Adaptive encoding complementary color stripe method for measuring three-dimensional profile of high-reflective object

Abstract

The application discloses a kind of self-adapting coding complementary color stripe high-reflective object three-dimensional topography measurement method.The application utilizes the selective absorption principle of light, uses color projector when measuring, projects color coding stripe with the color of the region being optical complementary color for the surface high-reflective region of the object to be measured, increases the absorption degree of the surface high-reflective region of the object to be measured to the intensity of the projected light, reduces the intensity of the reflected light, so that the intensity value of the deformed stripe collected is within the dynamic range of the camera, ensures the completeness of the measurement data of the region, solves the problem of three-dimensional data acquisition loss caused by the high-reflective surface of the object to be measured, and when coding the sinusoidal stripe pattern, only the color of the projected pattern is changed without changing the light intensity of the projected pattern, preventing the influence of high-order harmonics on the measurement results and improving the measurement accuracy.

Description

Technical Field

[0001] This invention relates to the field of optical non-contact measurement of the three-dimensional shape of highly reflective objects, specifically a method for measuring the three-dimensional shape of highly reflective objects with adaptively encoded complementary color fringes. Background Technology

[0002] Highly reflective surfaces typically exhibit non-uniform reflectivity. When incident light strikes these surfaces, interface reflections easily occur, creating a focusing effect at a specific point, leading to flares or shine. Due to dynamic range limitations, images captured by the camera at highly reflective locations often suffer from oversaturated pixels. This results in the loss of fringe phase information during fringe projection profilometry measurements of the object's 3D shape, leading to data gaps in the reconstruction and ultimately affecting the accuracy of the 3D measurement. Therefore, improving the measurement efficiency and accuracy of highly reflective surfaces remains a pressing challenge.

[0003] To address the challenge of data loss in the 3D topography of highly reflective areas when using fringe projection profilometry to measure the surface morphology of highly reflective objects, current research often employs methods such as multiple exposure time, adjusting projection light intensity, and polarizing filters. Numerous studies have been conducted by researchers both domestically and internationally in recent years, as detailed below:

[0004] The paper "Zhang P, Zhong K, Li Z, et al. Hybrid-quality-guided phase fusion model for high dynamic range 3D surface measurement by surface measurement by structured light technology[J]. Optics Express, 2022, 30(9): 14600-14614" proposes a hybrid-quality-guided phase fusion model to address the problem of fusing multiple images taken by a camera at different exposure times in the multiple exposure time method. This model uses a hybrid quality metric to more comprehensively evaluate phase quality, weighting and fusing all initial phases to obtain an accurate final phase for reconstructing the 3D shape of the object. However, this method only allows for subjective control of the exposure time, resulting in a lack of quantitative calculation to determine the appropriate exposure time during measurement, leading to unstable measurement quality. Furthermore, it requires capturing multiple sets of phase-shift fringe patterns, consuming a significant amount of time.

[0005] The paper "Liu Y, Fu Y, Cai X, et al. A novel high dynamic range 3D measurement method based on adaptive fringe projection technique[J]. Optics and Lasers in Engineering, 2020, 128(0):106004." proposes an adaptive fringe projection technique. This technique projects 255 uniform grayscale patterns onto the image surface to mark saturated areas. Then, another low-intensity uniform pattern is used to calculate the surface reflectance. Appropriate grayscale values ​​are projected in the camera coordinate system at the pixel level to establish the spatial relationship between the camera and the projection system. The generated adaptive fringe pattern is then used to measure the object. However, changing the light intensity value of the projected pattern during the measurement process introduces high-order harmonics, affecting measurement accuracy. Furthermore, the initial projection light intensity value is set blindly when calculating surface reflectance, leading to instability in the measurement results.

[0006] The paper "Wang Y, Zhang Q, Hu Y, et al. Rapid 3D measurement of high dynamic range surface based on multi-polarization fringe projection[J]. Optical Engineering, 2021, 60(8): 084107." proposes a high dynamic range surface 3D measurement technique based on multi-polarization fringe projection. A polarization camera is used to simultaneously acquire full-resolution phase-shifted images in four polarization directions. By analyzing the auxiliary pixels acquired by the camera and selecting appropriate polarization directions, a high-quality optimal phase-shifted fringe image is obtained, effectively removing the influence of specular highlights during 3D measurement of the object surface. However, this technique requires high precision in the placement and angle of the polarization camera in the measurement system, and the measurement operation is complex.

[0007] The methods or techniques mentioned in the aforementioned literature have solved the problem of measuring the three-dimensional shape of highly reflective objects to some extent. However, many problems still exist, such as the need to acquire a large number of fringe images, the need for complex calculations, or the need to add auxiliary devices, which increases the measurement difficulty. Therefore, there is an urgent need to develop a method for measuring the three-dimensional shape of highly reflective objects that requires fewer images. Summary of the Invention

[0008] To address the shortcomings of existing technologies, the technical problem this invention aims to solve is to provide a method for measuring the three-dimensional shape of highly reflective objects with adaptively encoded complementary color stripes.

[0009] The technical solution of this invention to solve the aforementioned technical problem is to provide a method for measuring the three-dimensional shape of highly reflective objects with adaptively encoded complementary color fringes, characterized in that the method includes the following steps:

[0010] (1) Set up the measurement system: The CCD camera and the color projector are fixed on the optical platform; the optical axis of the CCD camera and the optical axis of the color projector are on the same horizontal plane and are parallel to the optical platform; the CCD camera, the color projector and the object to be measured are in a triangular measurement relationship in space, and the object to be measured is located within the depth of field of the CCD camera and the color projector to form a clear image; the computer is connected to the CCD camera and the color projector respectively.

[0011] (2) Calibration Measurement System: The calibration plate with the circular mark is placed at different calibration positions within the depth of field of the CCD camera and the color projector where a clear image can be formed; at each calibration position, the color projector projects a sinusoidal fringe pattern onto the surface of the calibration plate, and the folding phase and unfolding phase of the calibration plate surface at that calibration position are solved; at the same time, a texture image of the calibration plate is acquired at each calibration position, and the center pixel coordinates of the circular mark on the calibration plate are extracted; the conversion relationship between the absolute phase of each pixel and the actual depth Z, as well as the relationship between the pixel coordinates of each pixel and the XY coordinates, are established to obtain the system calibration parameters and complete the three-dimensional calibration of the measurement system;

[0012] (3) Calibrate the colors captured by the CCD camera and their optical complementary colors:

[0013] S3.1 Replace the calibration plate with the circular mark, place the calibration color mark card in the middle of the calibration plate in step (2), the CCD camera, color projector and color mark card are in a triangular measurement relationship in space, and the color mark card is in the depth of field of the CCD camera and color projector to form a clear image.

[0014] S3.2. The CCD camera captures a color image of a color within a color patch in the color chart; then the computer records the hue value H5 of the color within the color patch captured by the CCD camera, and finally calculates and generates the hue value H6 of the optical complementary color of that color as shown in equation (1):

[0015] H6=H5+180°+ΔH (1)

[0016] In equation (1), H6 is the hue value of the optical complementary color generated by computer 1; when H6≥360°, the hue value H6=H6-360°; H5 is the hue value of the color within the color patch captured by the CCD camera; ΔH is the hue value used to compensate for the color projection error of the color projector.

[0017] S3.3 Control the color projector to project the optical complementary color of the color onto the color block of the color chart; then control the CCD camera to collect the light intensity grayscale image reflected back from the color block on the color chart; when the light intensity of the light intensity grayscale image of the color block collected by the CCD camera reaches the minimum value, the optical complementary color of the color projected by the color projector at this time is the optical complementary color of the color in the color block on the color chart in this measurement system, and the computer records the hue value of the optical complementary color projected by the color projector at this time;

[0018] S3.4 Repeat steps S3.2 to S3.3 until all colors in the color blocks on the color chart have their optical complementary colors in this measurement system, and all color blocks have completed the calibration of their optical complementary colors; at the same time, obtain the hue values ​​of all colors in the color blocks in the color chart captured by the CCD camera, as well as the hue values ​​of their corresponding optical complementary colors projected by all color projectors.

[0019] S3.5. Based on the hue values ​​of all colors in the color blocks of the color chart acquired by the CCD camera in step S3.4, draw radius lines with different polar angles on the H hue disk plane of the HSV color space model; then, based on the number N of color blocks in the color chart, filter the radius lines representing the hue values ​​to obtain the hue disk of the colors acquired by the camera.

[0020] S3.6. Based on the hue values ​​represented by each radius line in the color hue wheel acquired by the camera, find the hue value of the optical complementary color of the color in the corresponding color block in the color chart obtained in step S3.4; then draw radius lines with different polar angles on the H hue wheel plane of the HSV color space model to obtain the optical complementary color hue wheel.

[0021] (4) Extract the position of the highly reflective area on the surface of the object under test in the camera pixel coordinate system and transform it to the coordinate system of the projector's projected image:

[0022] S4.1 Replace the position of the color chart in step (3) with the object to be tested;

[0023] S4.2 The computer generates an RGB-coded dot matrix map with equal horizontal and vertical coordinate intervals, ensuring that the highly reflective area contains at least one complete interval, based on the pixel size of the imaging surface of the color projector and the size of the highly reflective area on the surface of the object to be measured. The map is then projected onto the surface of the object to be measured via the color projector.

[0024] The background of the RGB encoded dot matrix is ​​white light with an intensity value of 255. The RGB values ​​and the number of pixels that make up each cross mark in the RGB encoded dot matrix are different, and the RGB values ​​of different cross marks correspond one-to-one with the pixel position coordinates of the mark in the coordinate system of the projector's projected image.

[0025] S4.3, The CCD camera acquires a color image of the surface of the object under test covered with an RGB-coded dot matrix pattern;

[0026] S4.4 The computer first judges the color image acquired in step S4.3 pixel by pixel, and defines each oversaturated pixel as a highly reflective point on the surface of the object to be tested, thereby obtaining the position coordinates of the highly reflective area on the surface of the object to be tested in the camera pixel coordinate system; then it obtains and decodes the position coordinates and encoded RGB values ​​of the four marker points that are closest to the area and form the smallest rectangle in the camera pixel coordinate system.

[0027] S4.5. Using the RGB values ​​of these four marker points, find their position coordinates in the projector's projected image coordinate system, and establish a one-to-one correspondence with the position coordinates of the four marker points obtained in step S4.4 in the camera pixel coordinate system. Then, for each oversaturated pixel in the highly reflective area in the camera pixel coordinate system, find its position coordinates (u... c ,v c Linear interpolation calculations are performed to obtain the coordinates of each point (u) in the highly reflective area under the coordinate system of the projected image. p ,v p The position coordinates of );

[0028] (5) Extract the color of the highly reflective area on the surface of the object under test and calculate and generate an adaptively encoded complementary color sinusoidal stripe pattern:

[0029] S5.1. The CCD camera acquires a color image of the object under test with no high reflectivity on its surface under natural light. Using the position coordinates of the highly reflective area on the surface of the object under test in the camera pixel coordinate system obtained in step S4.4, the computer extracts the hue value H0 and saturation value S0 of the color image at that position coordinate. The camera then uses a color hue disk to perform a complementary hue lookup on the hue value H0 using linear interpolation, and calculates the hue value H of the corresponding optical complementary color in the optical complementary color hue disk. c As shown in equation (3):

[0030]

[0031] In equation (3), A is the minimum hue value of H0 in the sector area of ​​the color wheel captured by the camera, and B is the maximum hue value of H0 in the sector area of ​​the color wheel captured by the camera. c Let A be the hue value of its complementary color in the optical complementary color wheel, and B be the hue value of its complementary color. c Let B be the complementary hue value of B in the optical complementary hue wheel;

[0032] S5.2. A color projector projects white light onto the surface of the object to be measured. Using the position coordinates of the highly reflective area on the surface of the object to be measured in the camera pixel coordinate system obtained in step S4.4, the color saturation value S of the color image at that position is extracted by a computer. h Then through S c =S0-S h The saturation value S of the optical complementary color was calculated. c ;

[0033] S5.3. The computer generates a sinusoidal fringe grayscale image; then, using the position coordinates of the highly reflective area on the surface of the object to be tested in the coordinate system of the projector image obtained in step S4.5, the hue value H of the optical complementary color obtained in step S5.1 is encoded at the same coordinate position in the sinusoidal fringe grayscale image. c And the saturation value S obtained in step S5.2 c This yields an adaptively encoded complementary color sinusoidal stripe pattern.

[0034] (6) Solving the three-dimensional morphology information of the object to be tested: Based on the adaptive coded complementary color sinusoidal fringe pattern obtained in step S5.3, the computer controls the color projector according to the phase shift method and the optimal three-fringe selection method to project a set of adaptive coded complementary sinusoidal fringe patterns with different number of fringe patterns and phase shift amount onto the surface of the object to be tested; then the CCD camera acquires the deformed fringe image reflected by the surface of the object to be tested; after processing by the computer program, the unfolded phase map is obtained; then using the conversion relationship between the absolute phase and the actual depth Z obtained in step (2), and the relationship between the pixel coordinates and XY coordinates of each pixel point in the unfolded phase map, the three-dimensional morphology data of the surface of the object to be tested are obtained by substituting into the solution.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0036] 1. High Measurement Accuracy: When measuring highly reflective objects using traditional sinusoidal fringe projection profilometry, the camera's dynamic range limits the pixel saturation of highly reflective areas on the object's surface, resulting in missing measurement data and low accuracy. This invention utilizes the principle of selective light absorption. During measurement, a color projector projects color-coded stripes that are optically complementary to the highly reflective areas of the object's surface. This increases the absorption of projected light intensity by the highly reflective areas, reduces reflected light intensity, and ensures that the intensity values ​​of the deformed stripes are within the camera's dynamic range, guaranteeing complete measurement data for these areas. This solves the problem of missing 3D data caused by high surface reflectivity. Furthermore, when encoding the sinusoidal fringe pattern, only the color of the projected pattern is changed, not its intensity, preventing the influence of higher harmonics on the measurement results and improving measurement accuracy.

[0037] 2. Simple measuring device: Based on the principle of triangulation, the measuring system only requires a CCD camera and a color projector to acquire images and project fringe structured light. No additional hardware facilities are needed to complete the measurement requirements. Moreover, the system structure is simple and easy to set up.

[0038] 3. Simple measurement steps: This invention only requires a CCD camera to capture a color image of the surface of the highly reflective object to be measured, which is covered with an RGB-coded dot matrix pattern. This allows the acquisition of the position coordinates of the highly reflective area on the surface of the object in the coordinate system of the projected image. After completing the optical complementary color calibration of the measurement system using a color chart, two color images of the surface of the object to be measured are projected under natural light and white light using a color projector. This allows the calculation of the color information of the complementary color sinusoidal fringe code for the highly reflective area on the surface of the object to be measured, thus completing the generation of adaptive complementary color coded fringes. Finally, only one set of adaptive complementary color coded sinusoidal fringe patterns needs to be projected to obtain the final complete unfolded phase and obtain the three-dimensional morphological data of the surface of the highly reflective object to be measured.

[0039] 4. Short measurement time: After generating the adaptive coded complementary color stripe pattern, this invention only needs to project a set of sinusoidal stripe phase shift patterns with this code to solve the three-dimensional morphology data of the surface of the object under test, resulting in a short measurement time. It solves the problem of the traditional method that requires multiple modifications to the camera exposure time or the light intensity value of the projected stripe pattern to capture multiple sets of sinusoidal stripe phase shift patterns, solve the unfolded phase, and then fuse them to obtain the three-dimensional morphology of the object under test, which consumes a lot of time.

[0040] 5. The method of the present invention is universal, widespread, and easy to promote. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the measurement system structure of the present invention;

[0042] Figure 2 This invention provides a camera-based color hue disk for acquisition, as an embodiment of the present invention.

[0043] Figure 3 This is an embodiment of the optical complementary color chromaticity disk of the present invention;

[0044] Figure 4 This is an RGB encoded identifier dot matrix diagram according to an embodiment of the present invention;

[0045] In the diagram, 1 is a computer, 2 is a CCD camera, 3 is a color projector, 4 is the object to be measured, 5 is a color wheel for camera to collect colors, 6 is an optical complementary color wheel, and 7 is an RGB coded dot matrix diagram. Detailed Implementation

[0046] Specific embodiments of the present invention are given below. These specific embodiments are only used to further illustrate the present invention in detail and do not limit the scope of protection of the claims of the present invention.

[0047] This invention provides a method for measuring the three-dimensional shape of highly reflective objects with adaptively encoded complementary color fringes (hereinafter referred to as the method), characterized by comprising the following steps:

[0048] (1) Set up the measurement system: CCD camera 2 and color projector 3 are fixed on the optical platform; the optical axis of CCD camera 2 and the optical axis of color projector 3 are on the same horizontal plane and are parallel to the optical platform; so that CCD camera 2, color projector 3 and the object to be measured 4 are in a triangular measurement relationship in space, and the object to be measured 4 is located within the depth of field of CCD camera 2 and color projector 3 to form a clear image; computer 1 is connected to CCD camera 2 and color projector 3 respectively.

[0049] Computer 1 is used to control CCD camera 2 and color projector 3, and to store, display and process the acquired images to obtain the corresponding measurement results; CCD camera 2 is used to extract the position coordinates of the highly reflective area on the surface of the object under test 4 in the camera pixel coordinate system, as well as the color information of the area, and to acquire adaptively coded complementary color stripe images of the deformation after reflection from the surface of the object under test 4 during the measurement of the object's three-dimensional shape data; color projector 3 is used to project the adaptively coded complementary color stripe pattern onto the surface of the object under test 4.

[0050] Preferably, in step (1), the angle between the optical axes of the CCD camera 2 and the color projector 3 is 25-30°.

[0051] (2) Calibration of the measurement system: The calibration plate with the circular mark is placed at different calibration positions within the depth of field of the CCD camera 2 and the color projector 3, where a clear image can be formed. At each calibration position, the color projector 3 projects a sinusoidal fringe pattern onto the surface of the calibration plate, and the folding phase and unfolding phase of the calibration plate surface at that calibration position are solved. At the same time, a texture image of the calibration plate is acquired at each calibration position, and the center pixel coordinates of the circular mark on the calibration plate are extracted. The conversion relationship between the absolute phase of each pixel and the actual depth Z, as well as the relationship between the pixel coordinates of each pixel and the XY coordinates, are established to obtain the system calibration parameters and complete the three-dimensional calibration of the measurement system.

[0052] Preferably, in step (2), the plane accuracy of the calibration plate is 1 μm.

[0053] Preferably, in step (2), the phase shift method is used to solve the folded phase, and more preferably, the four-step phase shift method is used. The optimal three-fringe selection method is used to solve the absolute phase, with the number of fringes in the three sets being 100, 99, and 90, respectively.

[0054] (3) Calibrate the colors acquired by CCD camera 2 and their optical complementary colors:

[0055] S3.1 Replace the calibration plate with the circular mark, place the calibration color mark card in the middle of the calibration plate in step (2), the CCD camera 2, the color projector 3 and the color mark card are in a triangular measurement relationship in space, and the color mark card is in a clear image within the depth of field of the CCD camera 2 and the color projector 3.

[0056] S3.2, CCD camera 2 acquires a color image of a color within a color block in a color chart; then computer 1 records the hue value H5 of the color within the color block acquired by CCD camera 2. According to the principle of photometric complementarity, the theoretical complementary color hue value of hue value H5 differs from it by 180°. However, due to the projection color error of color projector 3, it is necessary to take the theoretical complementary color hue value as the origin and change the hue value along the positive and negative directions of the hue interval, and superimpose the hue value ΔH to compensate for the projection color error of color projector 3, and finally calculate and generate the hue value H6 of the optical complementary color of the color (as shown in formula (1)).

[0057] Computer 1 calculates the hue value H6 of the optical complementary color of this color as shown in equation (1):

[0058] H6=H5+180°+ΔH (1)

[0059] In equation (1), H6 is the hue value of the optical complementary color generated by computer 1; when H6≥360°, the hue value H6=H6-360°; H5 is the hue value of the color within the color patch acquired by CCD camera 2; ΔH is the hue value used to compensate for the color projection error of color projector 3.

[0060] S3.3 Control the color projector 3 to project the optical complementary color of the color onto the color block of the color chart; then control the CCD camera 2 to collect the light intensity grayscale image reflected back from the color block on the color chart; when the light intensity of the light intensity grayscale image of the color block collected by the CCD camera 2 reaches the minimum value, then the optical complementary color of the color projected by the color projector 3 at this time is the optical complementary color of the color in the color block on the color chart in this measurement system, and the computer 1 records the hue value of the optical complementary color projected by the color projector 3 at this time;

[0061] S3.4 Repeat steps S3.2 to S3.3 until all colors in the color blocks on the color chart have their optical complementary colors in this measurement system, and all color blocks have completed the calibration of their optical complementary colors; at the same time, obtain the hue values ​​of all colors in the color blocks in the color chart collected by the CCD camera 2, as well as the hue values ​​of the optical complementary colors projected by all the corresponding color projectors 3.

[0062] S3.5. Based on the hue values ​​of all colors in the color blocks of the color chart acquired by the CCD camera 2 in step S3.4, draw radius lines with different polar angles on the H hue disk plane of the HSV color space model; then, based on the number N of color blocks in the color chart, filter the radius lines representing the hue values ​​to obtain the camera-acquired color hue disk 5.

[0063] Preferably, in step S3.5, the screening principle for the radius lines representing hue values ​​is: when the adjacent angles of different radius lines are less than 360 / N° (15° in this embodiment), the median value of the polar angle of these radius lines is selected to simplify them into a single line and the redundant radius lines are discarded.

[0064] S3.6. Based on the hue values ​​represented by each radius line in the color hue disk 5 acquired by the camera, find the hue value of the optical complementary color of the color in the corresponding color block in the color chart obtained in step S3.4; then draw radius lines with different polar angles on the H hue disk plane of the HSV color space model to obtain the optical complementary color hue disk 6.

[0065] Preferably, in step 3, in this embodiment, a 24-color swatch is selected. When the adjacent angles of different radius lines are less than 15°, the H hue disk plane is finally divided into ten sector intervals to draw the camera-collected color hue disk 5 (e.g., Figure 2 (As shown); the camera captures ten sector-shaped intervals in the color hue wheel 5, each interval corresponding to the optical complementary color hue wheel 6 (as shown). Figure 3 The sector regions with the same number (as shown) are a pair of optically complementary hue regions.

[0066] (4) Extract the position of the highly reflective area on the surface of the object 4 under test in the camera pixel coordinate system and transform it to the coordinate system of the projector's projected image:

[0067] S4.1 Replace the position of the color chart in step (3) with the object to be tested 4;

[0068] S4.2. The computer 1 generates an RGB-coded dot matrix map 7 with the same horizontal and vertical coordinate intervals and ensures that the highly reflective area contains at least one complete interval, based on the pixel size of the imaging surface of the color projector 3 and the size of the highly reflective area on the surface of the object to be tested 4. The map is then projected onto the surface of the object to be tested 4 via the color projector 3.

[0069] The background of the RGB encoding dot matrix diagram 7 is white light with a light intensity value of 255. The RGB values ​​and the number of pixels that make up each cross mark in the RGB encoding dot matrix diagram 7 are different, and the RGB values ​​of different cross marks correspond one-to-one with the pixel position coordinates of the mark in the coordinate system of the projector's projected image.

[0070] S4.3, CCD camera 2 acquires a color image of the surface of the object under test 4 covered with RGB coded dot matrix pattern 7;

[0071] S4.4 First, the computer 1 judges the color image acquired in step S4.3 pixel by pixel, and defines each oversaturated pixel as a highly reflective point on the surface of the object under test 4, thereby obtaining the position coordinates of the highly reflective area on the surface of the object under test 4 in the camera pixel coordinate system; then it obtains and decodes the position coordinates and encoded RGB values ​​of the four marker points that are closest to the area and form the smallest rectangle in the camera pixel coordinate system.

[0072] S4.5. Using the RGB values ​​of these four marker points, find their position coordinates in the projector's projected image coordinate system, and establish a one-to-one correspondence with the position coordinates of the four marker points obtained in step S4.4 in the camera pixel coordinate system. Then, for each oversaturated pixel in the highly reflective area in the camera pixel coordinate system, find its position coordinates (u... c ,v c Linear interpolation calculations are performed (as shown in equation (2)) to finally obtain the coordinates of each point (u) in the highly reflective area under the coordinate system of the projector's projected image. p ,v p The position coordinates of );

[0073] Preferably, in step S4.5, the linear interpolation calculation is as shown in equation (2):

[0074]

[0075] In equation (2), (u c11 ,v c11 ), (u c12 ,v c12 ), (u c21 ,v c21 (u) represents the position coordinates of the three marker points (top left, top right, and bottom left) forming a rectangle in the camera pixel coordinate system; p11 ,v p11 ), (u p12 ,v p12 ), (u p21 ,v p21 Let be the coordinates of the three marker points (top left, top right, and bottom left) forming a rectangle in the coordinate system of the projected image. Since the horizontal and vertical coordinates of the marker points have the same part, they can be simplified to be represented by these three marker points.

[0076] (5) Extract the color of the highly reflective area on the surface of the object under test and calculate and generate an adaptively encoded complementary color sinusoidal stripe pattern:

[0077] S5.1, CCD camera 2 acquires a color image of the object under test 4 under natural light with no high reflectivity. Using the position coordinates of the highly reflective area on the surface of the object under test 4 in the camera pixel coordinate system obtained in step S4.4, computer 1 extracts the hue value H0 and saturation value S0 of the color image at that position coordinate. The camera acquires a color hue disk 5 and uses linear interpolation to perform a complementary hue lookup on the hue value H0. The corresponding optical complementary color hue value H is calculated in the optical complementary color hue disk 6. c As shown in equation (3):

[0078]

[0079] In equation (3), A is the minimum hue value of H0 in the sector area of ​​the camera's color hue wheel 5, and B is the maximum hue value of H0 in the sector area of ​​the camera's color hue wheel 5. c Let A be the hue value of its complementary color in optical complementary color wheel 6, and B be the hue value of its complementary color. c The complementary hue value of B in optical complementary hue wheel 6;

[0080] S5.2, The color projector 3 projects white light onto the surface of the object to be tested 4. Using the position coordinates of the highly reflective area on the surface of the object to be tested 4 in the camera pixel coordinate system obtained in step S4.4, the computer 1 extracts the color saturation value S of the color image at that position. h Then through S c =S0-S h The saturation value S of the optical complementary color was calculated. c ;

[0081] S5.3, Computer 1 generates a sinusoidal fringe grayscale image; then, using the position coordinates of the highly reflective area on the surface of the object 4 obtained in step S4.5 in the coordinate system of the projector's projected image, the hue value H of the optical complementary color obtained in step S5.1 is encoded at the same coordinate position in the sinusoidal fringe grayscale image. c And the saturation value S obtained in step S5.2 c This yields an adaptively encoded complementary color sinusoidal stripe pattern.

[0082] (6) Solving the three-dimensional morphology information of the object to be tested: Based on the adaptive coded complementary color sinusoidal fringe pattern obtained in step S5.3, the computer 1 controls the color projector 3 according to the phase shift method and the optimal three-fringe selection method to project a set of adaptive coded complementary sinusoidal fringe patterns with different number of fringe patterns and phase shift amount onto the surface of the object to be tested 4; then the CCD camera 2 acquires the deformed fringe image reflected by the surface of the object to be tested 4; after processing by the computer 1 program, the unfolded phase map is obtained; then using the conversion relationship between the absolute phase and the actual depth Z obtained in step (2), and the relationship between the pixel coordinates and XY coordinates of each pixel point in the unfolded phase map, the three-dimensional morphology data of the surface of the object to be tested 4 are obtained by substituting into the solution.

[0083] Example

[0084] In this embodiment, computer 1 is connected to a DLP color digital projector 3 of model Lightcrafter4500 via an HDMI cable, with a resolution of 912×1140 pixels; computer 1 is also connected to a CCD camera 2 of model XIQ MQ042CG-CM via a USB interface, with a resolution of 2048×2048 pixels.

[0085] The object to be tested 4 is a colored object with a highly reflective surface. According to the principle of selective absorption of light, the color projector 3 projects a set of color-coded stripes that are optically complementary to the color of the highly reflective area on the surface of the object to be tested 4. This increases the absorption of the light intensity of the light projected by the color projector 3 by the highly reflective area on the surface of the object to be tested 4, thereby reducing the intensity of the deformed stripes reflected back from the surface of the object to be tested 4 by the CCD camera 2, so that the light intensity value is within its dynamic range. The computer 1 demodulates the collected stripe information and calculates the unfolded phase. Then, the three-dimensional morphology data of the surface of the object to be tested 4 is restored by using the measurement system calibration parameters obtained in step (2).

[0086] Any aspects not covered in this invention are applicable to existing technologies.

Claims

1. A method for measuring the three-dimensional shape of a highly reflective object with adaptively encoded complementary color fringes, characterized in that, The method includes the following steps: (1) Set up the measurement system: CCD camera (2) and color projector (3) are fixed on the optical platform; the optical axis of CCD camera (2) and the optical axis of color projector (3) are on the same horizontal plane and are parallel to the optical platform; CCD camera (2), color projector (3) and the object to be measured (4) are in a triangular measurement relationship in space, and the object to be measured (4) is located within the depth of field of CCD camera (2) and color projector (3) to form a clear image; computer (1) is connected to CCD camera (2) and color projector (3) respectively. (2) Calibration of the measurement system: The calibration plate with the circular mark is placed at different calibration positions within the depth of field of the CCD camera (2) and the color projector (3) where a clear image can be formed; at each calibration position, the color projector (3) projects a sinusoidal fringe pattern onto the surface of the calibration plate, and solves the folding phase and unfolding phase of the calibration plate surface at that calibration position; at the same time, a texture image of the calibration plate is acquired at each calibration position, and the center pixel coordinates of the circular mark on the calibration plate are extracted; the conversion relationship between the absolute phase of each pixel and the actual depth Z, as well as the relationship between the pixel coordinates of each pixel and the XY coordinates, are established to obtain the system calibration parameters and complete the three-dimensional calibration of the measurement system; (3) Calibrate the color acquired by the CCD camera (2) and its optical complementary color: S3.1 Replace the calibration plate with the circular mark, place the calibration color mark card in the middle of the calibration plate in step (2), the CCD camera (2), the color projector (3) and the color mark card are in a triangular measurement relationship in space, and the color mark card is located within the depth of field of the CCD camera (2) and the color projector (3) to form a clear image; S3.2, The CCD camera (2) acquires a color image of a color within a color block in the color chart; then the computer (1) records the hue value H5 of the color within the color block acquired by the CCD camera (2), and finally calculates and generates the hue value H6 of the optical complementary color of that color as shown in equation (1): H6=H5+180°+ΔH (1) In formula (1), H6 is the hue value of the optical complementary color generated by computer (1); when H6≥360°, the hue value H6=H6-360°; H5 is the hue value of the color in the color block collected by CCD camera (2); ΔH is the hue value to compensate for the color error projected by color projector (3); S3.3 Control the color projector (3) to project the optical complementary color of the color onto the color block of the color chart; then control the CCD camera (2) to collect the light intensity grayscale image reflected back from the color block on the color chart; when the light intensity of the light intensity grayscale image of the color block collected by the CCD camera (2) reaches the minimum value, then the optical complementary color of the color projected by the color projector (3) at this time is the optical complementary color of the color in the color block on the color chart in this measurement system, and the computer (1) records the hue value of the optical complementary color projected by the color projector (3) at this time; S3.4 Repeat steps S3.2 to S3.3 until all the colors in the color blocks on the color chart have their optical complementary colors in this measurement system and all the color blocks have completed the calibration of their optical complementary colors; at the same time, obtain the hue values ​​of the colors in all the color blocks in the color chart collected by the CCD camera (2) and the hue values ​​of the optical complementary colors projected by all the corresponding color projectors (3); S3.

5. Based on the hue values ​​of all colors in the color blocks of the color chart acquired by the CCD camera (2) in step S3.4, draw radius lines with different polar angles on the H hue disk plane of the HSV color space model; then, based on the number N of color blocks in the color chart, filter the radius lines representing the hue values ​​to obtain the camera-acquired color hue disk (5). S3.

6. Based on the hue values ​​represented by each radius line in the color hue disk (5) acquired by the camera, find the hue value of the optical complementary color of the color in the corresponding color block in the color chart obtained in step S3.4; then draw the radius lines with different polar angles on the H hue disk plane of the HSV color space model to obtain the optical complementary color hue disk (6). (4) Extract the position of the highly reflective area on the surface of the object to be measured (4) in the camera pixel coordinate system and transform it to the projector projection image coordinate system: S4.1 Replace the position of the color chart in step (3) with the object to be tested (4); S4.2 The computer (1) generates an RGB-coded dot matrix map (7) with the same horizontal and vertical coordinate intervals and the high reflective area of ​​the surface of the object to be tested (4) according to the pixel size of the imaging surface of the color projector (3) and the size of the high reflective area. The map is then projected onto the surface of the object to be tested (4) via the color projector (3). The background of the RGB encoding dot matrix (7) is white light with a light intensity of 255. The RGB values ​​and number of pixels of each cross mark in the RGB encoding dot matrix (7) are different, and the RGB values ​​of different cross marks correspond one-to-one with the pixel position coordinates of the mark in the coordinate system of the projector's projected image. S4.3, CCD camera (2) acquires a color image of the surface of the object to be measured (4) covered with an RGB-coded dot matrix (7); S4.4, The computer (1) first judges the color image acquired in step S4.3 pixel by pixel, and defines each oversaturated pixel as a high reflective point on the surface of the object to be tested (4), thereby obtaining the position coordinates of the high reflective area on the surface of the object to be tested (4) in the camera pixel coordinate system; then it obtains and decodes the position coordinates and encoded RGB values ​​of the four markers that are closest to the area and form the smallest rectangle in the camera pixel coordinate system. S4.

5. Using the RGB values ​​of these four marker points, find their position coordinates in the projector's projected image coordinate system, and establish a one-to-one correspondence with the position coordinates of the four marker points obtained in step S4.4 in the camera pixel coordinate system. Then, for each oversaturated pixel in the highly reflective area in the camera pixel coordinate system, find its position coordinates (u... c ,v c Linear interpolation calculations are performed to obtain the coordinates of each point (u) in the highly reflective area under the coordinate system of the projected image. p ,v p The position coordinates of ); (5) Extract the color of the highly reflective area on the surface of the object to be tested (4) and calculate and generate an adaptively coded complementary color sinusoidal stripe pattern: S5.1, The CCD camera (2) acquires a color image of the object under test (4) under natural light without high reflectivity. Using the position coordinates of the high reflectivity area on the surface of the object under test (4) in the camera pixel coordinate system obtained in step S4.4, the computer (1) extracts the hue value H0 and saturation value S0 of the color image at that position coordinate. The camera acquires a color hue disk (5) and uses linear interpolation to perform a complementary hue lookup on the hue value H0. The corresponding optical complementary color hue value H is calculated in the optical complementary color hue disk (6). c As shown in equation (3): In equation (3), A is the minimum hue value of H0 in the sector area of ​​the camera's color hue wheel (5), and B is the maximum hue value of H0 in the sector area of ​​the camera's color hue wheel (5). c Let A be the hue value of its complementary color in the optical complementary color wheel (6), and B be the hue value of its complementary color. c Let B be the complementary hue value of B in the optical complementary hue wheel (6); S5.2, The color projector (3) projects white light onto the surface of the object to be tested (4). Using the position coordinates of the highly reflective area on the surface of the object to be tested (4) obtained in step S4.4 in the camera pixel coordinate system, the computer (1) extracts the color saturation value S of the color image at that position. h Then through S c =S0-S h The saturation value S of the optical complementary color was calculated. c ; S5.3, The computer (1) generates a sinusoidal fringe grayscale image; then, using the position coordinates of the highly reflective area on the surface of the object under test (4) obtained in step S4.5 in the coordinate system of the projector's projected image, the hue value H of the optical complementary color obtained in step S5.1 is encoded at the same coordinate position in the sinusoidal fringe grayscale image. c And the saturation value S obtained in step S5.2 c This yields an adaptively encoded complementary color sinusoidal stripe pattern. (6) Solving the three-dimensional morphology information of the object to be tested: Based on the adaptive coded complementary color sinusoidal fringe pattern obtained in step S5.3, the computer (1) controls the color projector (3) according to the phase shift method and the optimal three-fringe selection method to project a set of adaptive coded complementary sinusoidal fringe patterns with different number of fringe patterns and phase shift amount onto the surface of the object to be tested (4); then the CCD camera (2) acquires the deformed fringe image reflected by the surface of the object to be tested (4); then the computer (1) processes the image to obtain the unfolded phase map; then the conversion relationship between the absolute phase and the actual depth Z obtained in step (2) and the relationship between the pixel coordinates and XY coordinates of each pixel point in the unfolded phase map are used to solve the three-dimensional morphology data of the surface of the object to be tested (4).

2. The method for measuring the three-dimensional shape of a highly reflective object with adaptive coded complementary color fringes according to claim 1, characterized in that, In step (1), the angle between the optical axes of the CCD camera (2) and the color projector (3) is 25-30°.

3. The method for measuring the three-dimensional shape of a highly reflective object with adaptively encoded complementary color fringes according to claim 1, characterized in that, In step (2), the plane accuracy of the calibration plate is 1 μm.

4. The method for measuring the three-dimensional shape of a highly reflective object with adaptively encoded complementary color fringes according to claim 1, characterized in that, In step (2), the phase shift method is used to solve the folded phase; the optimal three-fringe selection method is used to solve the absolute phase, with the number of the three fringe groups being 100, 99, and 90 respectively.

5. The method for measuring the three-dimensional shape of a highly reflective object with adaptively encoded complementary color fringes according to claim 1, characterized in that, In step S3.5, the selection principle for the radius lines representing hue values ​​is: when the adjacent angles of different radius lines are less than 360 / N°, the median value of the polar angle of these radius lines is selected to simplify them into a single line and the redundant radius lines are discarded.

6. The method for measuring the three-dimensional shape of a highly reflective object with adaptively encoded complementary color fringes according to claim 1, characterized in that, In step S4.5, the linear interpolation calculation is shown in equation (2): In equation (2), (u c11 ,v c11 ), (u c12 ,v c12 ), (u c21 ,v c21 (u) represents the position coordinates of the three marker points (top left, top right, and bottom left) forming a rectangle in the camera pixel coordinate system; p11 ,v p11 ), (u p12 ,v p12 ), (u p21 ,v p21 ) represents the position coordinates of the three marker points (top left, top right, and bottom left) that form a rectangle in the coordinate system of the projected image.

Images