CN116609334A - Nonlinear error compensation method based on phase deviation surface detection system - Google Patents

Nonlinear error compensation method based on phase deviation surface detection system Download PDF

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CN116609334A
CN116609334A CN202310170272.5A CN202310170272A CN116609334A CN 116609334 A CN116609334 A CN 116609334A CN 202310170272 A CN202310170272 A CN 202310170272A CN 116609334 A CN116609334 A CN 116609334A
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screen
curve
gamma
camera
gray
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王熙
黄蒸
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Shanghai Shenghuang Optical Technology Co ltd
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Shanghai Shenghuang Optical Technology Co ltd
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    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G3/00—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes
    • G09G3/20—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/55—Specular reflectivity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2320/00—Control of display operating conditions
    • G09G2320/02—Improving the quality of display appearance
    • G09G2320/0271—Adjustment of the gradation levels within the range of the gradation scale, e.g. by redistribution or clipping
    • G09G2320/0276—Adjustment of the gradation levels within the range of the gradation scale, e.g. by redistribution or clipping for the purpose of adaptation to the characteristics of a display device, i.e. gamma correction
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2380/00—Specific applications
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E30/00—Energy generation of nuclear origin
    • Y02E30/30—Nuclear fission reactors

Abstract

The invention discloses a nonlinear error compensation method based on a phase deflection surface detection system, which comprises the following steps: s2, acquiring imaging data of a camera when a screen displays three-channel white light images with different gray scales, acquiring a relation curve between the display gray scales of the screen and the imaging gray scales of the camera from the imaging data of the camera, acquiring a screen Gamma parameter according to the type of the curve, and judging whether the curve meets the Gamma curve or not so as to acquire an accurate Gamma parameter or an approximate Gamma parameter; s3, applying the screen Gamma parameter obtained in the step S2 to a structured light imaging compensation process of the phase deflection system. The invention effectively reduces the errors introduced by the nonlinearity of the screen and the camera in the process from the stripe generation to the shooting of the surface image of the object to be detected, the compensated structured light intensity curve is more similar to an ideal sinusoidal curve, the accuracy of a phase deflection detection system is improved, and the noise of the grid shape in the detection output gray level diagram can be effectively restrained.

Description

Nonlinear error compensation method based on phase deviation surface detection system
Technical Field
The invention belongs to the technical field of machine vision, and particularly relates to a nonlinear error compensation method based on a phase deflection surface detection system.
Background
The phase deviation surface detection is to calculate the phase by using a fringe pattern of a screen projected frames with a certain phase difference from each other, and detect defects based on the phase information. The stripes are displayed through a screen and projected onto the surface of an object to be detected, stripe information on the surface of the object to be detected is acquired by a camera, the light intensity projected by the screen and the gray value in the screen are in a nonlinear relation, the light intensity of the object to be detected after reflection is influenced by the surface reflectivity and the ambient light, and finally the response of the camera to the reflected light intensity is nonlinear; errors in the screen and camera are introduced from the fringe generation to the capture of the surface image, and these errors can have an impact on the final detection; the general method for eliminating the nonlinear error of the system is to increase the number of steps of the stripe phase and improve the quality of the stripe; increasing the number of fringe phase steps affects the real-time performance in industrial applications, and therefore, a method for improving fringe quality is generally employed.
The entire imaging process of the phase-shift surface detection system is shown in fig. 12, the coded structured light is:
wherein A (X, y) is the intensity of the background light, B (X, y)/A (X, y) is the fringe contrast, X (X, y) is the pixel coordinates, T is the structured photoperiod, delta n Is the phase shift magnitude.
After the structured light is displayed through the actual response function of the screen, the output light intensity is expressed as:
wherein gamma is s Is the Gamma non-linear value of the screen. The common LCD screen can be subjected to unified Gamma correction before leaving the factory to enable the photoelectric characteristic of the LCD screen to be in accordance with the visual characteristic of human eyes sensitive to dark field change, so that the LCD screen has similar visual effect, namely similar Gamma response. Secondly, since the phase deflection system uses white light to display the structural light image, and the white light of the screen is formed by overlapping red, green and blue three-color light, the light intensity variation of the three-channel output light can influence the light intensity variation of the final output white light.
The structured light reflected by the object to be measured is expressed as:
wherein R (x, y) is the reflectivity of the object to be measured. Since the camera is focused on the surface of the object to be measured, the stripe projected by the screen is blurred by an approximate gaussian with respect to the structured light in an out-of-focus state.
The final CCD camera obtains the structured light as follows:
where K is the proportionality coefficient and A is a constant.
According to the above process, it can be seen that the structural light original data undergoes three-channel mixing on the screen, nonlinear response on the screen and nonlinear response of the camera at least twice, and nonlinear errors are introduced to the subsequent phase calculation of the detection, so that the nonlinearity of the process needs to be processed.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a nonlinear error compensation method based on a phase deflection surface detection system, which is used for eliminating errors caused by a screen and a camera and ensuring the accuracy of a detection result.
The technical scheme adopted for solving the technical problems is as follows: a nonlinear error compensation method based on a phase-shift surface detection system, comprising:
acquiring imaging data of a camera when a screen displays white light images with different gray scales and three channels, acquiring a relation curve between the display gray scales of the screen and the imaging gray scales of the camera according to the imaging data of the camera, acquiring a screen Gamma parameter according to the curve type, and judging whether the curve meets the Gamma curve or not so as to acquire an accurate Gamma parameter or an approximate Gamma parameter;
and applying the obtained screen Gamma parameter to a structured light imaging compensation process of the phase deflection system.
Further, in the step of obtaining the accurate Gamma parameter or the approximate Gamma parameter, when the Gamma curve is satisfied, obtaining the accurate Gamma parameter with the minimum error through the Gamma curve with different parameters and the error summation of the collected curve; when the curve does not meet the Gamma curve, polynomial fitting is firstly carried out on the curve, and then the data obtained by polynomial root finding is fitted to a power function to obtain the approximate Gamma parameter.
Further, the step of obtaining the accurate Gamma parameter or the approximate Gamma parameter comprises,
s21, placing a mirror surface to a detection area, enabling a camera to focus on the surface of the mirror surface, setting a screen to display a series of white light images with gray values such as full images, wherein the gray value range is 0-255, the gray value difference of adjacent frames is grayDiff, and controlling the camera to acquire the white light images reflected by the mirror surface;
s22 to shot count image Calculating the average gray value of pixels of the region which is positioned in the center of the image and has the size of winSize multiplied by winSize to obtain count image The discrete gray average value data are used for obtaining a relation curve between a screen display gray value and a gray value of an image actually acquired by the camera;
s23 displaying gray values gray according to the screen screen GrayMean, which is the gray value of the image actually acquired by the camera camera The type of the relation curve between the two parameters acquires the screen Gamma parameter.
Further, in the step S23, when the curve meets the Gamma curve, searching for the accurate Gamma parameter based on the error value, first, normalizing the original curve, and displaying gray value of the original screen as gray value screen The mean value of the central area of the screen imaged by the original camera is grayMean camera Normalized norm Gray screen With a norm GrayMean camera The relation between them approximately corresponds to a power function camera (i)＝normGray screen (i) gamma ；
And secondly, carrying out Gamma parameter search based on the normalized data.
Further, the second step includes,
coarse search, walk through to a start A is the starting point end For the end point, the step length is a step A series of parameters a, a list of E (a) is obtained, and two values a with the minimum E (a) are obtained left And a right ；
Fine search, at a left And a right Calculate a continuously mid ＝(a left -a right ) 2 and E (a) right )、E(a mid )、E(a left ) When |E (a right )-E(a mid )|＜|E(a left )-E(a mid ) Time order a left ＝a mid Otherwise let a right ＝a mid The method comprises the steps of carrying out a first treatment on the surface of the Until the search interval meets the target precision a right -a left ＜accuracy target Return to time a mid As a searched Gamma value Gamma search The Gamma value of the screen is Gamma screen ＝gamma search 。
Further, in step S23, when the curve does not satisfy the Gamma curve trend, performing approximate solution by using polynomial curve fitting, obtaining a gray value displayed on the screen when the average value of the central area of the camera acquired image is equal to the target gray value by using polynomial function root after fitting, and obtaining an approximate Gamma value Gamma of the screen by fitting the power function to the obtained scattered points fit The following are provided:
further, the step of applying the obtained screen Gamma parameter to the structured light imaging compensation of the phase deviation system includes the steps of screen In the form of (2) compensating the gray value displayed by the screen to obtain a nonlinear compensated gray value CorrectGray screen The formula is as follows:
further, the method further comprises the step of adjusting screen parameters, wherein the relation curve between the display gray level of three channels of the screen R, G, B and the imaging gray level of the camera is required to be adjusted in advance, imaging data of the R, G, B three channels of the screen in different gray level values are acquired respectively, the relation curve between the display gray level of three channels of the screen R, G, B and the imaging gray level of the camera is acquired according to the imaging data of the camera, the difference between the three channels of the screen R, G, B is enabled to be minimum, and the RGB color parameters and the contrast parameters of the screen are adjusted, so that the three channels of white light intensity output curve of the screen display is close to the Gamma curve.
The invention firstly adjusts three channel output parameters of a screen RGB to reduce the influence of the three channel output difference of the screen on the light intensity of the output white light, and compensates the nonlinearity introduced by the screen and the camera based on mirror imaging.
The beneficial effects of the invention are as follows: the method effectively reduces errors introduced by nonlinearity of a screen and a camera in the process from stripe generation to shooting of the surface image of the object to be detected, the compensated structured light intensity curve is closer to an ideal sinusoidal curve, the accuracy of a phase deflection detection system is improved, and the noise of grid shapes in the detection output gray level diagram can be effectively restrained.
Drawings
FIG. 1 is a schematic diagram of a phase deviation surface detection system according to the present invention.
Fig. 2 is a graph of the intensity change of the RGB single channel and three channel mixed when r=50, g=43, and b=52, and contrast 50.
Fig. 3 shows the light intensity variation curves of the RGB single channel and three channel mixed when r=50, g=43, and b=52, and contrast ratio 75.
Fig. 4 is an original image acquired by the present invention.
Fig. 5 is a structured light imaging result before compensation.
Fig. 6 is a compensated structured light imaging result.
Fig. 7 is a three-dimensional view of structured light gray scale before compensation.
Fig. 8 is a three-dimensional view of the compensated structured light gray scale.
Fig. 9 shows the gray scale variation curve of a certain line of the structured light original before and after compensation.
FIG. 10 shows the gray scale image output of the phase deviation system before compensation.
FIG. 11 is a gray scale image output of the compensated phase deviation system.
Fig. 12 is a schematic diagram of the whole imaging process of the phase deviation surface detection system in the background art.
Detailed Description
In order to make the present invention better understood by those skilled in the art, the following description will make clear and complete descriptions of the technical solutions of the embodiments of the present invention with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
The invention discloses a nonlinear error compensation method based on a phase deflection surface detection system, which comprises the following steps:
as shown in fig. 1, a phase deflection surface detection system is installed, a mirror is placed in a detection area, a camera is focused on the mirror surface, and camera exposure is adjusted so that the camera imaging does not overexposure when a gray 255 image is displayed on the screen.
S1, respectively acquiring imaging data of R, G, B three channels of a screen at different gray values, acquiring a relation curve of three channel display gray scales of the screen R, G, B and camera imaging gray scales according to the imaging data of a camera, and adjusting a screen RGB color parameter and a contrast parameter to enable a three channel white light intensity output curve displayed by the screen to be close to a Gamma curve;
specifically, in the step S3, firstly, the screen cannot ensure that three primary colors have the same photoelectric conversion curve, and by independently adjusting the characteristics of the RGB channels, the difference of the RGB three-channel output curve is smaller, and the Gamma value is closer, so that the change of the white light intensity caused by mixing of the RGB three channels is avoided to a certain extent from deviating from the Gamma curve; when the color parameters r=50, g=43, and b=52 are obtained by adjusting the test screen AOC20E1H, the RGB three-channel brightness change curves are closest, as shown in fig. 2.
Secondly, when obvious segmentation appears on the screen curve, whether the brightness output of RGB three channels is saturated or not needs to be checked respectively; the screen contrast is adjusted to prevent saturation of the RGB three-channel curve, so that the segmentation phenomenon of the white light curve obtained by mixing the RGB three channels is avoided; as shown in fig. 3, when the color parameters r=50, g=43, b=52 and the contrast ratio is 75, the output brightness saturation phenomenon occurs in both the B channel and the R channel, and the output segment is further generated to the final three-channel white light R50G43B 52; in contrast, in fig. 2, when the contrast is 50, the output of the R, G, B three-channel curve is close and no saturation occurs, and the output of the three-channel white light R50G43B52 is not segmented.
S2, acquiring imaging data of a camera when the screen displays white light images with different gray scales and three channels by using a screen after the parameters are adjusted, acquiring a screen Gamma parameter according to a relation curve of the display gray scales of the screen and the imaging gray scales of the camera, and judging whether the curve meets the Gamma curve or not so as to acquire the accurate Gamma parameter or the approximate Gamma parameter;
specifically, in the step S2, when the curve meets the Gamma curve, obtaining the accurate Gamma parameter with the minimum error through the sum of the errors of the Gamma curves with different parameters and the acquired curve; when the curve does not meet the Gamma curve, performing polynomial fitting on the curve, and obtaining approximate Gamma parameters by fitting a power function on data obtained by solving the root of the polynomial;
more specifically, the step S2 comprises the following substeps,
s21, placing a mirror surface to a detection area, enabling a camera to focus on the surface of the mirror surface, setting a screen to display a series of white light images with gray values such as full images (three-channel gray values are equal), wherein the gray value range is 0-255, the gray value difference of adjacent frames is grayDiff, and controlling the camera to acquire a series of white light images reflected by the mirror surface; in this embodiment, the mirror is a coated mirror, the gray value difference graydiff=1 between adjacent frames, and the number of collected images count image Related to the adjacent frame gray value difference grayDiff:
s22 to shot count image Zhang TuCalculating the average gray value of pixels of the region which is positioned in the center of the image and has the size of winSize multiplied by winSize to obtain count image The discrete gray average value data are used for obtaining a relation curve between a screen display gray value and a gray value of an image actually acquired by a camera; in this embodiment, the grayDiff is 1, and the number of acquired images is 256. From the center of the 256 images captured, the calculated average gray value of the winsize=300 small area is taken, and 256 pieces of discrete gray average data are obtained, which are 256 Zhang Chunse images with gray values from 0 to 255 controlled to be displayed on the screen, and imaging results of all 256 images captured by the camera are controlled, as shown in fig. 4.
S23 displaying gray values gray according to the screen screen GrayMean, which is the gray value of the image actually acquired by the camera camera The type of the relation curve between the two is used for selecting a screen Gamma parameter fitting mode;
in the step S23, when the curve meets the Gamma curve, searching for an accurate Gamma parameter based on the error value; firstly, normalizing an original curve, wherein the gray value of the original screen display is gray screen The mean value of the central area of the screen imaged by the original camera is grayMean camera Normalized norm Gray screen With a norm GrayMean camera The relation between them approximately corresponds to a power function camera (i)＝normGray screen (i) gamma ；
Specifically, the normalization formula is:
normalized norm Gray screen With a norm GrayMean camera The relation between them approximately corresponds to a power function camera (i)＝normGray screen (i) gamma Let the power function y=x that the screen satisfies a The parameter a is an unknown, and the error expression is as follows:
i epsilon [0,255]
ln(normGray screen (i) a -normGray screen (i) gamma )＝(a-gamma)ln(normGray screen (i) Monotonous, can get E (a) monotonously increases with |a-gamma|; therefore, the value of a can be searched according to the variation of E (a) to find the optimal value of a.
The second step of searching for accurate Gamma parameters based on the error value is to search for Gamma parameters based on normalized data, perform coarse search, and traverse to obtain a start A is the starting point end For the end point, the step length is a step A series of parameters a, a list of E (a) is obtained, two values a are obtained which minimize E (a) left And a right The method comprises the steps of carrying out a first treatment on the surface of the Fine search, at a left And a right Calculate a continuously mid ＝(a left -a right ) 2 and E (a) right )、E(a mid )、E(a left ) When |E (a right )-E(a mid )|＜|E(a left )-E(a mid ) Time order a left ＝a mid Otherwise let a right ＝a mid The method comprises the steps of carrying out a first treatment on the surface of the Until the search interval meets the target precision a right -a left ＜accuracy target Return to time a mid As a searched Gamma value Gamma search The Gamma value of the screen is Gamma screen ＝gamma search . In this embodiment, walk a start ＝0.1，a end ＝2.9，a step A series of a values when=0.1, and accuracy target =0.01. Step a step The smaller the coarse search is, the longer the time consumption of the coarse search is, and the obtained fine search interval is more accurate;
in the step S23, when the curve does not satisfy the Gamma curve trend, a polynomial curve fitting is used to perform an approximate solution, a second order polynomial is generally used to perform fitting, a polynomial function is used to root after fitting to obtain a gray value displayed on the screen when the average value of the central area of the camera-captured image is equal to the target gray value, and a series of obtained scattered point fitting exponentiation functions are used to obtain an approximate Gamma value Gamma of the screen fit The following are provided:
this parameter can compensate for the majority of the non-linear portion of the curve.
S3, applying the screen Gamma parameter obtained in S2 to a structured light imaging compensation process of the phase deflection system. According to the screen Gamma parameter Gamma obtained in the step S2 screen In the form of (2) compensating the gray value displayed by the screen to obtain a nonlinear compensated gray value CorrectGray screen The formula is as follows:
CorrectGrayMean based on compensated gray value photographing camera And CorrectGray screen In an approximately linear relationship, then uses CorrectGray screen The generated structured light compensates nonlinear influence, and better detection effect can be obtained by detecting the generated structured light after compensation.
As shown in fig. 5 and fig. 6, comparing the structure light imaging results before and after compensation, it can be seen that the light intensity variation of the structure light before compensation has deviated from sine seriously, the widths of the black stripes and the white stripes are unequal and the difference is larger, and the widths of the black stripes and the white stripes after compensation are approximately equal; the more visual gray scale variation trend can be seen by combining fig. 7 and 8, wherein the gray list0 and gray list1 curves in fig. 9 are the gray scale variation curves of the pixels in the same row in fig. 5 and 6, respectively, and the gray list curves are ideal sinusoidal curves with the same period, and the light intensity curves of the compensated structured light can be seen to be more approximate to the ideal sinusoidal curves.
As can be seen from the detection output gray level diagrams 10 and 11 before and after compensation, the image before uncorrected has obvious periodic grids due to the deviation of the structured light image from the ideal sinusoidal curve, and the periodic grids of the corrected image are obviously weakened, which indicates that the compensation can suppress the grid-shaped noise in the detection output gray level diagram.
The foregoing detailed description is provided to illustrate the present invention and not to limit the invention, and any modifications and changes made to the present invention within the spirit of the present invention and the scope of the appended claims fall within the scope of the present invention.

Claims (8)

1. A nonlinear error compensation method based on a phase-shift surface detection system, comprising:
acquiring imaging data of a camera when a screen displays white light images with different gray scales and three channels, acquiring a relation curve between the display gray scales of the screen and the imaging gray scales of the camera according to the imaging data of the camera, acquiring a screen Gamma parameter according to the curve type, and judging whether the curve meets the Gamma curve or not so as to acquire an accurate Gamma parameter or an approximate Gamma parameter;
and applying the obtained screen Gamma parameter to a structured light imaging compensation process of the phase deflection system.
2. The nonlinear error compensation method based on the phase deviation surface detection system according to claim 1, wherein: in the step of obtaining the accurate Gamma parameter or the approximate Gamma parameter, when the Gamma curve is satisfied, obtaining the accurate Gamma parameter with the minimum error through the Gamma curve with different parameters and the error summation of the collected curve; when the curve does not meet the Gamma curve, polynomial fitting is firstly carried out on the curve, and then the data obtained by polynomial root finding is fitted to a power function to obtain the approximate Gamma parameter.
3. The nonlinear error compensation method based on the phase deviation surface detection system according to claim 1 or 2, characterized in that: the step of obtaining the accurate Gamma parameter or the approximate Gamma parameter comprises,
s21, placing a mirror surface to a detection area, enabling a camera to focus on the surface of the mirror surface, setting a screen to display a series of white light images with gray values such as full images, wherein the gray value range is 0-255, the gray value difference of adjacent frames is grayDiff, and controlling the camera to acquire the white light images reflected by the mirror surface;
s22 to shot count image Calculating the average gray value of pixels of the region which is positioned in the center of the image and has the size of winSize multiplied by winSize to obtain count image The discrete gray average value data are used for obtaining a relation curve between a screen display gray value and a gray value of an image actually acquired by the camera;
s23 displaying gray values gray according to the screen screen GrayMean, which is the gray value of the image actually acquired by the camera camera The type of the relation curve between the two parameters acquires the screen Gamma parameter.
4. A method of compensating for nonlinear errors based on a phase-deflecting surface detecting system as set forth in claim 3, wherein: in the step S23, when the curve satisfies the Gamma curve, searching for the accurate Gamma parameter based on the error value, and in the first step, normalizing the original curve, wherein the gray value of the original screen display is gray screen The mean value of the central area of the screen imaged by the original camera is grayMean camera Normalized norm Gray screen With a norm GrayMean camera The relation between them approximately corresponds to a power function camera (i)＝normGray screen (i) gamma ；
And secondly, carrying out Gamma parameter search based on the normalized data.
5. The method for compensating for nonlinear errors based on a phase-shift surface detection system as recited in claim 4, wherein: the second step may comprise the steps of,
coarse search, walk through to a start A is the starting point end For the end point, the step length is a step A series of parameters a, a list of E (a) is obtained, and two values a with the minimum E (a) are obtained left And a right ；
Fine search, at a left And a right Calculate a continuously mid ＝(a left -a right ) 2 and E (a) right )、E(a mid )、E(a left ) When |E (a right )-E(a mid )|＜|E(a left )-E(a mid ) Time order a left ＝a mid Otherwise let a right ＝a mid The method comprises the steps of carrying out a first treatment on the surface of the Until the search interval meets the target precision a right -a left ＜accuracy target Return to time a mid As a searched Gamma value Gamma search The Gamma value of the screen is Gamma screen ＝gamma search 。
6. A method of compensating for nonlinear errors based on a phase-deflecting surface detecting system as set forth in claim 3, wherein: in the step S23, when the curve does not satisfy the Gamma curve trend, performing approximate solution by using polynomial curve fitting, obtaining a gray value displayed on the screen when the average value of the central area of the camera-collected image is equal to the target gray value by taking root of the polynomial function after fitting, and obtaining an approximate Gamma value Gamma of the screen by fitting the obtained scattered points with an exponentiation function fit The following are provided:
7. a method of compensating for nonlinear errors based on a phase-deflecting surface detecting system as set forth in claim 3, wherein: the step of the structured light imaging compensation process for applying the obtained screen Gamma parameters to the phase deflection system comprises the steps of screen In the form of (2) compensating the gray value displayed by the screen to obtain a nonlinear compensated gray value CorrectGray screen The formula is as follows:
8. the nonlinear error compensation method based on the phase deviation surface detection system according to claim 1, wherein: the method further comprises the step of adjusting screen parameters, wherein the relation curve between the display gray level of three channels of the screen R, G, B and the imaging gray level of the camera is adjusted in advance, imaging data of the R, G, B three channels of the screen in different gray level values are acquired respectively, the relation curve between the display gray level of three channels of the screen R, G, B and the imaging gray level of the camera is acquired according to the imaging data of the camera, the difference between the three channels of the screen R, G, B is minimized, and the RGB color parameters and the contrast parameters of the screen are adjusted, so that the three channels of white light intensity output curve displayed by the screen is close to the Gamma curve.
CN202310170272.5A 2023-02-27 2023-02-27 Nonlinear error compensation method based on phase deviation surface detection system Pending CN116609334A (en)

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