A polarization three-dimensional imaging method fusing fringe projection

Abstract

This invention discloses a polarization-based 3D imaging method using fused fringe projection, comprising: acquiring a polariton image of a target surface; establishing a micro-element normal vector mathematical model on the target surface and calculating the zenith angle and azimuth angle; projecting multiple sinusoidal grating fringe patterns with continuous phase changes onto the target surface using a projector and simultaneously acquiring data using a camera, calculating the absolute phase information of the target; obtaining point cloud data of each point on the target surface using the absolute phase information by calibrating the camera and projector, and calculating the gradient information of each point based on the point cloud data; determining the theoretical range of the azimuth angle based on the gradient information and the normal vector mathematical model; correcting the azimuth angle according to the theoretical range; and reconstructing the 3D shape of the target based on the zenith angle and the corrected azimuth angle. This invention achieves accurate reconstruction of the 3D shape of the target by correcting the azimuth angle, and the device required to implement this method has a simple structure, which helps to reduce computational efficiency and cost.

Description

Technical Field

[0001] This invention belongs to the field of optical imaging technology, and specifically relates to a polarization three-dimensional imaging method that fuses fringe projection. Background Technology

[0002] Utilizing modern optoelectronic technology as a detection method offers robust advantages such as high precision, non-contact operation, anti-interference capabilities, and high speed, making it a major development direction in the field of optical imaging. This technology is evolving towards intelligence, automation, miniaturization, and diversification. Traditional photoelectric detection techniques primarily acquire light intensity information from a target scene—two-dimensional information—but this acquisition process often results in the loss of numerous important physical quantities within the target scene. After acquiring intensity information, methods such as feature detection and matching, target extraction, and tracking are generally required to interpret information from different scenes, thus limiting imaging quality and hindering the accurate interpretation of object 3D shape information. 3D imaging technology, as a means of acquiring crucial information about the real three-dimensional world, can provide depth information that cannot be obtained from two-dimensional images, providing data support and a theoretical foundation for reconstructing the true geometric shape of targets and subsequent 3D recognition and detection. Structured light 3D reconstruction technology based on stripe projection, as a non-contact active measurement method, can be considered as adding stable and significant feature points to the surface of the target by projecting a specific pattern sequence onto the surface of the target. The captured deformed coded stripe pattern modulated by the target is beneficial for obtaining accurate 3D contour data from the image carrying the 3D morphology information of the target surface.

[0003] Polarization-based 3D imaging is a passive imaging method that utilizes the polarization characteristics of light to reconstruct the surface of a target. Based on Fresnel's principle, it only requires establishing a mapping relationship between the 3D contour features of the target surface and the polarization characteristics of the emitted light waves to achieve 3D reconstruction of the target. It offers advantages such as high cost-effectiveness and simple information acquisition, providing the possibility for high-precision 3D reconstruction using the polarization characteristics of the target. However, during the interpretation of the polarization characteristics of the emitted light from the target surface, the singularity problem in the normal vector calculation leads to distortion in the integral reconstruction results. Therefore, resolving the singularity problem has become crucial for polarization-based 3D imaging technology.

[0004] Existing technology includes a polarization-based 3D reconstruction method combining a Kinect depth sensor. This method primarily utilizes the coarse depth data acquired by Kinect as prior information. It correlates surface normals obtained from the coarse depth map with normals obtained from polarization cues, fusing the high-resolution target surface normal directions obtainable from the visible light polarization image with the low-resolution depth information obtained by the camera. By applying additional constraints to eliminate low-frequency orientation blurring, it achieves correction of the normal map and super-resolution information fusion of the depth image, thus improving image quality. However, in practical applications, this method uses an additional depth sensor, leading to a more complex system structure and typically requiring higher computational performance.

[0005] It is evident that, on the one hand, traditional photoelectric detection methods, limited by detector limitations and other factors, can only acquire two-dimensional information about the target. While acquiring target information, they also lose crucial information in the light field, such as spectrum, phase, and polarization, resulting in limited imaging quality, difficulties in extracting feature information, and an inability to accurately interpret the object's three-dimensional shape. On the other hand, existing reconstruction methods based on multiple sensors require feature matching between sensors, leading to high computational demands, more complex system structures, and longer computation times, which can cause errors and negatively impact the reconstruction results and accuracy. Summary of the Invention

[0006] To address the aforementioned problems in the existing technology, this invention provides a polarization-based three-dimensional imaging method that fuses fringe projections. The technical problem to be solved by this invention is achieved through the following technical solution:

[0007] This invention provides a polarization three-dimensional imaging method for fusing fringe projection, comprising:

[0008] Obtain a polariton image of the target surface;

[0009] A mathematical model of micro-element normal vectors is established on the target surface. Polarization characteristic parameters, including the zenith angle θ and azimuth angle, are calculated using the polariton image.

[0010] Multiple sinusoidal grating fringe patterns with continuous phase changes are projected onto the target surface using a projector and simultaneously acquired using a camera to calculate the target's absolute phase information.

[0011] By calibrating the camera and projector, point cloud data of each point on the target surface is obtained using the absolute phase information, and gradient information of each point is calculated based on the point cloud data.

[0012] The theoretical range of the azimuth angle is determined based on the gradient information and the mathematical model of the normal vector.

[0013] Based on the theoretical range, the azimuth angle Perform correction;

[0014] Based on the zenith angle θ and the corrected azimuth angle The three-dimensional shape of the target is reconstructed by integrating the normal vectors of the target surface using an integral reconstruction algorithm.

[0015] In one embodiment of the present invention, the step of acquiring a polariton image of a target surface includes:

[0016] In an indoor environment, an integrating sphere is used to simulate natural light illumination;

[0017] The polarizer in front of the camera lens is rotated to a preset angle in sequence, and the reflected light from the target surface is collected by an imaging detector to obtain polariton images at different angles; wherein the preset angles include 0°, 45°, 90° and 135°.

[0018] Target background segmentation is performed on the polariton images at different angles.

[0019] In one embodiment of the present invention, the step of establishing a micro-surface element normal vector mathematical model on the target surface and calculating polarization characteristic parameters using the polariton image includes:

[0020] Based on the mapping relationship between the three-dimensional contour information of the target surface micro-element and the target surface normal vector, a mathematical model of the micro-element normal vector is established on the target surface, and the zenith angle θ is calculated according to the following formula:

[0021]

[0022] In the formula, n represents the refractive index of the target surface, ρ represents the degree of polarization of the polariton image obtained using the Stockes vector method to describe the intensity and polarization state of light waves, and θ is located at... between;

[0023] The polarization phase angle φ of the polarizer image is calculated using the following formula:

[0024]

[0025] In the formula, I max I min ξ represents the maximum and minimum light intensity obtained by rotating the polarizer one revolution, respectively; I represents the light intensity when the polarization phase angle is φ; ξ represents the angle between the transmission axis of the polarizer and the initial position of the polarizer; φ is between 0 and 2π.

[0026] Calculate the azimuth angle using the polarization phase angle φ

[0027] In one embodiment of the present invention, or

[0028] In one embodiment of the present invention, the step of projecting multiple sinusoidal grating fringe patterns with continuous phase changes onto the target surface using a projector and simultaneously acquiring them using a camera, and calculating the absolute phase information of the target, includes:

[0029] Multiple sinusoidal grating fringe patterns with continuous phase changes are projected onto the target surface using a projector and synchronized with cameras to obtain multiple images.

[0030] Based on the multiple images, the phase expansion method in the time phase expansion algorithm is used to perform phase expansion and obtain absolute phase information.

[0031] In one embodiment of the present invention, the normal vector mathematical model includes an X-axis, a Y-axis, and a Z-axis, wherein the X-axis is perpendicular to the Y-axis and lies within the tangent plane at each point, the Z-axis intersects the X-axis and Y-axis, and is perpendicular to the tangent plane; the gradient information includes the gradient field information p of the normal vector of the target surface in the X-axis direction. sl And the gradient field information q in the Y-axis direction sl ;

[0032] The steps for determining the theoretical range of the azimuth angle based on the gradient information and the mathematical model of the normal vector include:

[0033] Based on prior gradient information and the mathematical model of the normal vector, the target surface p is determined respectively. sl The relationship between the value of and the value of azimuth, and q sl The relationship between the value of and the value of azimuth;

[0034] Based on the target surface p sl The relationship between the value of and the value of azimuth, and q sl The relationship between the value of and the value of azimuth is used to determine the theoretical range of the azimuth of the target surface.

[0035] In one embodiment of the present invention, the azimuth angle is determined according to the theoretical interval range. Before performing the calibration step, the following steps are also included:

[0036] Determine the azimuth angle Whether it is within the theoretical range of azimuth angle.

[0037] In one embodiment of the present invention, the azimuth angle is determined according to the theoretical interval range. The steps for performing the calibration include:

[0038] When the azimuth angle When the azimuth angle is outside the theoretical range, the azimuth angle will be... Perform a 180° flip to obtain the corrected azimuth angle.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0040] This invention provides a polarization-based 3D imaging method that integrates fringe projection. It utilizes important phase and polarization information in the light field and achieves accurate reconstruction of the target's 3D shape through azimuth correction. In addition, the structure required to implement this invention is simple. Apart from the projection optical engine, only one image acquisition sensor is needed, eliminating the need for feature matching between multiple sensors, which reduces computational efficiency and cost to some extent.

[0041] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0042] Figure 1 This is a flowchart of a polarization three-dimensional imaging method for fused fringe projection provided in an embodiment of the present invention;

[0043] Figure 2 This is a schematic diagram of the mathematical model of the normal vector provided in an embodiment of the present invention;

[0044] Figure 3 p is provided in the embodiments of the present invention sl A schematic diagram showing the relationship between the value of and the value of azimuth.

[0045] Figure 4 The q provided in the embodiments of the present invention sl A schematic diagram showing the relationship between the value of and the value of azimuth.

[0046] Figure 5 This is a schematic diagram illustrating the theoretical range of the target surface azimuth angle provided in an embodiment of the present invention. Detailed Implementation

[0047] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0048] Figure 1 This is a flowchart of a polarization-based three-dimensional imaging method using fused fringe projection provided in an embodiment of the present invention. Figure 1 As shown, this embodiment of the invention provides a polarization orientation correction method for fused fringe projection, including:

[0049] S1. Obtain the polariton image of the target surface;

[0050] S2. Establish a mathematical model of the micro-element normal vector on the target surface, and calculate the polarization characteristic parameters using a polariton image. The polarization characteristic parameters include the zenith angle θ and the azimuth angle.

[0051] S3. Project multiple sinusoidal grating fringe patterns with continuous phase changes onto the target surface using a projector and simultaneously acquire them using a camera to calculate the absolute phase information of the target.

[0052] S4. By calibrating the camera and projector, the point cloud data of each point on the target surface is obtained using absolute phase information, and the gradient information of each point is calculated based on the point cloud data.

[0053] S5. Determine the theoretical range of azimuth angle based on gradient information and normal vector mathematical model;

[0054] S6. Calculate the azimuth angle based on the theoretical range. Perform correction;

[0055] S7, Based on zenith angle θ and corrected azimuth angle The three-dimensional shape of the target is reconstructed by integrating the normal vectors of the target surface using an integral reconstruction algorithm.

[0056] Optionally, in step S1 above, the step of obtaining a polariton image of the target surface includes:

[0057] In an indoor environment, an integrating sphere is used to simulate natural light illumination;

[0058] The polarizer in front of the camera lens is rotated to a preset angle in sequence, and the reflected light from the target surface is collected by the imaging detector to obtain polariton images at different angles; the preset angles include 0°, 45°, 90° and 135°.

[0059] Target background segmentation is performed on polariton images at different angles.

[0060] Specifically, firstly, natural light illumination is simulated indoors using an integrating sphere. Then, reflected light from the target surface is collected using an imaging detector. During the acquisition process, the polarizer in front of the camera lens can be rotated to obtain polariton images at four preset angles: 0°, 45°, 90°, and 135°. After acquiring polariton images at different angles, reasonable thresholds are set to segment the target and background regions in each polariton image. It should be noted that this embodiment can use any existing image processing algorithm to segment the polariton images, so it will not be elaborated here.

[0061] In step S2 above, the step of establishing a mathematical model of the micro-surface element normal vector on the target surface and calculating the polarization characteristic parameters using the polariton image includes:

[0062] S201. Based on the mapping relationship between the three-dimensional contour information of the micro-surface elements of the target surface and the normal vector of the target surface, establish a mathematical model of the normal vector of the micro-surface elements on the target surface.

[0063] S202. Using the polarizer image, obtain the degree of polarization ρ of the polarizer image according to the Stockes vector representation method for describing light wave intensity and polarization state, and calculate the zenith angle θ according to the following formula:

[0064]

[0065] In the formula, n represents the refractive index of the target surface, and θ is located at... between;

[0066] S203. Since the intensity of reflected light from the target surface changes with the polarizer angle, the change in the intensity information of the micro-surface elements can be expressed as follows:

[0067]

[0068] In the formula, I max I min The maximum and minimum light intensities obtained by rotating the polarizer one revolution are respectively represented by I, which represents the light intensity when the polarization phase angle is φ, and ξ represents the angle between the transmission axis of the polarizer and the starting position of the polarizer. φ is between 0 and 2π.

[0069] Figure 2 This is a schematic diagram of the normal vector mathematical model provided in an embodiment of the present invention. In this embodiment, based on the mapping relationship between the three-dimensional topographic information of the target surface micro-element and the normal vector, a normal vector mathematical model for characterizing the three-dimensional contour information of the target can be established. Specifically, as shown... Figure 2 As shown, the mathematical model of the normal vector includes the X-axis, Y-axis, and Z-axis. The X-axis is perpendicular to the Y-axis and lies in the tangent plane at each point on the target surface. The Z-axis intersects the X-axis and Y-axis and is perpendicular to the tangent plane. It should be understood that the zenith angle is the angle between the direction of the normal vector and the Z-axis, and the azimuth angle is the angle between the projection of the normal vector onto the XoY plane and the direction of the X-axis.

[0070] Please see Figure 2 The mathematical model of the normal vector shown is as follows: the normal vector of a point on the target surface z = f(x,y) is expressed as... normal vector The direction is affected by the polarization characteristic parameters zenith angle θ and azimuth angle Due to constraints, it is necessary to solve for these two parameters using the polarization characteristics of the target. According to Fresnel's formula, the intensity of reflected light changes after passing through the polarizer. During the generation of the polariton image, the polarizer is placed in front of the camera. The maximum and minimum light intensities acquired by pixels in the polariton image are denoted as I0 and I1, respectively. max I minThe angle between the transmission axis of the polarizer and the initial reference position is ξ, and the polarization phase angle of the reflected light is φ. Based on the principle of polarization imaging, this embodiment uses the approach of reconstructing diffuse reflection targets. Typically, the reflectivity of diffuse reflection targets ranges from 1.4 to 1.6. In this embodiment, the refractive index of the target surface is set to n = 1.5. Therefore, the zenith angle θ and azimuth angle of the normal vector of the target surface can be calculated using the degree of polarization ρ and the polarization phase angle φ. For example:

[0071]

[0072]

[0073] It should be noted that the azimuth angle obtained in this embodiment is calculated using polarization information. Singularity exists. or

[0074] Optionally, in step S3 above, the step of projecting multiple sinusoidal grating fringe patterns with continuous phase changes onto the target surface using a projector and simultaneously acquiring them using a camera, and calculating the absolute phase information of the target, includes:

[0075] Multiple sinusoidal grating fringe patterns with continuous phase changes are projected onto the target surface using a projector and synchronized with cameras to obtain multiple images.

[0076] Based on multiple images, the multi-frequency heterodyne method in the time phase unfolding algorithm is used to perform phase unfolding to obtain absolute phase information.

[0077] In the polarization three-dimensional imaging method for fused fringe projection provided by this invention, the azimuth angle is calculated. Then, it is necessary to further utilize the fused fringe projection method to obtain point cloud data carrying prior gradient information of the target surface.

[0078] Specifically, a monocular structured light system is constructed using an industrial camera and a projector. Multiple sinusoidal grating fringe patterns with continuous phase changes are projected onto the target surface via the projector. The camera then captures the modulated fringes to extract phase information. In this embodiment, the multi-frequency heterodyne method in the time-phase unfolding algorithm is used for phase unfolding to obtain the final absolute phase information. Furthermore, the system is calibrated using a monocular inverse camera model, and the projection matrices of the camera and projector are solved. Based on the transformation relationship from absolute phase information to three-dimensional coordinates, point cloud data is acquired.

[0079] Additionally, in step S4, a region of interest (ROI) can be set on the target surface. After Gaussian smoothing of the point cloud data at each point within the ROI, the gradient information {p} at each point within the ROI is calculated. sl(x,y),q sl (x,y)}, where p sl The gradient field information of the normal vector of the target surface in the X-axis direction, q sl This refers to the gradient field information of the normal vector of the target surface along the Y-axis. Of course, in some other embodiments of the present invention, the region of interest may not be defined, and the gradient information can be calculated directly using all the point cloud data of the target surface. sl (x,y),q sl (x,y)}. This invention does not limit this.

[0080] Step S5 above, which involves determining the theoretical range of the azimuth angle based on gradient information and the mathematical model of the normal vector, includes:

[0081] S501. Based on prior gradient information and normal vector mathematical models, the target surface p is determined respectively. sl The relationship between the value of and the value of azimuth, and q sl The relationship between the value of and the value of azimuth;

[0082] S502, Based on the target surface p sl The relationship between the value of and the value of azimuth, and q sl The relationship between the value of and the value of azimuth is used to determine the theoretical range of the azimuth of the target surface.

[0083] Please continue reading Figure 2 In this embodiment, the normal vector of a point z = f(x,y) on the target surface It can be represented as:

[0084]

[0085]

[0086] The above equation can be simplified to the following relationship:

[0087]

[0088] Furthermore,

[0089]

[0090] Where, n x n y and n z These represent the normal vectors of the point. In the components along the X, Y, and Z axes, θ represents the normal vector at that point. The zenith corner, Represents the normal vector of that point. The azimuth angle.

[0091] Based on the above analysis, it can be seen that for a point z = f(x,y), the gradient field information p of its normal vector in the X-axis direction and the gradient field information q in the Y-axis direction will jointly determine the azimuth angle. The approximate range of the gradient information {p} is thus determined in this embodiment. sl (x,y),q sl Using (x,y)} as prior information, the singularity problem of azimuth angle obtained from the polarizer image is corrected, and the uniqueness of the direction of the normal vector of the micro-element of the target surface is determined.

[0092] Figure 3 p is provided in the embodiments of the present invention sl A schematic diagram showing the relationship between the values ​​of and azimuth angle. Figure 4 The q provided in the embodiments of the present invention sl A schematic diagram showing the relationship between the values ​​of and azimuth angle. Figure 5 This is a schematic diagram illustrating the theoretical range of the target surface azimuth angle provided in an embodiment of the present invention. For example... Figure 3-5 As shown, the plane is divided into four regions by the horizontal and vertical axes, forming the first, second, third, and fourth quadrants in a counter-clockwise direction, starting from the upper right. Please refer to [link / reference]. Figure 3 The horizontal axis represents p sl To determine the value of , establish a cross-shaped plane coordinate system. The horizontal and vertical axes divide the plane into four different quadrants. Each quadrant corresponds to one of the four possible azimuth angle values, thus dividing the range from 0 to 2π into four parts. The region to the left of the vertical axis represents p. sl When the azimuth angle value is greater than 0, the range of values ​​within the right region represents p. sl When the azimuth angle is less than 0, the range of values ​​is obviously within that range. From the properties of sine and cosine functions, we know that when p sl When the value is greater than 0, the range of azimuth angle values ​​is: Right now Figure 3 The second and third quadrants in the diagram; when p sl When <0, the range of azimuth angle values ​​is: and Right now Figure 3 The first and fourth quadrants of the map.

[0093] Similarly, please see Figure 4 The vertical axis represents q. sl The values ​​of q are represented in the region below the horizontal axis. sl When the azimuth angle is greater than 0, the range of values ​​within the azimuth angle and the area above it represent q. sl When q < 0, the range of azimuth values ​​is within this range. sl When >0, azimuth angle The value range of is π to 2π, that is Figure 4The third and fourth quadrants in the diagram; when q sl When <0, azimuth angle The value range of is 0 to π, that is... Figure 4 The first and second quadrants in the diagram.

[0094] Furthermore, combined Figure 3 and Figure 4 , with p sl >0 and q sl Taking the case where the value is greater than 0 as an example, by taking the intersection of their respective intervals, the theoretical range of the azimuth angle can be determined as follows: That is Figure 5 The third quadrant is shown.

[0095] In this embodiment, the azimuth angle is determined based on the theoretical range. Before the calibration step, the following are also included:

[0096] Determine the azimuth Whether it is within the theoretical range of azimuth angle.

[0097] Specifically, if the calculated azimuth angle If it does not fall within the theoretical range, then the azimuth angle will be... By flipping π, the corrected azimuth angle is obtained. Thus, the zenith angle θ and the corrected azimuth angle are used. The polarization azimuth correction of the target is obtained by integrating the normal vector of the target surface using an integral reconstruction algorithm.

[0098] As can be seen from the above embodiments, the beneficial effects of the present invention are as follows:

[0099] This invention provides a polarization-based 3D imaging method that integrates fringe projection. It utilizes important phase and polarization information in the light field and achieves accurate reconstruction of the target's 3D shape through azimuth correction. In addition, the structure required to implement this invention is simple. Apart from the projection optical engine, only one image acquisition sensor is needed, eliminating the need for feature matching between multiple sensors, which reduces computational efficiency and cost to some extent.

[0100] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0101] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0102] Although this application has been described herein in conjunction with various embodiments, other variations of the disclosed embodiments can be understood and implemented by those skilled in the art in carrying out the claimed application by reviewing the accompanying drawings, the disclosure, and the appended claims.

[0103] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A polarization three-dimensional imaging method of fusion fringe projection, characterized in that, include: Obtain a polariton image of the target surface; A microfacet normal mathematical model is established on the target surface, and a polarization characteristic parameter is calculated by using the polarization sub-image, the polarization characteristic parameter including zenith angle and azimuth angle ; Multiple sinusoidal grating fringe patterns with continuous phase changes are projected onto the target surface using a projector and simultaneously acquired using a camera to calculate the target's absolute phase information. By calibrating the camera and projector, point cloud data of each point on the target surface is obtained using the absolute phase information, and gradient information of each point is calculated based on the point cloud data. The theoretical range of the azimuth angle is determined based on the gradient information and the mathematical model of the normal vector. According to the theoretical range interval for the azimuth angle correction is made; Based on zenith angle And the corrected azimuth angle The normal vector of the target surface is integrated by using the integral reconstruction algorithm, and the three-dimensional morphology of the target is reconstructed. The normal vector mathematical model comprises an X axis, a Y axis and a Z axis, wherein the X axis is perpendicular to the Y axis and is located in a tangent plane of the points, the Z axis intersects the X axis and the Y axis, and the Z axis is perpendicular to the tangent plane; and the gradient information comprises gradient field information of the normal vector of the target surface in the X axis direction and gradient field information of the normal vector of the target surface in the Y axis direction. ;​ The steps for determining the theoretical range of the azimuth angle based on the gradient information and the mathematical model of the normal vector include: Based on prior gradient information and the mathematical model of the normal vector, the target surface is determined respectively. The relationship between the value of and the value of azimuth angle and The relationship between the value of and the value of azimuth; According to the target surface The relationship between the value of and the value of azimuth angle and The relationship between the value of and the value of azimuth is used to determine the theoretical range of the azimuth angle of the target surface; Based on the theoretical range, the azimuth angle The steps for performing the calibration include: When the azimuth angle When the azimuth angle is outside the theoretical range, the azimuth angle will be... Perform a 180° flip to obtain the corrected azimuth angle. .

2. The polarization three-dimensional imaging method for fused fringe projection according to claim 1, characterized in that, The steps for acquiring a polariton image of the target surface include: In an indoor environment, an integrating sphere is used to simulate natural light illumination; The polarizer in front of the camera lens is rotated sequentially to a preset angle, and the reflected light from the target surface is collected using an imaging detector to obtain polariton images at different angles; wherein, the preset angle includes , , and ; Target background segmentation is performed on the polariton images at different angles.

3. The polarization three-dimensional imaging method for fused fringe projection according to claim 2, characterized in that, The steps of establishing a mathematical model of micro-surface element normal vectors on the target surface and calculating polarization characteristic parameters using the polariton image include: Based on the mapping relationship between the three-dimensional contour information of the target surface micro-element and the target surface normal vector, a mathematical model of the micro-element normal vector is established on the target surface, and the zenith angle is calculated according to the following formula. : In the formula, Represents the refractive index of the target surface. This represents the degree of polarization of a polariton image obtained using the Stockes vector representation method to describe the intensity and polarization state of light waves. lie in between; The polarization phase angle of the polariton image is calculated using the following formula. : In the formula, , These represent the maximum and minimum light intensities obtained by rotating the polarizer one revolution, respectively. The polarization phase angle is represented as Light intensity at that time This indicates the angle between the transmission axis of the polarizer and the starting position of the polarizer. lie in between; Using the polarization phase angle Calculate azimuth .

4. The polarization three-dimensional imaging method for fused fringe projection according to claim 3, characterized in that, or .

5. The polarization three-dimensional imaging method for fused fringe projection according to claim 1, characterized in that, The steps of projecting multiple sinusoidal grating fringe patterns with continuous phase changes onto the target surface using a projector and simultaneously acquiring them using a camera, and calculating the absolute phase information of the target, include: Multiple sinusoidal grating fringe patterns with continuous phase changes are projected onto the target surface using a projector and synchronized with cameras to obtain multiple images. Based on the multiple images, a time-phase unfolding algorithm is used to perform phase unfolding to obtain absolute phase information.

6. The polarization three-dimensional imaging method for fused fringe projection according to claim 1, characterized in that, Based on the theoretical range, the azimuth angle Before performing the calibration step, the following steps are also included: Determine the azimuth angle Whether it is within the theoretical range of azimuth angle.

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