Binary iterative sub-pixel matching method and system for phase structured light three-dimensional measurement

Abstract

The application belongs to the technical field of optical three-dimensional measurement, and discloses a two-division iteration sub-pixel matching method and system for phase structured light three-dimensional measurement, which comprises the following steps: obtaining a phase map; performing legality marking and pixel-level initial matching on the phase map; determining a sub-pixel search area based on the pixel-level initial matching; and performing sub-pixel matching point search based on the sub-pixel search area by using a two-division iteration method to obtain a sub-pixel matching point. The application can improve the precision of binocular matching in phase structured light three-dimensional measurement, thereby improving the precision of three-dimensional reconstruction.

Description

Technical Field

[0001] This invention relates to the field of optical three-dimensional measurement technology, specifically to a binary iterative sub-pixel matching method and system for phase structured light three-dimensional measurement. Background Technology

[0002] Phase-based 3D measurement has extremely wide applications in the industrial field. In industrial manufacturing, phase-assisted 3D topography measurement can be applied to dimensional inspection and surface quality assessment during the manufacturing process. In automobile manufacturing, this technology can be used to measure the topography of the car body surface to detect indicators such as flatness and curvature. The importance of these applications lies in their ability to improve manufacturing accuracy and product quality while reducing scrap rates and production costs. In mechanical design, phase-assisted 3D topography measurement can be used for bearing surface topography measurement and part fit inspection. By measuring the surface topography of parts, the machining quality and assembly accuracy of the parts can be evaluated. The importance of these applications lies in their ability to improve the performance and stability of mechanical equipment while reducing failure rates and maintenance costs. In summary, the application and importance of phase-based 3D measurement in the industrial field are mainly reflected in improving manufacturing accuracy and product quality, reducing scrap rates and production costs, improving the performance and stability of mechanical equipment, and reducing failure rates and maintenance costs.

[0003] Binocular phase matching is a crucial step in the phase-shifting 3D measurement algorithm. It primarily involves matching the binocular phase maps pixel-by-pixel based on phase values, and then using the matched points for 3D reconstruction. Therefore, the accuracy of binocular matching directly impacts the accuracy of 3D reconstruction. To obtain highly accurate 3D point cloud data, it is essential to ensure high precision in the binocular phase map phase matching.

[0004] Existing phase-based binocular matching primarily uses mean interpolation or linear interpolation methods for sub-pixel matching. These methods directly use interpolation to obtain the coordinates of sub-pixel matching points based on known information. These methods suffer from insufficient accuracy and difficulty in adapting to the phase variation with pixel changes in theoretically invariant directions. In practical measurements, this leads to reduced accuracy in phase-based binocular matching, thereby reducing the accuracy of the point cloud obtained from 3D reconstruction.

[0005] Phase subpixel matching can solve the problem of low accuracy in phase binocular matching. Phase subpixel matching is defined as a method for determining the subpixel-level position of corresponding phases in a phase image. It typically uses a matching phase image as a reference and searches for the corresponding subpixel phase point in another image within acceptable accuracy and efficiency limits. Therefore, phase subpixel matching usually involves at least two phase images. To ensure matching accuracy, orthogonal phase images are usually used, resulting in a total of four phase images for binocular systems.

[0006] Existing literature and data show that current phase subpixel matching methods directly use interpolation methods for solving the problem, without utilizing prior phase characteristics, and lack methods to guarantee search accuracy during the solution process. This results in the inability to guarantee high-precision binocular phase matching, or difficulty in adapting to the characteristic of phase variation with pixels in theoretically invariant directions. Consequently, the methods suffer from low phase binocular matching accuracy, significant susceptibility to singularities leading to point cloud noise, and reduced overall 3D reconstruction point cloud accuracy. Summary of the Invention

[0007] The purpose of this invention is to overcome the above-mentioned shortcomings and provide a binary iterative sub-pixel matching method and system for phase structured light three-dimensional measurement, ensuring the accuracy of three-dimensional measurement.

[0008] The objective of this invention can be achieved through the following technical solutions:

[0009] In a first aspect, the present invention provides a binary iterative sub-pixel matching method for three-dimensional measurement of phase structured light, comprising:

[0010] Obtain the phase map;

[0011] Perform validity marking and pixel-level initial matching on the phase map;

[0012] Determine the sub-pixel search region based on pixel-level initial matching;

[0013] Based on the subpixel search region, a binary iterative method is used to search for subpixel matching points to obtain subpixel matching points.

[0014] As a further improvement of the present invention, the phase map is obtained by obtaining a binocular orthogonal phase map based on a phase shift algorithm.

[0015] As a further improvement of the present invention, the step of performing legality marking and pixel-level initial matching on the phase map includes:

[0016] The phase map is marked as valid. Regions in the phase map that do not have phase values ​​are empty values. Pixels in the phase map that have phase but are not empty values ​​are marked as 1 and designated as points to be matched.

[0017] The center point of the matching window is found using epipolar constraints. Then, pixel-level corresponding points are found in the neighborhood of the center point of the matching window to perform initial pixel-level matching.

[0018] As a further improvement of the present invention, when using epipolar constraints to find the center point of the matching window of the corresponding point, the front and back depth constraints and phase height mapping are introduced into the matching search process, so that the search range is narrowed from an epipolar line to the vicinity of a point.

[0019] As a further improvement of the present invention, the step of determining the sub-pixel search region based on pixel-level initial matching includes:

[0020] The range of phase difference values ​​between adjacent pixels on the phase map to be matched is statistically analyzed, and the phase difference value of the corresponding matching point in the initial pixel-level matching is calculated. Based on the range of phase difference values ​​between adjacent pixels and the phase difference value of the corresponding point in the initial pixel-level matching, the search range of the matching point in the phase map to be matched and the maximum step size of the first search are determined.

[0021] As a further improvement of the present invention, determining the search range of the sub-pixel matching points of the matched point on the matched phase map and the maximum step size of the first search includes:

[0022] Divide the phase difference of the corresponding matching point in the initial pixel-level matching by the mean of the range of phase differences between adjacent pixels in the phase map to be matched, and round the result up to obtain the sub-pixel search region. Half of this value is used as the maximum step size for the first search.

[0023] As a further improvement of the present invention, the sub-pixel matching point search based on the sub-pixel search region and the sub-pixel matching point obtained by using a binary iterative method includes:

[0024] Within the subpixel search region, an iterative search method is employed, coupling orthogonal phases and using bilinear interpolation to evaluate the subpixel matching points obtained in each iteration. When the matching point does not meet the preset phase deviation, the search step size for the next iteration is halved, and the search direction for the iteration is updated based on the actual deviation value. When the number of iterations reaches a preset value or the phase deviation of the corresponding point is less than the preset phase deviation, the search is terminated, and the final subpixel matching point is obtained.

[0025] As a further improvement of the present invention, the iterative search method is a variable step-size binary iteration, which means that the step size of each search is reduced by half compared to the previous search. The search direction is determined by the relationship between the phase value of the sub-pixel obtained by bilinear interpolation and the phase value to be matched. If the value of the sub-pixel is too small, the matching search direction becomes the direction of monotonically increasing phase; if the value of the sub-pixel is too large, the matching search direction becomes the direction of monotonically decreasing phase.

[0026] As a further improvement of the present invention, the coupled orthogonal phase is used to determine the sub-pixel matching point, that is, the Euclidean distance of the orthogonal phase between the matching points, through a function of the coupled orthogonal phase, thereby obtaining the matching accuracy.

[0027] In a second aspect, the present invention provides a binary iterative sub-pixel matching system for phase structured light three-dimensional measurement, comprising:

[0028] The acquisition module is used to acquire the phase map;

[0029] The marking and matching module is used to perform legality marking and pixel-level initial matching on the phase map;

[0030] The region determination module is used to determine the sub-pixel search region based on pixel-level initial matching;

[0031] The iterative module is used to search for subpixel matching points based on the subpixel search region using a binary iterative method to obtain subpixel matching points.

[0032] Thirdly, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aforementioned binary iterative sub-pixel matching method for phase structured light three-dimensional measurement.

[0033] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the binary iterative subpixel matching method for phase structured light three-dimensional measurement.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] This invention introduces a phase validity marker in pixel-level initial matching and a phase height mapping in epipolar search, improving the efficiency of pixel-level initial matching. Subsequently, the information obtained from the initial matching is used to limit the search range of sub-pixel matching, improving the search efficiency of sub-pixel matching. Furthermore, the monotonicity of the phase is utilized, combined with variable-step-size binary iteration and bilinear interpolation, to search for sub-pixel matching points, ensuring the search efficiency, accuracy, and convergence of sub-pixel matching points. Finally, a function coupled with orthogonal phases is used to determine the precision of sub-pixel matching points, thereby achieving higher matching accuracy. Attached Figure Description

[0036] Figure 1 This is a flowchart of a binary iterative subpixel matching method for phase structured light three-dimensional measurement according to the present invention;

[0037] Figure 2 This is a flowchart of the sub-pixel matching method given in an embodiment of the present invention;

[0038] Figure 3 Four phase images, one horizontal and one vertical, from the left and right cameras; (a) horizontal phase from the left camera, (b) vertical phase from the left camera, (c) horizontal phase from the right camera, and (d) vertical phase from the right camera.

[0039] Figure 4The epipolar constraint is used to find the center point of the matching window for the corresponding points; where (a) is the left camera view and (b) is the right camera view.

[0040] Figure 5 Flowchart of a binocular pixel-level matching algorithm based on epipolar constraints;

[0041] Figure 6 Flowchart of subpixel matching based on pixel-level initial matching and binary iterative subpixel matching;

[0042] Figure 7 A schematic diagram of a binary iterative subpixel matching system based on phase structured light 3D measurement. Detailed Implementation

[0043] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0044] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0045] like Figure 1 As shown, the first objective of this invention is to provide a binary iterative sub-pixel matching method for three-dimensional phase structured light measurement, comprising:

[0046] S1, obtain the phase map;

[0047] S2, perform legality marking and pixel-level initial matching on the phase map;

[0048] S3, determine the sub-pixel search region based on pixel-level initial matching;

[0049] S4, based on the subpixel search region, uses a binary iterative method to search for subpixel matching points and obtain subpixel matching points.

[0050] This invention discloses a binary iterative sub-pixel matching method for phase-structured light 3D measurement, belonging to the field of optical 3D measurement technology. The invention first performs phase map validity marking and initial pixel-level matching, then determines the sub-pixel search region based on prior phase characteristics to narrow the search range, and finally uses a binary iterative method to search for sub-pixel matching points. This invention can improve the accuracy of binocular matching in phase-structured light-based 3D measurement, thereby enhancing the accuracy of 3D reconstruction.

[0051] The steps of the present invention are described in detail below. The binocular binary iterative sub-pixel matching method for phase structured light three-dimensional measurement includes the following steps:

[0052] Step 1: Phase map validity marking and pixel-level initial matching.

[0053] On the obtained stereo phase map, the phase map is marked for validity to reduce the search and matching of invalid points; the epipolar constraint is used to find the center point of the matching window of the corresponding point, and the pixel-level corresponding point is found in the neighborhood of the center point of the matching window to achieve the initial pixel-level matching of the corresponding points of the stereo camera.

[0054] Optionally, in step one, the sub-pixel matching method is based on pixel-level initial matching. A binocular orthogonal phase map is obtained using a phase-shifting algorithm. The phase map is then marked for validity; regions in the phase map without phase values ​​are considered null values. Pixels in the phase map that have phase values ​​but are not null values ​​are marked as 1 and designated as points to be matched. The center point of the matching window for the corresponding point is found using methods such as epipolar constraints, and pixel-level initial matching is performed.

[0055] Optionally, in step one, when searching for the center point of the corresponding pixel-level initial matching window using epipolar constraints, in order to improve the efficiency and accuracy of the matching search, front and back depth constraints and phase height mapping are introduced into the matching search process. This can reduce the search range from an epipolar line to the vicinity of a point, thereby improving the matching efficiency.

[0056] Step 2: Determine the subpixel search area and narrow down the search range.

[0057] The range of phase difference values ​​between adjacent pixels on the phase map to be matched is statistically analyzed, and the phase difference value of the corresponding matching point in the initial pixel-level matching is calculated. Based on the range of phase difference values ​​between adjacent pixels and the phase difference value of the corresponding point in the initial pixel-level matching, the search range of the matching point in the phase map to be matched and the maximum step size of the first search are determined.

[0058] Optionally, in step two, before performing sub-pixel matching, the method divides the phase difference value of the matching point corresponding to the initial pixel matching by the average value of the difference range of phase values ​​between adjacent pixels on the phase map to be matched, and rounds the resulting value up to obtain the sub-pixel search area. Half of this value is used as the maximum step size for the first search to reduce the search range and improve the search accuracy and efficiency of sub-pixel matching points.

[0059] Step 3: Use the binary iterative method to search for sub-pixel matching points.

[0060] Within the search range, an iterative search method is adopted, coupling orthogonal phases and using bilinear interpolation to evaluate the sub-pixel matching points obtained in each iteration. When the matching point does not meet the preset phase deviation, the search step size for the next iteration is halved, and the search direction of the iteration is updated according to the actual deviation value. When the number of iterations reaches the preset value or the phase value deviation of the corresponding point is less than the preset phase deviation, the search is terminated, and the final sub-pixel matching point is obtained.

[0061] Optionally, in step three, the method utilizes the monotonicity of phase, combining variable-step-size binary search iteration and bilinear interpolation to search for sub-pixel matching points. Variable-step-size binary search iteration means that the step size of each search is halved compared to the previous search, resulting in rapid convergence of the solution. The search direction is determined by the relationship between the phase value of the sub-pixel obtained through bilinear interpolation and the phase value to be matched. If the value of the sub-pixel is too small, the matching search direction changes to a monotonically increasing phase direction; if the value of the sub-pixel is too large, the matching search direction changes to a monotonically decreasing phase direction.

[0062] Optionally, in step three, the method uses a function coupled with orthogonal phase to determine the accuracy of sub-pixel matching points during sub-pixel matching, i.e., the Euclidean distance of the orthogonal phases between matching points, thereby obtaining higher matching accuracy.

[0063] The method of the present invention will be described in detail below with reference to specific embodiments and accompanying drawings:

[0064] The invention will now be further described with reference to the accompanying drawings.

[0065] like Figure 2 As shown, this invention is a binary iterative sub-pixel matching method for phase-oriented binocular matching, and its specific implementation steps are as follows:

[0066] 1) After the measurement system obtains the phase-shifted fringe pattern modulated by the object under test, it obtains, according to the principle of the phase-shifting method, the following... Figure 3 The image shows four absolute phase images, one horizontal and one vertical, taken from a binocular camera.

[0067] 2) Mark the validity of the phase map. Mark the pixels with phase values ​​that do not match as "1" and the pixels without phase values ​​as "0".

[0068] 3) Use epipolar constraints to find the center point of the matching window for corresponding points. Using points in one side of the binocular image as the points to be matched, use epipolar constraints, foreground / background depth constraints, and phase height mapping to find the center point of the matching window for corresponding points, such as... Figure 4 As shown.

[0069] 4) Find the final pixel-level corresponding point within the neighborhood of the center point of the matching window. The overall flowchart of the phase binocular pixel-level initial matching process is as follows: Figure 5 As shown.

[0070] 5) Calculate the range of phase differences between adjacent pixels in a single phase map of the binoculars. The final average phase difference between adjacent pixels in the horizontal phase is 'a', and the average phase difference between adjacent pixels in the vertical phase is 'b'.

[0071] 6) Determine the phase difference value of the matching point corresponding to the initial pixel-level matching. Based on the information of the pixel-level matching points obtained in step one, count the phase difference values ​​of the horizontal and vertical phases of all matching point pairs. The horizontal phase difference value of the matching point is c, and the vertical phase difference value of the matching point is d.

[0072] 7) Determine the search range of subpixel matching points and the maximum step size for the first search. Based on the information obtained in step two, determine the search range of subpixel matching points: the horizontal search range is Ceiling(c / a), and the vertical search range is Ceiling(d / b). Therefore, the step size for the first search in the horizontal direction is Ceiling(c / 2a), and the step size for the first search in the vertical direction is Ceiling(d / 2b), where Ceiling() represents rounding up.

[0073] 8) Set the matching precision and maximum number of searches. Determine the matching precision as e and the maximum number of searches as num based on the actual project requirements.

[0074] 9) Sub-pixel matching point search using a binary iterative method. This invention utilizes the monotonic consistency of the phase map, employing a variable-step-size binary iterative method combined with bilinear interpolation for precise sub-pixel matching point search. Its basic idea is to first determine the integer-pixel matching point, then determine the phase value of the sub-pixel matching point through bilinear interpolation, and determine the search direction by comparing it with the phase of the point to be matched. See the detailed process below. Figure 5 .

[0075] 10) The sub-pixel matching points obtained in each iteration of the search are evaluated using a coupling function via bilinear interpolation. This invention employs the Euclidean distance between the orthogonal phases of the matching points to couple the phase information, and uses this coupling information to evaluate the matching accuracy. The specific formula is as follows:

[0076] S = (phaseLv - phaseRv(x,y)) 2 +(phaseLh-phaseRh(x,y)) 2

[0077] 11) When the number of iterations reaches the preset value or the accuracy requirement meets the preset value, the search process is terminated, and the final sub-pixel matching point is obtained.

[0078] 12) In a specific example of a 3D measurement system, using the whole pixels of one side of the camera as the matching basis, sub-pixel matching of all pixels is completed using the above method.

[0079] like Figure 7 As shown, the second objective of this invention is to propose an unsupervised logging comprehensive record summarization system based on a non-autoregressive model, comprising:

[0080] The acquisition module is used to acquire the phase map;

[0081] The marking and matching module is used to perform legality marking and pixel-level initial matching on the phase map;

[0082] The region determination module is used to determine the sub-pixel search region based on pixel-level initial matching;

[0083] The iterative module is used to search for subpixel matching points based on the subpixel search region using a binary iterative method to obtain subpixel matching points.

[0084] A third objective of this invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the aforementioned binary iterative subpixel matching method for phase structured light three-dimensional measurement.

[0085] The fourth objective of this invention is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned binary iterative subpixel matching method for phase structured light three-dimensional measurement.

[0086] 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.

[0087] 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 the invention. 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 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0088] 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.

[0089] 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.

[0090] 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 binary iterative sub-pixel matching method for three-dimensional phase structured light measurement, characterized in that, Includes the following steps: Obtain the phase map; Perform validity marking and pixel-level initial matching on the phase map; specifically including: The phase map is marked as valid. Regions in the phase map that do not have phase values ​​are empty values. Pixels in the phase map that have phase but are not empty values ​​are marked as 1 and designated as points to be matched. Using epipolar constraints, the center point of the matching window is found, and pixel-level corresponding points are found in the neighborhood of the center point of the matching window to perform initial pixel-level matching. Determining the sub-pixel search region based on pixel-level initial matching; specifically including: The range of phase difference values ​​between adjacent pixels on the phase map to be matched is statistically analyzed, and the phase difference value of the corresponding matching point in the initial pixel-level matching is calculated. Based on the range of phase difference values ​​between adjacent pixels and the phase difference value of the corresponding point in the initial pixel-level matching, the search range of the matching point in the phase map to be matched and the maximum step size of the first search are determined. Based on the subpixel search region, a binary iterative method is used to search for subpixel matching points to obtain subpixel matching points. Specifically, the search range of the sub-pixel matching points of the matched point on the phase map to be matched in the corresponding phase map to be matched, and the maximum step size of the first search are determined: Divide the phase difference of the corresponding matching point in the initial pixel-level matching by the mean of the range of phase differences between adjacent pixels in the phase map to be matched, and round the result up to obtain the sub-pixel search region. Half of this value is used as the maximum step size for the first search.

2. The binary iterative sub-pixel matching method for phase structured light three-dimensional measurement according to claim 1, characterized in that, The phase map is obtained by using a phase-shifting algorithm to obtain a binocular orthogonal phase map.

3. The binary iterative sub-pixel matching method for phase structured light three-dimensional measurement according to claim 1, characterized in that, When using epipolar constraints to find the center point of the matching window for corresponding points, front and back depth constraints and phase height mapping are introduced into the matching search process, which reduces the search range from an epipolar line to the vicinity of a point.

4. The binary iterative sub-pixel matching method for phase structured light three-dimensional measurement according to claim 1, characterized in that, The subpixel-based search region employs a binary iterative method to search for subpixel matching points, obtaining these points through: Within the subpixel search region, an iterative search method is employed, coupling orthogonal phases and using bilinear interpolation to evaluate the subpixel matching points obtained in each iteration. When the matching point does not meet the preset phase deviation, the search step size for the next iteration is halved, and the search direction for the iteration is updated based on the actual deviation value. When the number of iterations reaches a preset value or the phase deviation of the corresponding point is less than the preset phase deviation, the search is terminated, and the final subpixel matching point is obtained.

5. The binary iterative sub-pixel matching method for phase structured light three-dimensional measurement according to claim 4, characterized in that, The iterative search method is a variable step-size binary iteration, which means that the step size of each search is reduced by half compared to the previous search. The search direction is determined by the relationship between the phase value of the sub-pixel obtained by bilinear interpolation and the phase value to be matched. If the value of the sub-pixel is too small, the matching search direction becomes the direction of monotonically increasing phase; if the value of the sub-pixel is too large, the matching search direction becomes the direction of monotonically decreasing phase.

6. The binary iterative sub-pixel matching method for phase structured light three-dimensional measurement according to claim 4, characterized in that, The coupled orthogonal phase is used to determine the sub-pixel matching point through a function of coupled orthogonal phase, that is, the Euclidean distance of the orthogonal phase between matching points, thereby obtaining the matching accuracy.

7. A binary iterative sub-pixel matching system for phase-structured light three-dimensional measurement, based on the binary iterative sub-pixel matching method for phase-structured light three-dimensional measurement according to any one of claims 1 to 6, characterized in that, include: The acquisition module is used to acquire the phase map; The marking and matching module is used to perform legality marking and pixel-level initial matching on the phase map; The region determination module is used to determine the sub-pixel search region based on pixel-level initial matching; The iterative module is used to search for subpixel matching points based on the subpixel search region using a binary iterative method to obtain subpixel matching points.

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