Non-contact measurement evaluation method, system and medium

Abstract

The invention provides a non-contact measurement evaluation method, a non-contact measurement evaluation system and a medium. According to the non-contact measurement evaluation method provided by the invention, according to a phase deflection imaging principle, images of different phases in an N-step phase shift method are utilized to calculate imaging brightness and contrast under different wavelength conditions; the accuracy of original information of imaging is evaluated; calculating the phase signal-to-noise ratio of each wavelength according to phase distribution calculation, and using the phase signal-to-noise ratio to evaluate the quality of the phase diagram; in addition, according to imaging evaluation and phase distribution calculation, the surface reflection type of the to-be-measured object is speculated. And integrating the data information of the pixels and the phase and the reflection type to obtain an evaluation value of the current wavelength, and determining the measurement wavelength. The evaluation method provided by the invention is simple in calculation, improves the screening efficiency of the measurement wavelength, evaluates the pixel and phase results in an omnibearing manner, optimizes the degree of adaptation between the measurement wavelength and the object to be measured, meets the complex scene requirements of phase deflection, and improves the accuracy of the phase deflection detection result.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a non-contact measurement evaluation method, system, and medium. Background Technology

[0002] Phase Measuring Deflectometry (PMD) is a high-precision technique for measuring the three-dimensional topography of mirrors / mirror-like surfaces. Its accuracy and reliability are highly dependent on the quality of the light source. In phase measuring deflectometry, LEDs are the most commonly used light source because they are low-cost, stable, and have sufficient monochromaticity.

[0003] However, existing technologies have the following drawbacks:

[0004] 1. Wavelength selection is fixed: In existing PMD measurement systems, the selection of wavelength depends on the operator's experience or prior knowledge of the material being measured, which lacks versatility and intelligence.

[0005] 2. Differences in imaging effects: Short-wavelength light sources (such as blue light) have weak diffraction effects and high spatial resolution, but are sensitive to surface roughness and prone to scattering; long-wavelength light sources (such as infrared light) have high tolerance for roughness, but lower spatial resolution. It is difficult to obtain optimal results on all surfaces with a single wavelength.

[0006] 3. Poor material adaptability: The spectral reflectance of different materials (such as metals, silicon, glass, and coatings) varies greatly. A wavelength that performs well on a metal surface may be completely unmeasurable on a silicon wafer. The system exhibits poor robustness when dealing with unknown or mixed material surfaces. Summary of the Invention

[0007] This invention proposes a non-contact measurement evaluation method, system, and medium, which solves at least one of the above-mentioned technical problems.

[0008] To achieve the above objectives, the present invention proposes the following technical solution:

[0009] An evaluation method for non-contact measurement, comprising:

[0010] Select several wavelengths and obtain the stripe image reflected by the surface of the object under test at each wavelength;

[0011] Based on the fringe images acquired by the camera, the imaging evaluation of the fringe images corresponding to different wavelengths is calculated; based on N-step phase shift, the phase signal-to-noise ratio of the fringe images corresponding to different wavelengths is calculated; based on the imaging evaluation and the phase signal-to-noise ratio, the reflection type of the surface of the object under test is evaluated, and the weighting coefficients of the imaging evaluation and the phase signal-to-noise ratio are determined respectively.

[0012] Imaging evaluation includes brightness evaluation and contrast evaluation;

[0013] Based on imaging evaluation, phase signal-to-noise ratio, and weighting coefficients, evaluation values ​​corresponding to different wavelengths are calculated to determine the measurement wavelength.

[0014] Furthermore, the brightness evaluation includes a global brightness evaluation, which calculates the mean value of the stripe images of different phases corresponding to any direction of the same wavelength as the global brightness evaluation.

[0015] Furthermore, the brightness evaluation includes local brightness evaluation. Based on the surface characterization characteristics of the object under test, a Region of Interest (ROI) is selected. The average pixel value within the ROI is calculated in the stripe image corresponding to different phases in any direction of the same wavelength, and this value is used as the local brightness evaluation.

[0016] Furthermore, contrast evaluation metrics include: the modulation value γ = (I) in any direction corresponding to the same wavelength. max -I min ) / (I max +I min );

[0017] In the formula, I max I represents the maximum pixel value of the current pixel within N phase shifts. min It is the minimum pixel value of this pixel point during N phase shifts.

[0018] Furthermore, the phase signal-to-noise ratio includes:

[0019] According to the N-step phase shift method, calculate the phase distribution of each pixel in the fringe pattern of any wavelength in any direction; set a sliding window and calculate the standard deviation of the mean phase distribution of each pixel in each window relative to the current window; use the mean standard deviation of all pixels as the global noise level estimate of the current fringe pattern; use the peak value of the phase distribution and the global noise level estimate to calculate the global phase signal-to-noise ratio of the wavelength in the current direction.

[0020] The phase distribution can be either enclosed phase or absolute phase.

[0021] The pixel range of the sliding window is the pixel row or pixel column in the same direction as the stripe pattern, and the pixels of the sliding window are the pixels corresponding to the middle area of ​​the stripe period.

[0022] Furthermore, if the phase distribution is a wrap-around phase, then the peak value of the phase distribution is 2π; if the phase distribution is an absolute phase, then the peak value of the phase distribution is the difference between the maximum and minimum absolute phases in the absolute phase diagram of the reference plane.

[0023] Furthermore, the evaluation value F_λ for any wavelength a =w1*(μ×I A +β×I ROI)+w2*γ+w3*PSNR_λ a

[0024] In the formula, λ a Let a be the wavelength, a∈N + a≥3; w1 is the weighting coefficient for brightness evaluation; w2 is the weighting coefficient for modulation value γ; w3 is the phase signal-to-noise ratio PSNR_λ a The weighting coefficient; μ is the global brightness evaluation I. A The weighting coefficient; β is the local brightness evaluation index I. ROI The weighting coefficients.

[0025] Based on the same inventive concept, this application also proposes a non-contact measurement evaluation system, comprising:

[0026] The stripe pattern generation module is used to modulate beams of different wavelengths into sinusoidal stripe patterns and project the sinusoidal stripe patterns onto the surface of the object to be measured.

[0027] The camera captures the fringe pattern reflected from the surface of the object under test at each wavelength;

[0028] The calculation module calculates the imaging evaluation of the fringe images corresponding to different wavelengths based on the fringe images acquired by the camera; calculates the phase signal-to-noise ratio of the fringe images corresponding to different wavelengths based on N-step phase shift; evaluates the reflection type of the surface of the object under test based on the imaging evaluation and phase signal-to-noise ratio, and determines the weighting coefficients of the imaging evaluation and phase signal-to-noise ratio respectively; and calculates the evaluation value corresponding to different wavelengths based on the imaging evaluation, phase signal-to-noise ratio, and weighting coefficients to determine the measurement wavelength.

[0029] Furthermore, it also includes: a stripe pattern generation module, including a light source; the light source is one or more of LED light source, display screen, and infrared light source.

[0030] On the other hand, the present invention also proposes a computer-readable storage medium storing at least one instruction or at least one program, wherein the at least one instruction or at least one program is loaded and executed by a processor to implement the method described above.

[0031] Based on the same inventive concept, this application also proposes an electronic device, comprising: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus.

[0032] Memory, used to store computer programs;

[0033] The processor implements the above method when executing programs stored in memory.

[0034] The beneficial effects of the embodiments of the present invention are as follows:

[0035] The non-contact measurement evaluation method proposed in this application, based on the imaging principle of phase deflection, utilizes images of different phases in the N-step phase shift method to calculate the brightness and contrast of the image under different wavelength conditions; this is used to evaluate the accuracy of the original imaging information; and based on the phase distribution calculation, the phase signal-to-noise ratio of each wavelength is calculated to evaluate the quality of the phase map; furthermore, based on the imaging evaluation and phase distribution calculation, the surface reflection type of the object under test is inferred; and by integrating pixel, phase data information, and reflection type, an evaluation value for the current wavelength is obtained to determine the measurement wavelength. The evaluation method proposed in this application is computationally simple, improves the efficiency of wavelength selection, and comprehensively evaluates pixel and phase results, optimizing the fit between the measurement wavelength and the object under test to meet the needs of complex phase deflection scenarios and improve the accuracy of phase deflection detection results. Attached Figure Description

[0036] Figure 1 This is a schematic diagram illustrating the principle of phase deflection;

[0037] Figure 2 This is a flowchart illustrating the non-contact measurement evaluation method proposed in this invention.

[0038] Figure 3 This is a schematic diagram of the electronic device proposed in this invention. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising”, “including”, etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0041] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0042] like Figure 1As shown, a PMD measurement system generally consists of a display screen, a camera, and the object being measured. The display screen acts as a diffuse light source, illuminating the stripe pattern onto the surface of the mirror object, while the camera captures the distorted stripe pattern modulated by the mirror surface.

[0043] Assuming the distances between the display screen, the object being measured, and the camera are known, the surface gradient information of the object can be obtained using the slope equation.

[0044] Since the light path is reversible, the light path is described in reverse order. Any ray emitted from a camera image pixel is reflected by point s on the reference plane mirror to point q on the display screen. If the angle between point s on the surface of the mirror being measured and the reference plane is θ, then the angle between the light rays sq and so emitted by the camera is 2θ.

[0045] In Δsqo, let ∠osq=α. According to the Law of Sines, there exists

[0046] If the period of the stripes on the display screen is P, then |oq| represents the phase change in the fringe pattern.

[0047] According to the above formula, we have This allows us to derive the gradient tanθ of the surface of the object under test.

[0048] Generally, if α≈90° and θ is very small, the calculation formula can be simplified to:

[0049] The simplified formula shows that the gradient information of the object under test is modulated and converted into the modulation phase of the reflection fringe. After processing with phase extraction and unfolding techniques, the phase offset in the horizontal and vertical directions corresponding to each camera pixel can be accurately obtained. Transform the phase into a gradient distribution in two perpendicular directions, tan2θ. x tan2θ y To obtain three-dimensional height distribution information, an integral algorithm or other spatial domain algorithm is used to calculate the three-dimensional surface shape of the object under test.

[0050] Based on the above measurement principle, this application proposes a non-contact measurement evaluation system, comprising:

[0051] The stripe pattern generation module is used to modulate several wavelength beams into sinusoidal stripe patterns and project the sinusoidal stripe patterns onto the surface of the object to be measured.

[0052] The stripe pattern generation module includes a light source; the light source is one or more of LED light source, display screen, and infrared light source.

[0053] Preferably, in the stripe pattern generation module of this embodiment, in order to achieve the selection of different wavelength beams, an LED light source composed of LED beads of different colors can be selected, and the color of the LED light source can be used as the wavelength selection; or a display screen can be used as the light source; in addition, an infrared light source can be added on the basis of the LED light source or the display screen as the selection of invisible light wavelength.

[0054] Preferably, this application does not limit the specific combination of light sources, and the combination of light sources can be determined in advance according to the material and color of the object to be tested.

[0055] The camera captures images of the stripes reflected from the surface of the object under test at each wavelength.

[0056] The calculation module calculates the imaging evaluation of the fringe images corresponding to different wavelengths based on the fringe images acquired by the camera; calculates the phase signal-to-noise ratio of the fringe images corresponding to different wavelengths based on N-step phase shift; evaluates the reflection type of the surface of the object under test based on the imaging evaluation and phase signal-to-noise ratio, and determines the weighting coefficients of the imaging evaluation and phase signal-to-noise ratio respectively; and calculates the evaluation value corresponding to different wavelengths based on the imaging evaluation, phase signal-to-noise ratio, and weighting coefficients to determine the measurement wavelength.

[0057] like Figure 2 As shown, based on the above evaluation system, this embodiment proposes the following method, including:

[0058] Select several wavelengths and obtain the stripe image reflected by the surface of the object under test at each wavelength.

[0059] Determine the initial wavelength of the light source based on the appearance characterization conditions of the object to be tested;

[0060] Appearance characterization conditions include the surface color of the test object, the surface reflectivity of the test object, or the type of surface reflection.

[0061] Given the surface color of the object to be tested, select a light source color that is similar in color to determine the initial wavelength. For example, if the object to be tested is an optical thin film, its color is observed to be yellow-green by the human eye. Set its initial wavelength to correspond to the wavelengths of the yellow light source and the green light source, and use these as the initial wavelengths.

[0062] Alternatively, the surface reflection type of the object to be tested is known, and there are multiple regions with different reflectivity; or the material of different regions of the surface of the object to be tested is known; select visible light and / or infrared light of similar color as the initial wavelength.

[0063] A series of specific wavelengths (λ1, λ2, ... λ) are selected in the initial band. a , a∈N + (a≥3), collect the stripe images reflected from the surface of the object under test at each wavelength.

[0064] Structured light is commonly used to add feature patterns to featureless surfaces to mark different locations on the surface. Common structured light patterns include phase-shifting fringes, Gray code, and speckle. Among them, phase-shifting fringes are the most commonly used structured light pattern in phase measurement deflection due to their high resolution and strong noise resistance.

[0065] In this embodiment, stripes with a known period are used as the structured light pattern.

[0066] Since the fringe images captured by the camera only contain light intensity information, it is necessary to convert the light intensity information into the required phase information. In PMD (Programmable Analyzer), digital phase-shifting technology is typically used to extract the phase information of the fringe pattern. This process requires phase shifting the original fringe pattern to generate multiple phase-shifted fringe images with different additional phases. Finally, the phase information of the object under test is calculated from these fringe images. A phase-shifted fringe image is a group of images in which the pixel grayscale varies sinusoidally along the row and column directions of the image.

[0067] For a standard N-step phase shift (N≥3, N∈N) + A phase-shifted fringe pattern consists of N fringe images. This embodiment employs a four-step phase-shifting method to calculate the phase information of the object under test. Specifically, four sinusoidal fringes with phases differing by 90 degrees are projected, and fringe images (I1, I2, I3, I4) corresponding to different phase fringes are acquired in both the vertical and horizontal directions. The light intensity distribution of the fringe image in any direction is as follows:

[0068]

[0069] In the formula, A represents the background light intensity, and B represents the amplitude light intensity. This represents the phase distribution to be solved, which includes the surface morphology information of the object under test.

[0070] Based on the fringe pattern acquired by the camera, the imaging evaluation of the fringe image corresponding to different wavelengths is calculated; based on N-step phase shift, the phase signal-to-noise ratio of the fringe image corresponding to different wavelengths is calculated; based on the imaging evaluation and the phase signal-to-noise ratio, the reflection type of the surface of the object under test is evaluated, and the weighting coefficients of the imaging evaluation and the phase signal-to-noise ratio are determined respectively.

[0071] Imaging evaluation includes brightness evaluation and contrast evaluation.

[0072] Based on the fringe images acquired by the camera, the phase distribution of the fringe pattern corresponding to each wavelength is calculated using N-step phase shift. Based on the phase distribution and fringe pattern, the imaging evaluation and phase pattern quality evaluation (phase signal-to-noise ratio) of the fringe images corresponding to different wavelengths are calculated to assess the reflection type of the surface of the object under test.

[0073] Brightness evaluation includes global brightness evaluation and local brightness evaluation.

[0074] Brightness evaluation includes global brightness evaluation, which involves calculating the average value of the fringe patterns of different phases corresponding to any direction at the same wavelength, as the global brightness evaluation value I. A .

[0075]

[0076] The averaged image removes stripe modulation and preserves the intrinsic reflective properties of the surface.

[0077] By calculating the pixel mean of different phase fringe patterns, the influence of light intensity of different wavelengths on the brightness of the fringe image can be reflected, serving as one of the brightness evaluation standards.

[0078] Brightness evaluation includes local brightness evaluation. Based on the surface characteristics of the object under test, the Region of Interest (ROI) is selected. The average pixel value within the ROI is calculated in the stripe image of different phases corresponding to the same wavelength in any direction, and this value is used as the local brightness evaluation.

[0079] Define the Region of Interest (ROI), calculate the average pixel value within the ROI region in stripe images of different phases corresponding to any direction of the same wavelength, and use it as a local brightness evaluation index.

[0080] Based on the surface characterization characteristics of the object to be tested, the Region of Interest (ROI) is selected, specifically including:

[0081] The ROI setting range (size) can be comprehensively set based on the size of the stripe image and hardware conditions.

[0082] The selection of ROI can be based on areas with known defects, areas with known high / low reflectivity, color transition areas, or other areas.

[0083] Preferably, multiple Regions of Interest (ROIs) can be set. If it is known that the surface of the object under test has regions of high / low reflectivity, the local brightness evaluation of the high-reflectivity and low-reflectivity regions can be calculated separately. Similarly, if the surface of the object under test has multiple colors, the ROI regions corresponding to the colors and / or the ROI regions of the color transition areas can be selected respectively. Likewise, for surfaces with obvious defects, ROIs can be selected at different locations based on the extent of the defects.

[0084] By selecting pixel values ​​of a portion of the surface of the object under test, local brightness is calculated to evaluate the influence of light intensity of different wavelengths on the brightness of the stripe image at a specific location, serving as one of the brightness evaluation criteria.

[0085] According to the quantum efficiency (QE) curve of the camera, the photoelectric conversion efficiency of the camera is different at different wavelengths, which is reflected in the different pixel values ​​in the striped image, that is, the different image brightness.

[0086] Therefore, image brightness can reveal the degree of influence of different wavelengths on the imaging of the same object under test, thereby analyzing the accuracy of subsequent phase deflection calculations. Furthermore, this application uses multiple phase images obtained through the N-step phase shift method as the basis for calculating the brightness image at that wavelength, eliminating fringe modulation, to represent the intrinsic reflection characteristics of the object's surface and considering the influence of the object's surface reflection type.

[0087] Depending on the application scenario of phase deflection, the reflection type of the object under test surface can be divided into specular reflection, mixed reflection (specular reflection + diffuse reflection), and diffuse reflection. Based on the judgment result of the reflection type of the object under test surface, the weight coefficient w1 for brightness evaluation is determined. In actual scenarios, mixed reflection is the main type.

[0088] Set a first brightness threshold and a second brightness threshold, with the first brightness threshold being greater than the second brightness threshold; the first brightness threshold is used to evaluate the overexposure of the current image.

[0089] Taking an 8-bit image as an example, the first threshold is set to 250, and the second threshold is set to 80. The values ​​of the first and second thresholds are for illustrative purposes only. The first threshold can also be set to 245, the second threshold to 90, etc. The threshold values ​​can be flexibly adjusted according to the actual image acquisition situation.

[0090] Alternatively, the specific values ​​of the first and second thresholds can be calculated by weighting the global brightness evaluation calculated from the fringe image corresponding to the shortest wavelength and the global brightness evaluation calculated from the fringe image corresponding to the longest wavelength, in order to closely approximate the actual scenario.

[0091] If both the global and local brightness evaluations calculated from the fringe image corresponding to the shortest wavelength among different wavelengths are less than the second threshold, the surface of the object under test is identified as diffuse reflection; if the global brightness evaluation calculated from the fringe image corresponding to the longest wavelength among different wavelengths is greater than the first threshold, the surface of the object under test is identified as specular reflection; otherwise, it is mixed reflection.

[0092] Furthermore, in the classification of mixed reflections, the degree of mixed reflection of the current object under test can be further determined;

[0093] If the global brightness evaluation calculated from the stripe image corresponding to the shortest wavelength among different wavelengths is less than the second threshold, the ROI region does not exceed 40% of the entire image, and the local brightness evaluation is greater than the second threshold and less than the first threshold, then the surface of the object under test is identified as a mixed reflection biased towards diffuse reflection.

[0094] If the global brightness evaluation calculated from the stripe image corresponding to the longest wavelength among different wavelengths is greater than the second threshold and less than the first threshold, the ROI area does not exceed 40% of the entire image, and the local brightness evaluation is greater than the first threshold, then the surface of the object under test is identified as a mixed reflection biased towards specular reflection.

[0095] If the local brightness evaluation and global brightness evaluation are refined by mixing the reflection types, then in the above judgment strategy, the ROI should be the brightest region in the current striped image.

[0096] Based on the comprehensive judgment of the above mixed reflection, the weighting coefficients of global brightness evaluation and local brightness evaluation in the brightness evaluation can be further determined. Where μ is the global brightness evaluation value I. A The weighting coefficient; β is the local brightness evaluation index I. ROI The weighting coefficients.

[0097] Contrast evaluation metrics include: the modulation value γ = (I) in any direction at the same wavelength. max -I min ) / (I max +I min )

[0098] In the formula, I max I represents the maximum pixel value of the current pixel within N phase shifts. min It is the minimum pixel value of this pixel point during N phase shifts.

[0099] Preferably, the pixel position used to calculate the modulation value can be selected from the transition position between the background and the stripes in the striped image, where the striped image is represented by the black and white boundary, in order to improve the accuracy of the contrast index.

[0100] Preferably, the formula for calculating the modulation value γ corresponding to any direction of the same wavelength can also be expressed as:

[0101]

[0102] In the formula, I1, I2, I3, and I4 are four stripe images with different phases obtained by the four-step phase-shifting method in the horizontal or vertical directions, respectively.

[0103] Preferably, the phase of the sinusoidal fringes can be increased, such as by projecting eight sinusoidal fringes with phases differing by 45 degrees sequentially; or by using fringe images with other phases to increase calculation accuracy. The corresponding modulation value is calculated according to the determined N-step phase shift method.

[0104] A higher γ value indicates clearer reflected fringes, a greater difference from background noise, and higher accuracy in phase calculation. Based on the determination of the surface reflection type of the object under test, the weighting coefficient w2 for fringe contrast is determined.

[0105] If the modulation value calculated from the stripe image corresponding to the longest wavelength among different wavelengths is greater than the first contrast threshold, it indicates that the surface of the object under test is specularly reflective; if it is less than the second contrast threshold, it indicates that the surface of the object under test is diffusely reflective; otherwise, it is mixed reflection. The first contrast threshold is greater than the second contrast threshold.

[0106] The value of γ is in the range of [0,1]. For example, the first contrast threshold can be set to 0.85 and the second contrast threshold can be set to 0.05. The threshold values ​​in this embodiment are just examples and can be adjusted flexibly according to the actual image acquisition situation.

[0107] Alternatively, the specific values ​​of the first contrast threshold and the second contrast threshold can be calculated by weighting the modulation values ​​calculated from the stripe images corresponding to the shortest and longest wavelengths, in order to closely approximate the actual scene.

[0108] Phase signal-to-noise ratio (SNR) includes: calculating the phase distribution of each pixel in a fringe image in any direction at any wavelength using the N-step phase-shifting method; setting a sliding window and sequentially calculating the standard deviation of the mean phase distribution of each pixel within each window relative to the current window; using the mean standard deviation of all pixels as an estimate of the global noise level of the current fringe image; and calculating the global phase SNR of the wavelength in the current direction using the peak value of the phase distribution and the global noise level estimate; wherein the phase distribution is either wrap-around phase or absolute phase.

[0109] If the phase distribution is a wrap-around phase, the peak value of the phase distribution is 2π; if the phase distribution is an absolute phase, the peak value of the phase distribution is the difference between the maximum and minimum absolute phases in the absolute phase diagram of the reference plane.

[0110] Phase signal-to-noise ratio (SNR) is used to evaluate signal quality and computational robustness.

[0111] Based on four fringe images in any direction (horizontal or vertical) under any wavelength condition, the phase distribution of any pixel (x,y) can be calculated, including the phase.

[0112]

[0113] Preferably, the phase of the sinusoidal fringes can be increased, such as by projecting eight sinusoidal fringes with phases differing by 45 degrees; or by projecting fringe images with other phases, to increase the calculation accuracy.

[0114] Based on the N-step phase shift method, the different wavelengths (λ1, λ2, ... λ) are calculated sequentially. a , a∈N + Phase distribution of pixel positions (x,y) in the stripe image corresponding to a≥3)

[0115] Preferably, the phase distribution can be a wrap-around phase to avoid calculation errors introduced by absolute phase calculations.

[0116] Preferably, the phase distribution can also be absolute phase. In the calculation of absolute phase, pixels in high-quality regions are assigned higher confidence in their phase values ​​and play a dominant role in optimization; pixels in low-quality regions are "smoothed out" or ignored. This can improve the accuracy and precision of subsequent calculations.

[0117] The modulation value of each pixel position obtained from the above contrast calculation is used as the unpacking weight of the phase wrapping and substituted into the global energy function; the global energy function is solved by minimization algorithm to obtain the absolute phase of each pixel position.

[0118] Choose either the wrap-around phase or the absolute phase as the phase distribution, which will serve as the basis for subsequent calculations.

[0119] In any striped image, set a sliding window and calculate the average phase distribution of L pixels within the window. Calculate the standard deviation of the phase distribution of pixels within each window in turn.

[0120]

[0121] In the formula, The standard deviation of the phase distribution in the M-th window is represented. This represents the phase distribution of the i-th pixel (x, y) in the M-th window; This represents the mean of the phase distribution in the Mth window.

[0122] Preferably, the pixel range of the sliding window is a pixel row or pixel column in the same direction as the stripe pattern, and the pixels of the sliding window are the pixels corresponding to the middle region of the stripe period.

[0123] Preferably, a single row (column) or multiple rows (columns) corresponding to the middle region of the stripe period can be selected as the pixel range of the sliding window.

[0124] If multiple rows (columns) are selected as the sliding window, and the pixel range of each row (column) is used as a sub-window, the standard deviation of the phase distribution of each sub-window is calculated, and the mean of the standard deviation of the phase distribution of the sub-windows is used as the standard deviation of the phase distribution of the sliding window composed of multiple rows (columns) of pixels.

[0125] The mean of all standard deviations in the fringe image This serves as an estimate of the global noise level for the graph.

[0126] If we choose the wrapping phase as the basis for calculation, since the range of phase values ​​is (-π, π], the peak value of the signal can be regarded as 2π, that is, 2π can be taken as the peak value of the phase distribution.

[0127] Global phase signal-to-noise ratio

[0128] If absolute phase is chosen as the basis for calculation, the absolute phase map of the reference plane is obtained in advance, and the difference Δref between the maximum and minimum absolute phases in the absolute phase map of the reference plane is taken as the peak value of the phase distribution.

[0129] Global phase signal-to-noise ratio

[0130] Calculate the global phase signal-to-noise ratio in the horizontal and vertical directions at the wavelength, and compare the results according to the calculation direction.

[0131] Preferably, the mean of the standard deviations of the stripe images of the same wavelength in the horizontal and vertical directions can also be obtained, and the mean of the standard deviations in different directions can be used as the standard deviation of the wavelength to calculate the global phase signal-to-noise ratio.

[0132] PSNR_λ a The higher the value, the higher the signal stability at the current wavelength.

[0133] Based on imaging evaluation, phase signal-to-noise ratio, and weighting coefficients, evaluation values ​​corresponding to different wavelengths are calculated to determine the measurement wavelength.

[0134] Based on the calculation of the evaluation factors and the strategy for determining the surface reflection type of the test object, the weight coefficient corresponding to each evaluation factor at the current wavelength can be determined, and the evaluation value at the current wavelength can be calculated.

[0135] F_λ a =w1*(μ×I A +β×I ROI )+w2*γ+w3*PSNR_λ a

[0136] In the formula, w1 is the weighting coefficient for brightness evaluation; w2 is the weighting coefficient for modulation value γ; and w3 is the phase signal-to-noise ratio (PSNR) λ. a The weighting coefficient; μ is the global brightness evaluation I. A The weighting coefficient; β is the local brightness evaluation I. ROI The weighting coefficients.

[0137] If the reflectance of the object to be measured is known, then the corresponding weight can be selected based on the reflectance.

[0138] If the surface reflectivity of the object to be measured is unknown, the surface reflection type of the object to be measured can be inferred based on the above calculation results, so as to select the corresponding weight.

[0139] Based on the difference between the global brightness evaluation and the local brightness evaluation, adjust the coefficients μ and β appropriately.

[0140] If the reflection is diffuse or specular, the brightness evaluation corresponding to specular reflection tends to be close to the pixel median. This application believes that, ideally, the pixel distribution follows a normal distribution, meaning that most pixel values ​​in a high-quality brightness image are distributed at the pixel median.

[0141] If it is mixed reflection, then adjust the coefficients μ and β according to the judgment result of the degree of mixing or the known reflectivity partitioning of the surface of the object to be tested; if the reflection type of the surface of the object to be tested is biased towards diffuse reflection, then make (μ×I A +β×I ROI ) Not greater than I A If the reflection type of the surface of the object being tested is biased towards specular reflection, then (μ×I) A +β×I ROI Not less than I A The evaluation value of the current striped image is the equal brightness evaluation value.

[0142] For test objects with specular reflection, the focus is on the impact of contrast evaluation (modulation value) on the final evaluation value, while the influence of brightness evaluation in the evaluation function is reduced.

[0143] In phase deflection applications, the quality of the phase map and its computational robustness directly affect the accuracy of the final 3D reconstruction or defect identification.

[0144] For the evaluation function (i.e. the formula for calculating the evaluation value) of fringe images of different wavelengths, the quality evaluation of the phase image (i.e., the phase signal-to-noise ratio) is as important as the imaging evaluation. If the imaging evaluation of the currently selected band tends to be consistent, the weight of the phase image quality evaluation can be increased in order to select a measurement wavelength that is conducive to high-precision calculation.

[0145] Preferably, the evaluation value of the stripe image corresponding to each wavelength can be calculated sequentially in the horizontal and vertical directions, and a wavelength with stable performance can be selected as the measurement wavelength based on the evaluation values ​​of different wavelengths in different directions.

[0146] Preferably, the average value of each evaluation factor in the horizontal and vertical directions can be calculated as the evaluation factor for the current wavelength to calculate the final evaluation value; and the measurement wavelength can be determined based on the final evaluation value.

[0147] This application also provides an electronic device, such as... Figure 3 As shown, it includes a processor 301, a communication interface 302, a memory 303, and a communication bus 304, wherein the processor 301, the communication interface 302, and the memory 303 communicate with each other through the communication bus 304.

[0148] Memory 303 is used to store computer programs;

[0149] The processor 301 implements the above method when executing the program stored in the memory 303.

[0150] Based on the same inventive concept, this application also proposes a computer-readable storage medium storing at least one instruction or at least one program, which is loaded and executed by a processor to implement the method described above.

[0151] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0152] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A non-contact measurement evaluation method, characterized in that, include: Select several wavelengths and obtain the stripe image reflected by the surface of the object under test at each wavelength; Based on the fringe images acquired by the camera, the imaging evaluation of the fringe images corresponding to different wavelengths is calculated; based on N-step phase shift, the phase signal-to-noise ratio of the fringe images corresponding to different wavelengths is calculated; based on the imaging evaluation and phase signal-to-noise ratio, the reflection type of the surface of the object under test is evaluated, and the weighting coefficients of the imaging evaluation and phase signal-to-noise ratio are determined respectively. Imaging evaluation includes brightness evaluation and contrast evaluation; Based on imaging evaluation, phase signal-to-noise ratio, and weighting coefficients, evaluation values ​​corresponding to different wavelengths are calculated to determine the measurement wavelength.

2. The evaluation method according to claim 1, characterized in that, Brightness evaluation includes global brightness evaluation, which calculates the mean value of the stripe images of different phases corresponding to any direction of the same wavelength as the global brightness evaluation.

3. The evaluation method according to claim 1, characterized in that, Brightness evaluation includes local brightness evaluation. Based on the surface characteristics of the object under test, a Region of Interest (ROI) is selected. The average pixel value within the ROI is calculated in the stripe image corresponding to different phases of the same wavelength in any direction, and this is used as the local brightness evaluation.

4. The evaluation method according to claim 1, characterized in that, Contrast evaluation indexes include: modulation value γ = (I max -I min ) / (I max +I min ) corresponding to the same wavelength in any direction; In the formula, I max is the maximum pixel value of the current pixel point in N-step phase shift; I min is the minimum pixel value of the pixel point in N-step phase shift.

5. The evaluation method according to claim 1, characterized in that, Phase signal-to-noise ratio, including: According to the N-step phase shift method, calculate the phase distribution of each pixel in the fringe pattern of any wavelength in any direction; set a sliding window and calculate the standard deviation of the mean phase distribution of each pixel in each window relative to the current window; use the mean standard deviation of all pixels as the global noise level estimate of the current fringe pattern; use the peak value of the phase distribution and the global noise level estimate to calculate the global phase signal-to-noise ratio of the wavelength in the current direction. The phase distribution can be either enclosed phase or absolute phase. The pixel range of the sliding window is the pixel row or pixel column in the same direction as the stripe pattern, and the pixels of the sliding window are the pixels corresponding to the middle area of ​​the stripe period.

6. The evaluation method according to claim 5, characterized in that, include: If the phase distribution is a wrap-around phase, then the peak value of the phase distribution is 2π; If the phase distribution is absolute phase, the peak value of the phase distribution is the difference between the maximum and minimum absolute phases in the absolute phase diagram of the reference plane.

7. The evaluation method according to claim 1, characterized in that, Evaluation value of any wavelength F_λ a = w1 * (μ * I A + β * I ROI ) + w2 * γ + w3 * PSNR_λ a In the formula, λ a Let a be the wavelength, a∈N + a≥3; w1 is the weighting coefficient for brightness evaluation; w2 is the weighting coefficient for modulation value γ; w3 is the phase signal-to-noise ratio PSNR_λ a The weighting coefficient; μ is the global brightness evaluation I. A The weighting coefficient; β is the local brightness evaluation index I. ROI The weighting coefficients.

8. A non-contact measurement evaluation system, characterized in that, include: The stripe pattern generation module is used to modulate several wavelength beams into sinusoidal stripe patterns and project the sinusoidal stripe patterns onto the surface of the object to be measured. The camera captures images of the stripes reflected from the surface of the object under test at each wavelength. The calculation module calculates the imaging evaluation of the fringe images corresponding to different wavelengths based on the fringe images acquired by the camera; calculates the phase signal-to-noise ratio of the fringe images corresponding to different wavelengths based on N-step phase shift; evaluates the reflection type of the surface of the object under test based on the imaging evaluation and phase signal-to-noise ratio, and determines the weighting coefficients of the imaging evaluation and phase signal-to-noise ratio respectively; and calculates the evaluation value corresponding to different wavelengths based on the imaging evaluation, phase signal-to-noise ratio, and weighting coefficients to determine the measurement wavelength.

9. The evaluation system according to claim 8, characterized in that, include: The stripe pattern generation module includes a light source; the light source is one or more of LED light source, display screen, and infrared light source.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction or at least one program, which is loaded and executed by a processor to implement the method as described in any one of claims 1-7.

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