comprises the following steps: obtaining a multi-line structured light strip image of a to-be-measured object based on a DLP light machine; obtaining a pixel coordinate of the to-be-measured object based on a gray gravity center method by utilizing the multi-line structured light strip image; obtaining a three-dimensional coordinate of the to-be-measured object based on a pre-calibrated multi-light plane by utilizing the pixel coordinate of the to-be-measured object; and taking the three-dimensional coordinate of the to-be-measured object as a three-dimensional measurement result of the to-be-measured object, and calibrating a multi-light plane for the to-be-measured object after obtaining a single light plane by utilizing the DLP light machine, so that the measurement efficiency is higher, the structure is simple, and the system cost is lower on the basis of ensuring a certain precision.

Description

Technical Field

[0001] This invention relates to the field of mobile projection-based three-dimensional measurement, and specifically to a mobile projection-based three-dimensional measurement method and apparatus. Background Technology

[0002] Currently, several methods exist for 3D measurement of industrial components, but few offer high-precision, low-cost, and rapid measurement capabilities. Contact measurement methods, such as coordinate measuring machines (CMMs), can accurately measure the dimensions and shape of complex workpieces; however, the measurement process relies on point-by-point scanning with a probe, which is slow, inefficient, and may damage the object's surface. Furthermore, these devices are bulky and have stringent environmental requirements. In non-contact measurement, optical measurement methods are a key research focus, categorized into active and passive methods. Structured light measurement is the most important and commonly used method in active non-contact measurement, offering advantages such as numerous feature points, high measurement accuracy, and strong anti-interference capabilities. It projects characteristic structured light onto the object's surface, forming a light field. Combining this with triangulation principles, the light field information is converted into depth information, thus obtaining the 3D structure of the object's surface. Structured light measurement can be classified into three types based on the light source: spot-type, strip-type, and surface-type. Spot-type structured light measurement projects a single point onto the object's surface to obtain depth information; to obtain information about the entire object's surface, point-by-point scanning is required. Linear structured light uses a line light source, reducing the scanning dimension to one dimension compared to spot light. The accuracy of conventional linear structured light is on par with spot light, while line structured light, limited by the laser, still requires a high-precision displacement stage to complete the three-dimensional measurement of the object under test, resulting in disadvantages such as slow measurement speed, large size, and high cost. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a mobile projection-based three-dimensional measurement method and device, which enables rapid measurement of three-dimensional objects through an innovative multi-light plane calibration method.

[0004] To achieve the above objectives, the present invention provides a mobile projection-based three-dimensional measurement method, comprising:

[0005] S1. Acquire multi-line structured light stripe images of the object under test based on DLP optomechanics;

[0006] S2. Obtain the pixel coordinates of the object under test using the multi-line structured light stripe image based on the gray-scale centroid method;

[0007] S3. Obtain the three-dimensional coordinates of the object under test based on the pixel coordinates of the object under test using a pre-calibrated multi-light plane;

[0008] S4. Use the three-dimensional coordinates of the object to be measured as the three-dimensional measurement result of the object to be measured.

[0009] Preferably, the acquisition of the multi-line structured light stripe image of the object under test based on DLP optomechanics includes:

[0010] The first multi-line structured light stripe image of the object under test is obtained by projecting multi-line structured light stripes onto the surface of the object under test using a DLP optical engine.

[0011] After adjusting the number of pixel columns of grayscale 255 corresponding to the DLP optical engine and the object under test, the second multi-line structured light stripe image of the object under test is obtained;

[0012] The first multi-line structured light stripe image and the second multi-line structured light stripe image are used as the multi-line structured light stripe images of the object under test.

[0013] Preferably, obtaining the pixel coordinates of the object under test using the multi-line structured light bar image based on the gray-level centroid method includes:

[0014] The center line of the multi-line structured light stripe image modulated by the surface of the object under test is obtained using the gray-scale centroid method based on the multi-line structured light stripe image.

[0015] The pixel coordinates of the object under test are obtained using the center line of the light stripe in the multi-line structured light stripe image.

[0016] Preferably, the pre-calibration of the multi-plane optical system includes:

[0017] S3-1, Using a DLP optical engine to project equally spaced multi-line structured light stripes;

[0018] S3-2. Establish the initial relationship between the multi-light plane by using the pixel positions of each stripe in the equally spaced multi-line structured light stripe in the projected image and the light plane formed by the projection of each stripe.

[0019] S3-3. Use a portion of the projected multi-light plane as the base multi-light plane;

[0020] S3-4. Perform single-light plane calibration processing using the aforementioned basic multi-light plane;

[0021] S3-5. Substitute the parameters of the single-light plane into the initial relationship of the multi-light plane, calculate the initial relationship of the multi-light plane, and complete the initial calibration of the multi-light plane.

[0022] S3-6. Calculate the optical plane optimization formula using the diameter data of the standard sphere measured by the multi-plane measurement that has been initially calibrated;

[0023] S3-7. Using the aforementioned light plane optimization formula and the initial relationship of the multi-light plane, the final multi-light plane relationship is obtained, and the calibration process of the multi-light plane is completed.

[0024] Furthermore, the single-light plane calibration includes:

[0025] S3-5-1. Perform basic calibration on the dual telecentric lens to obtain the first transformation formula;

[0026] S3-5-2. When the checkerboard pattern of the calibrated target surface is clearly imaged, acquire the target image;

[0027] S3-5-3. Using a DLP optical engine to project a single-line structured light onto the calibration target surface to obtain the intersection line between the light plane and the target plane;

[0028] S3-5-4. Acquire the light stripe imaging of the single-line structured light and the checkerboard imaging corresponding to the light stripe imaging;

[0029] S3-5-5. After adjusting the plane position of the calibration target surface and moving it up by dmm, repeat S3-5-2 to S3-5-3 to obtain n sets of initial single-light plane images;

[0030] S3-5-6. Obtain the rotation matrix and translation vector using the homography matrix;

[0031] S3-5-7. Using the world coordinates of the checkerboard corner points and the pixel coordinates of the checkerboard corner points corresponding to the initial image of the single light plane, the second homography matrix is ​​obtained based on the DLT algorithm.

[0032] S3-5-8. Use the second homography matrix to obtain the second transformation relation;

[0033] S3-5-9. The target plane is obtained by fitting the corner points of the chessboard using the least squares method.

[0034] S3-5-10. Using the pixel coordinates of the single-line structured light, the camera coordinates of the light stripe centerline are obtained based on the camera intrinsic parameters and the single-line structured light target plane equation corresponding to the single-line structured light.

[0035] S3-5-11. The single-light plane is obtained by fitting the camera coordinates of the light stripe centerline.

[0036] S3-5-12. Obtain the plane equation based on the single-light plane to complete the single-light plane calibration.

[0037] Furthermore, the calculation formula for the first transformation relationship obtained by performing basic calibration processing on the dual telecentric lenses is as follows:

[0038]

[0039] Among them, (X) w1 Y w1 (u1, v1) are world coordinates, (u1, v1) are pixel coordinates, R1 is the rotation matrix, T1 is the translation matrix, and H1 is the first homography matrix.

[0040] Furthermore, the calculation formula for establishing the initial relationship between the pixel positions of each stripe in the equally spaced multi-line structured light stripe in the projected image and the light plane formed by the projection of each stripe is as follows:

[0041] A = f1(u) = a1u n +a2u n-1 +…+a n+1

[0042] B = f2(u) = b1u n +b2u n-1 +…+b n+1

[0043] C = f3(u) = c1u n +c2u n-1 +…+c n+1

[0044] D = f4(u) = d1u n +d2u n-1 +…+d n+1

[0045] Where A, B, C, and D represent the four parameters in the equation Ax + By + Cz + D = 0 for the light plane, and a n b n c n d n denoted by , where u is the number of pixel columns in the projected image where the projected light stripe is located, and n is the degree of the polynomial.

[0046] Furthermore, the formula for calculating the optical plane optimization formula using the diameter data of the standard sphere measured by the multi-plane measurement that has been initially calibrated is as follows:

[0047] F = ||RR i (a j ,b j ,c j ,d j )|| 2 (j = 1, 2, ... 6)

[0048] Where R is the standard radius of the standard sphere, R i Let a be the radius of the sphere obtained by calculating the coefficients after polynomial fitting. j b j c j d j are the coefficients of the polynomial.

[0049] Preferably, obtaining the three-dimensional coordinates of the object under test based on the pixel coordinates of the object under test using a pre-calibrated multi-light plane includes:

[0050] By substituting the pixel coordinates of the object under test into the corresponding pre-calibrated light plane calibration formula, the three-dimensional coordinates of the object under test can be obtained.

[0051] Based on the same inventive concept, the present invention also provides a mobile projection-type three-dimensional measurement device, including a DLP optical engine, a camera with dual telecentric lenses, a DLP mounting plate, a camera mounting plate, an adapter plate, a camera base plate, a base plate, and a gantry.

[0052] The DLP optical engine is fixed to the base plate via a DLP mounting plate. The camera and dual telecentric lenses are fixed to the base plate via a camera mounting plate, an adapter plate, and a camera base plate. The base plate is then fixed to the gantry.

[0053] Compared with the closest existing technology, the present invention has the following advantages:

[0054] The moving projection method projects a large number of light strips. In order to achieve full-resolution measurement, the light strips are shifted. In order to effectively improve measurement efficiency, multi-plane calibration of the object under test based on DLP optomechanic has high measurement efficiency, and while ensuring a certain level of accuracy, the structure is simple and the system cost is low. Attached Figure Description

[0055] Figure 1 This is a flowchart of a mobile projection-based three-dimensional measurement method provided by the present invention;

[0056] Figure 2 This is a schematic diagram of the single-light plane calibration process of a mobile projection-type three-dimensional measurement method provided by the present invention;

[0057] Figure 3 This is a schematic diagram of a mobile projection-type three-dimensional measuring device provided by the present invention;

[0058] Figure 4 This is a schematic diagram of the light strip translation of a mobile projection-type three-dimensional measuring device provided by the present invention;

[0059] Figure label:

[0060] 1. DLP optical engine; 2. Camera with dual telecentric lenses; 3. DLP mounting plate; 4. Camera mounting plate; 5. Adapter plate; 6. Camera base plate; 7. Base plate; 8. Gantry; 9. Standard ball; 10. Support component; 11. Component under test. Detailed Implementation

[0061] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0062] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] Example 1:

[0064] This invention provides a mobile projection-based three-dimensional measurement method, such as... Figure 1 As shown, it includes:

[0065] S1. Acquire multi-line structured light stripe images of the object under test based on DLP optomechanics;

[0066] S2. Obtain the pixel coordinates of the object under test using the multi-line structured light stripe image based on the gray-scale centroid method;

[0067] S3. Obtain the three-dimensional coordinates of the object under test based on the pixel coordinates of the object under test using the pre-calibrated multi-light plane;

[0068] S4. Use the three-dimensional coordinates of the object to be measured as the three-dimensional measurement result of the object to be measured.

[0069] S1 specifically includes:

[0070] S1-1. Using a DLP optical engine, project a multi-line structured light stripe onto the surface of the object under test to obtain the first multi-line structured light stripe image of the object under test.

[0071] S1-2. After adjusting the number of pixel columns of grayscale 255 corresponding to the DLP optical engine and the object under test, the second multi-line structured light stripe image of the object under test is obtained.

[0072] S1-3. Use the first multi-line structured light stripe image and the second multi-line structured light stripe image as the multi-line structured light stripe image of the object to be tested.

[0073] S2 specifically includes:

[0074] S2-1. Using the multi-line structured light stripe image, the center line of the light stripe image modulated by the surface of the object under test is obtained based on the gray-scale centroid method.

[0075] S2-2. Obtain the pixel coordinates of the object under test using the center line of the light stripe in the multi-line structured light stripe image.

[0076] S3 specifically includes:

[0077] S3-1, Using a DLP optical engine to project equally spaced multi-line structured light stripes;

[0078] S3-2. Establish the initial relationship between the multi-light plane by using the pixel positions of each stripe in the equally spaced multi-line structured light stripe in the projected image and the light plane formed by the projection of each stripe.

[0079] S3-3. Use a portion of the projected multi-light plane as the base multi-light plane;

[0080] S3-4. Perform single-light plane calibration processing using the aforementioned basic multi-light plane;

[0081] S3-5. Substitute the parameters of the single-light plane into the initial relationship of the multi-light plane, calculate the initial relationship of the multi-light plane, and complete the initial calibration of the multi-light plane.

[0082] S3-6. Calculate the optical plane optimization formula using the diameter data of the standard sphere measured by the multi-plane measurement that has been initially calibrated;

[0083] S3-7. Using the aforementioned light plane optimization formula and the initial relationship of the multi-light plane, the final multi-light plane relationship is obtained, and the calibration process of the multi-light plane is completed.

[0084] S3-8. Obtain the multi-line structured light stripe image modulated on the surface of the object to be tested, extract the pixel coordinates of the center line of each light stripe, and obtain the pixel coordinates of the object to be tested.

[0085] S3-9. Substitute the pixel coordinates of the surface of the object under test into the corresponding pre-calibrated light plane relationship to obtain the three-dimensional coordinates of the object under test.

[0086] In this embodiment, a mobile projection-based three-dimensional measurement method includes a single-light plane calibration process, as follows: Figure 2 As shown.

[0087] In this embodiment, due to factors such as the accuracy of the displacement stage, the calibration results deviate from the theoretical values ​​to a certain extent. This invention utilizes the calibrated multi-plane measurement of the standard sphere diameter and uses the Levenberg-Marquardt algorithm to nonlinearly optimize the relationship.

[0088] The formula for calculating S3-3 is as follows:

[0089] A = f1(u) = a1u n +a2u n-1 +…+a n+1

[0090] B = f2(u) = b1u n +b2u n-1 +…+b n+1

[0091] C = f3(u) = c1u n +c2un-1 +…+c n+1

[0092] D = f4(u) = d1u n +d2u n-1 +…+d n+1

[0093] Where A, B, C, and D represent the four parameters in the equation Ax + By + Cz + D = 0 for the light plane, and a n b n c n d n denoted by , where u is the number of pixel columns in the projected image where the projected light stripe is located, and n is the degree of the polynomial.

[0094] S3-5 specifically includes:

[0095] S3-5-1. Perform basic calibration on the dual telecentric lens to obtain the first transformation formula;

[0096] S3-5-2. When the checkerboard pattern of the calibrated target surface is clearly imaged, acquire the target image;

[0097] S3-5-3. Using a DLP optical engine to project a single-line structured light onto the calibration target surface to obtain the intersection line between the light plane and the target plane;

[0098] S3-5-4. Acquire the light stripe imaging of the single-line structured light and the checkerboard imaging corresponding to the light stripe imaging;

[0099] S3-5-5. After adjusting the plane position of the calibration target surface and moving it up by dmm, repeat S3-5-2 to S3-5-3 to obtain n sets of initial single-light plane images;

[0100] S3-5-6. Obtain the rotation matrix and translation vector using the homography matrix;

[0101] S3-5-7. Using the world coordinates of the checkerboard corner points and the pixel coordinates of the checkerboard corner points corresponding to the initial image of the single light plane, the second homography matrix is ​​obtained based on the DLT algorithm.

[0102] S3-5-8. Use the second homography matrix to obtain the second transformation relation;

[0103] S3-5-9. The target plane is obtained by fitting the corner points of the chessboard using the least squares method.

[0104] S3-5-10. Using the pixel coordinates of the single-line structured light, the camera coordinates of the light stripe centerline are obtained based on the camera intrinsic parameters and the single-line structured light target plane equation corresponding to the single-line structured light.

[0105] S3-5-11. The single-light plane is obtained by fitting the camera coordinates of the light stripe centerline.

[0106] S3-5-12. Obtain the plane equation based on the single-light plane to complete the single-light plane calibration.

[0107] The formula for calculating S3-5-1 is as follows:

[0108]

[0109] Among them, (X) w1 Y w1 (u1, v1) are world coordinates, (u1, v1) are pixel coordinates, R1 is the rotation matrix, T1 is the translation matrix, and H1 is the first homography matrix.

[0110] In this embodiment, a mobile projection-type three-dimensional measurement method is described. After adjusting the plane position of the calibration target surface and moving it upward by 0.25mm, steps S3-5-2 to S3-5-3 are repeated to obtain 25 sets of initial single-light plane images.

[0111] In this embodiment, a moving projection-based three-dimensional measurement method, the relationship of the second homography matrix in S3-5-7 is as follows:

[0112]

[0113] Among them, (X) w2 Y w2 (u2, v2) are world coordinates, (u2, v2) are pixel coordinates, R2 is the rotation matrix, T2 is the translation matrix, and H2 is the second homography matrix.

[0114] In this embodiment, a mobile projection-based three-dimensional measurement method is described, and the calculation formula for the second transformation relationship in S3-5-8 is as follows:

[0115]

[0116] Among them, (x c y c , z c To calibrate the coordinates of each corner point of the checkerboard pattern on the target surface in the camera coordinate system, (X) w2 Y w2 Z w2 The world coordinates of each corner point of the chessboard are given by R2, where R2 is the rotation matrix and T2 is the translation matrix.

[0117] In this embodiment, a moving projection-based three-dimensional measurement method is described, and the calculation formula for the target plane equation in S3-5-10 is as follows:

[0118] Aixc+Biyc+Cizc+Di=0

[0119] Among them, A i B i C i D i These are the parameters of the target plane equation.

[0120] In this embodiment, a mobile projection-based three-dimensional measurement method uses the following formula to calculate the camera coordinates of the center line of a single-line structured light beam, based on the pixel coordinates of the single-line structured light beam:

[0121]

[0122] Among them, (x Lc y Lc ) represents the camera coordinates of each point on the center line of the single-line structured light stripe, (u L v L The pixel coordinates of each point on the center line of a single-line structured light stripe.

[0123] In this embodiment, a moving projection-based three-dimensional measurement method, the single-light plane calibration formula of S3-5-12 is as follows:

[0124] Ax Lc +By Lc +Cz Lc +D Lc =0

[0125] Among them, (x Lc y Lc , z Lc ) represents the complete camera coordinates of the light stripe centerline, and A, B, C, and D are the single-light plane parameters, respectively.

[0126] The formula for calculating S3-7 is as follows:

[0127] F = ||RR i (a j ,b j ,c j ,d j )|| 2 (j = 1, 2, ... 6)

[0128] Where R is the standard radius of the standard sphere, R i Let a be the radius of the sphere obtained by calculating the coefficients after polynomial fitting. j b j c j d j are the coefficients of the polynomial.

[0129] In this embodiment, a mobile projection-based three-dimensional measurement method is provided, wherein the R... i The result is obtained by substituting R into the initial fringe light plane relation.

[0130] Example 2:

[0131] This invention provides a mobile projection-type three-dimensional measurement device, such as... Figure 3 As shown, it includes a DLP optical engine 1, a camera 2 with dual telecentric lenses, a DLP mounting plate 3, a camera mounting plate 4, an adapter plate 5, a camera base plate 6, a base plate 7, and a gantry 8.

[0132] The DLP optical engine 1 is fixed to the base plate 7 via the DLP mounting plate 3. The camera 2 with dual telecentric lenses is fixed to the base plate 7 via the camera mounting plate 4, the adapter plate 5, and the camera base plate 6. The base plate 7 is fixed to the gantry 8. The standard ball 9 is set on the support member 10. The part to be measured 11 is set below the camera 2 with dual telecentric lenses.

[0133] The working process of this embodiment is as follows:

[0134] Step 1: Place the object to be tested 11 on the stage;

[0135] Step 2, as follows Figure 4 As shown, the DLP optical engine 1 projects multi-line structured light stripes onto the surface of the object being measured. During the measurement process, the measurement is continuously moved by shifting the number of pixels with a gray level of 255 in the projected image on the DLP optical engine, thereby increasing the sampling rate. The camera takes pictures and records them as p.

[0136] Step 3: Extract the center line of the light stripe in p using the gray-scale centroid method to obtain its pixel coordinates. Based on the calibration model of the multi-light plane, obtain its three-dimensional coordinates in the camera coordinate system, thereby completing the size measurement.

[0137] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0138] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0139] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0140] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A mobile projection-based three-dimensional measurement method, characterized in that, include: S1. Acquire multi-line structured light stripe images of the object under test based on DLP optomechanics; S2. Obtain the pixel coordinates of the object under test using the multi-line structured light stripe image based on the gray-scale centroid method; S3. Obtain the three-dimensional coordinates of the object under test based on the pixel coordinates of the object under test using a pre-calibrated multi-light plane; The pre-calibration of the multi-plane optical system includes: S3-1, Using a DLP optical engine to project equally spaced multi-line structured light stripes; S3-2. Using the pixel positions of each stripe in the equally spaced multi-line structured light stripe in the projected image and the light plane formed by the projection of each stripe, an initial relationship between the multi-light plane is established. The calculation formula is as follows: Where A, B, C, and D represent the four parameters in the equation Ax + By + Cz + D = 0 for the light plane, and a n b n c n d n denoted by , where u is the number of pixel columns in the projected image where the projected light stripe is located, and n is the degree of the polynomial. S3-3. Use a portion of the projected multi-light plane as the base multi-light plane; S3-4. Perform single-light plane calibration processing using the aforementioned basic multi-light plane; S3-5. Substitute the parameters of the single-light plane into the initial relationship of the multi-light plane, calculate the initial relationship of the multi-light plane, and complete the initial calibration of the multi-light plane. S3-6. Calculate the optical plane optimization formula using the diameter data of the standard sphere measured by the multi-plane measurement that has been initially calibrated; S3-7. Using the aforementioned light plane optimization formula and the initial relationship of the multi-light plane, the final multi-light plane relationship is obtained, and the calibration process of the multi-light plane is completed. S4. Use the three-dimensional coordinates of the object to be measured as the three-dimensional measurement result of the object to be measured.

2. The mobile projection-based three-dimensional measurement method as described in claim 1, characterized in that, The acquisition of the multi-line structured light stripe image of the object under test based on DLP optomechanics includes: The first multi-line structured light stripe image of the object under test is obtained by projecting multi-line structured light stripes onto the surface of the object under test using a DLP optical engine. After adjusting the number of columns of pixels with a grayscale of 255 in the DLP optical engine projection image, the second multi-line structured light stripe image of the object under test is obtained; The first multi-line structured light stripe image and the second multi-line structured light stripe image are used as the multi-line structured light stripe images of the object under test.

3. The mobile projection-based three-dimensional measurement method as described in claim 1, characterized in that, The pixel coordinates of the object under test obtained using the multi-line structured light stripe image based on the gray-level centroid method include: The center line of the light stripe in the multi-line structured light stripe image modulated by the object surface is obtained using the gray-scale centroid method; The pixel coordinates of the object under test are obtained using the center line of the light stripe in the multi-line structured light stripe image.

4. The mobile projection-based three-dimensional measurement method as described in claim 1, characterized in that, The single-light plane calibration includes: S3-5-1. Perform basic calibration on the dual telecentric lens to obtain the first transformation formula; S3-5-2. When the checkerboard pattern of the calibrated target surface is clearly imaged, acquire the target image; S3-5-3. Using a DLP optical engine to project a single-line structured light onto the calibration target surface to obtain the intersection line between the light plane and the target plane; S3-5-4. Acquire the light stripe imaging of the single-line structured light and the checkerboard imaging corresponding to the light stripe imaging; S3-5-5. After adjusting the plane position of the calibration target surface and moving it up by dmm, repeat S3-5-2 to S3-5-3 to obtain n sets of initial single-light plane images; S3-5-6. Obtain the rotation matrix and translation vector using the homography matrix; S3-5-7. Using the world coordinates of the checkerboard corner points and the pixel coordinates of the checkerboard corner points corresponding to the initial image of the single light plane, the second homography matrix is ​​obtained based on the DLT algorithm. S3-5-8. Use the second homography matrix to obtain the second transformation relation; S3-5-9. The target plane is obtained by fitting the corner points of the chessboard using the least squares method. S3-5-10. Using the pixel coordinates of the single-line structured light, the camera coordinates of the light stripe centerline are obtained based on the camera intrinsic parameters and the single-line structured light target plane equation corresponding to the single-line structured light. S3-5-11. The single-light plane is obtained by fitting the camera coordinates of the light stripe centerline. S3-5-12. Obtain the plane equation based on the single-light plane to complete the single-light plane calibration.

5. The mobile projection-based three-dimensional measurement method as described in claim 4, characterized in that, The calculation formula for the first transformation relationship obtained by performing basic calibration on the dual telecentric lenses is as follows: Among them, (X) w1 Y w1 (u1, v1) are world coordinates, (u1, v1) are pixel coordinates, R1 is the rotation matrix, T1 is the translation matrix, and H1 is the first homography matrix.

6. The mobile projection-based three-dimensional measurement method as described in claim 1, characterized in that, The formula for calculating the optical plane optimization formula using the diameter data of the standard sphere measured by the multi-plane measurement that has been initially calibrated is as follows: Where R is the standard radius of the standard sphere, R i Let a be the radius of the sphere obtained by calculating the coefficients after polynomial fitting. j b j c j d j are the coefficients of the polynomial.

7. The mobile projection-based three-dimensional measurement method as described in claim 1, characterized in that, Obtaining the three-dimensional coordinates of the object under test based on a pre-calibrated multi-light plane using the pixel coordinates of the object under test includes: By substituting the pixel coordinates of the object under test into the pre-calibrated multi-light plane calibration formula corresponding to the object under test, the three-dimensional coordinates of the object under test can be obtained.

8. A mobile projection-type three-dimensional measuring device, employing the method described in any one of claims 1-7, characterized in that, Includes DLP optical engine (1), camera with double telecentric lens (2), DLP mounting plate (3), camera mounting plate (4), adapter plate (5), camera base plate (6), base plate (7) and gantry (8); The DLP optical engine (1) is fixed on the base plate (7) by the DLP mounting plate (3). The camera with dual telecentric lenses is fixed on the base plate (7) by the camera mounting plate (4), the adapter plate (5) and the camera base plate (6). The base plate (7) is then fixed on the gantry (8).

Images