Non-contact measurement method and system for center-to-center distance of optical surface in lens

Abstract

The invention relates to the technical field of center-to-center distance measurement, and particularly discloses a non-contact measurement method and system for the center-to-center distance of an optical surface in a lens. The method comprises the following steps: step S1, carrying out image acquisition on the optical surface of a to-be-measured lens; step S2, carrying out preprocessing on the image of the optical surface; step S3, carrying out feature extraction on the image of the optical surface; step S4, constructing an image three-dimensional surface model; performing error correction on the center distance; and S8, performing man-machine interaction. An image processing technology is adopted, through image acquisition, preprocessing, feature extraction and image three-dimensional surface model construction, center point coordinate determination, optical surface center distance calculation and error correction, measurement accuracy is improved, a non-contact measurement method is adopted, and potential damage to the optical surface is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of center distance measurement, and in particular to a non-contact measurement method and system for the center distance of optical surfaces in a lens. Background Art

[0002] In the field of optics, the center distance of the optical surfaces of a lens (also called air distance or optical distance) is one of the key parameters that affect lens performance. Accurate measurement of the center distance of the optical surfaces is essential to ensure the imaging quality, focusing performance, and overall optical performance of the lens.

[0003] The center distance of optical surfaces usually refers to the distance between the center points of the optical element surfaces in the lens. Specifically, it can be the distance between the center points of the front and back surfaces of an optical element (i.e., the center thickness of the element), or it can be the air gap between two adjacent optical elements, such as the distance from the center of the back surface of the first optical element to the center of the front surface of the second optical element.

[0004] Traditional non-contact measurement methods for the center distance of optical surfaces in lenses include mechanical contact measurement, interferometry, and laser scanning. Mechanical contact measurement uses tools such as mechanical probes or micrometers to directly contact the optical surface for measurement. This method may cause damage to the optical surface, especially on optical components with high precision and extremely high surface quality requirements. In addition, contact force may cause measurement errors. Interferometry is to measure the shape and position of the optical surface through an interferometer, thereby indirectly calculating the center distance. Although this method has high measurement accuracy, the equipment cost is high, the operation is complicated, and the environmental conditions (such as temperature and vibration) are strict. The laser scanning method uses laser scanning technology to measure the position of the optical surface, but this method may be affected by the uneven reflectivity of the optical component surface, resulting in inaccurate measurement results. Traditional methods are also unable to correct errors in the measurement results and cannot guarantee the accuracy of the measurement. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a non-contact measurement method and system for the center distance between optical surfaces in a lens, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a non-contact measurement method for the center distance of optical surfaces in a lens, comprising the following steps: step S1: collecting images of the optical surface of the lens to be measured, step S2: preprocessing the optical surface image, step S3: extracting features of the optical surface image, step S4: constructing a three-dimensional surface model of the image, step S5: determining the coordinates of the center points of the optical surface, step S6: calculating the center distance of the optical surface, step S7: performing error correction on the center distance, and step S8: performing human-computer interaction.

[0007] Step S1: Capturing an image of the optical surface of the lens to be tested: using a high-resolution camera to capture an image of the optical surface of the lens to be tested; Step S2: preprocessing the optical surface image: preprocessing the optical surface image of the lens to be tested collected in step S1; Step S3: extracting features of the optical surface image: extracting feature points or feature lines of the optical surface from the pre-processed image using image processing software; Step S4: constructing a three-dimensional surface model of the image: generating three-dimensional point cloud data of the lens to be tested by using a three-dimensional reconstruction algorithm according to the extracted feature points or feature lines, wherein the three-dimensional point cloud data includes the three-dimensional shape and position information of the optical surface, and obtaining a three-dimensional surface model by performing surface fitting on the point cloud data; Step S5: Determine the coordinates of the center point of the optical surface: construct the three-dimensional surface model of the image according to the step S4, and determine the coordinates of the center point of the optical surface; Step S6: Calculate the center distance of the optical surface: Calculate the center distance of the optical surface in the lens according to the coordinates of the center points of the optical surface determined in step S5; Step S7: performing error correction on the center distance: performing multiple verifications on the center distance of the optical surface in the lens calculated in step S6 and performing error correction; Step S8: Perform human-computer interaction: used to establish a user interface to visualize the measurement results, verification reports, and error correction results on a mobile device for personnel reference.

[0008] Preferably, the mathematical model for denoising the optical surface image in step S2 is specifically expressed as: , where I(x0, y0) represents the pixel value of the filtered image at position (x0, y0), and M represents the total number of pixels in the neighborhood. For a filtering window of (2k+1)×(2k+1), , k represents the radius of the filter window, that is, the distance from the center pixel to the edge of the window, i and j represent the indexes in the horizontal and vertical directions respectively, which are used to traverse all pixels in the filter window, and I (x0+i, y0+i) represents the pixel value of the original image at position (x0+i, y0+i), where (x0+i, y0+i) is the position of the neighborhood pixel relative to the center pixel (x0, y0).

[0009] Preferably, the characteristic points of the optical surface include corner points, edge points, intersection points, intersection points, inflection points and extreme points; the characteristic lines of the optical surface include edge lines and contour lines.

[0010] Preferably, the expression of the three-dimensional surface model is specifically: , where S(x, y) represents the output value of the three-dimensional surface model, (x, y) represents the coordinates of the point on the image surface, (x i ,y i ) represents the coordinates of the i-th point in the point cloud, N represents the number of points in the point cloud data, i represents the number of the point cloud data point, λ i Expressed as the fitting surface coefficient of the i-th point, It is expressed as a radial basis function, that is, the surface point (x, y) and the i-th data point (x i ,y i ), where .

[0011] Preferably, the specific model for determining the coordinates of the center point of the optical surface is: , , , where (C x , C y , C z ) represents the pixel coordinates of the center point of the optical surface, N represents the number of points in the point cloud data, i represents the number of the point cloud data point, and x i Represented as the horizontal coordinate of the i-th point in the point cloud, y i Represented as the ordinate of the i-th point in the point cloud, w i Expressed as the weight of the i-th point, S(x i ,y i ) is represented by the point in the point cloud at position (x i ,y i ) on the fitted surface.

[0012] Preferably, the calculation model of the center distance of the optical surfaces in the lens is specifically: , where d is the center pixel spacing of the optical surface in the lens, (Cx1 , C y1 , C z1 )、(C x2 , C y2 , C z2 ) are represented as the pixel coordinates of the center points of the two optical surfaces; Convert pixel spacing to actual spacing, specifically: ,in, It is expressed as the center distance of the optical surfaces in the lens, Cr is the camera resolution, and Mm is the magnification of the microscope.

[0013] Preferably, the step of performing error correction on the center distance in step S7 is specifically as follows: Step S71: Calculate the error value caused by temperature change on the measurement , the calculation model is as follows: , where d0 represents the design value of the center distance of the optical surface, α represents the linear expansion rate of the optical element when the temperature changes, T represents the actual temperature during measurement, and T0 represents the preset ideal temperature; Step S72: Calculate the average deviation value of the measurement , the calculation model is as follows: , where m represents the number of measurements, j represents the number of measurements, and Mv j It is expressed as the center distance of the optical surface measured at the jth time; Step S72: Calculate the measured value after error correction , the calculation model is as follows: ,in, Expressed as the optical surface center distance value after error correction, Expressed as the measured mean deviation value, It is expressed as the error caused by temperature change during the jth measurement.

[0014] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a non-contact measurement system for the center distance of optical surfaces in a lens, which implements the above-mentioned non-contact measurement method for the center distance of optical surfaces in a lens, including: an optical surface image acquisition module, an optical surface image preprocessing module, an image feature extraction module, an image three-dimensional surface model construction module, a center point coordinate determination module, a center distance calculation module, an error correction module and a human-computer interaction module.

[0015] The optical surface image acquisition module uses a high-resolution camera to capture the optical surface image of the lens to be tested, and transmits the image to the optical surface image preprocessing module; The optical surface image preprocessing module is used to preprocess the optical surface image of the lens to be tested acquired by the optical surface image acquisition module; The image feature extraction module is used to extract feature points or feature lines of the optical surface from the image information preprocessed by the optical surface image preprocessing module using image processing software; The module for constructing a three-dimensional surface model of an image generates three-dimensional point cloud data of the lens to be tested by using a three-dimensional reconstruction algorithm according to the extracted feature points or feature lines. The three-dimensional point cloud data includes the three-dimensional shape and position information of the optical surface, and obtains a three-dimensional surface model by performing surface fitting on the point cloud data. The module for determining the center point coordinates determines the coordinates of the center point of the optical surface according to the three-dimensional surface model of the module for constructing the image three-dimensional surface model; The center distance calculation module calculates the center distance of the optical surface in the lens according to the coordinates of the center point of the optical surface determined by the center point coordinate determination module; The error correction module verifies the center distance of the optical surface in the lens calculated by the center distance calculation module for multiple times and performs error correction; The human-computer interaction module is used to establish a user interface to visually display the measurement results, verification reports and error correction results on the mobile device for personnel reference.

[0016] Technical effects and advantages of the present invention: 1. The present invention can achieve sub-pixel measurement accuracy through high-resolution cameras and precise image processing algorithms, and conduct non-contact measurement to reduce human and mechanical errors and ensure the high repeatability of measurement results; 2. The present invention improves the measurement accuracy by performing multiple verifications and error corrections on the calculated optical surface center distances; 3. The present invention collects and preprocesses the image of the optical surface of the lens to be tested, extracts the features of the optical surface image and constructs a three-dimensional surface model of the image, determines the coordinates of the center point of the optical surface, calculates the center distance of the optical surface and performs error correction, and adopts a non-contact measurement method, which can not only improve production efficiency and product quality, but also reduce production costs, and provides an efficient and reliable solution for the manufacture and detection of optical components. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0018] Figure 1It is a schematic diagram of the method flow of the present invention.

[0019] Figure 2 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Example 1 See also Figure 1 As shown, the present invention provides a non-contact measurement method for the center distance of optical surfaces in a lens, comprising the following steps: step S1: collecting images of the optical surface of the lens to be measured, step S2: preprocessing the optical surface image, step S3: extracting features of the optical surface image, step S4: constructing a three-dimensional surface model of the image, step S5: determining the coordinates of the center points of the optical surface, step S6: calculating the center distance of the optical surface, step S7: performing error correction on the center distance, and step S8: performing human-computer interaction.

[0022] Step S1: Capturing an image of the optical surface of the lens to be tested: using a high-resolution camera to capture an image of the optical surface of the lens to be tested; In this embodiment, it should be specifically explained that the optical surface image of the lens to be tested includes the front and back images of the optical surface; In this embodiment, it should be specifically explained that in step S1, a high-resolution camera is used to capture an optical surface image of the lens to be tested, and the process is performed under appropriate lighting conditions. The appropriate lighting conditions refer to an environment that ensures that the image quality meets the measurement and analysis requirements, including uniformity, brightness, lighting direction, color temperature, light source stability, and light source type and intensity adjusted for different materials and environments to reduce reflections and improve image clarity; In this embodiment, it should be specifically explained that the uniformity means that the illumination should be uniform on the surface of the lens to be tested to avoid shadows or bright spots, which will affect the clarity and contrast of the image; the brightness means that the intensity of the illumination should be sufficient so that the camera can capture a clear image, but not too bright to cause overexposure of the image; the illumination direction means that the illumination direction should minimize or eliminate reflection and glare, and oblique or (diffuse) scattered light is usually used to achieve this purpose; the color temperature means that the color temperature of the illumination should match the camera white balance setting to ensure the color accuracy of the image; the light source stability means that the illumination should be stable to avoid changes in image brightness due to light source fluctuations.

[0023] In this embodiment, it should be specifically explained that the specific operation of performing image acquisition on the optical surface of the lens to be tested in step S1 is: Step 1: prepare a high-precision three-dimensional optical measurement device, which is equipped with a high-resolution camera, an optical lens, and image processing software. Before the measurement begins, calibrate the measurement device to ensure that its measurement accuracy and stability meet the requirements. The calibration includes camera calibration and lens distortion correction. Step 2: Fix the lens to be tested on a precision fixture to ensure that the lens to be tested can be accurately positioned in the horizontal and vertical directions, install a high-resolution camera on a fixed optical bracket, align it with the main optical axis of the lens, and use a ring-shaped LED light source to surround the lens to provide uniform illumination; Step 3. Turn on the LED light source and adjust the brightness to an appropriate level to ensure that both optical surfaces of the lens are clearly visible. Use a high-resolution camera to capture the front image of the optical surface of the lens to be tested, and then capture the back image without moving the lens to be tested. Use multi-angle lighting technology to illuminate the lens to be tested from different directions to reveal the subtle features of the optical surface and reduce the measurement error caused by a single lighting angle.

[0024] Step S2: preprocessing the optical surface image: preprocessing the optical surface image of the lens to be tested collected in step S1; In this embodiment, it should be specifically explained that the specific method of preprocessing the optical surface image in step S2 is: The collected optical surface image is subjected to denoising, contrast enhancement, distortion correction and background elimination to improve the image quality; the denoising specifically uses Gaussian filtering to remove image noise; the contrast enhancement specifically uses the Canny edge detection algorithm to perform edge enhancement; the distortion correction specifically uses image processing software to perform edge detection, identify the contour image of the optical surface for correction; and remove lens distortion and uneven lighting effects in the image.

[0025] In this embodiment, it should be specifically explained that the mathematical model for denoising the optical surface image in step S2 is specifically expressed as: , where I(x0, y0) represents the pixel value of the filtered image at position (x0, y0), and M represents the total number of pixels in the neighborhood. For a filtering window of (2k+1)×(2k+1), , k represents the radius of the filter window, that is, the distance from the center pixel to the edge of the window, i and j represent the indexes in the horizontal and vertical directions respectively, which are used to traverse all pixels in the filter window, and I (x0+i, y0+i) represents the pixel value of the original image at position (x0+i, y0+i), where (x0+i, y0+i) is the position of the neighborhood pixel relative to the center pixel (x0, y0).

[0026] In this embodiment, it should be specifically explained that, in image processing, an index is used to specify the position of a pixel; for a two-dimensional image, each pixel can be indexed by a pair of coordinates (x0, y0), where x0 is the position of the pixel in the horizontal direction (column), and y0 is the position of the pixel in the vertical direction (row); a neighborhood refers to a group of pixels surrounding a specific pixel in image processing; in a filtering operation, a neighborhood is usually a small two-dimensional area centered on the currently processed pixel and includes the pixels around the pixel.

[0027] Step S3: extracting features of the optical surface image: extracting feature points or feature lines of the optical surface from the pre-processed image using image processing software; In this embodiment, it should be specifically explained that the characteristic points of the optical surface include corner points, edge points, intersection points, intersection points, inflection points and extreme points; the characteristic lines of the optical surface include edge lines and contour lines.

[0028] Step S4: constructing a three-dimensional surface model of the image: generating three-dimensional point cloud data of the lens to be tested by using a three-dimensional reconstruction algorithm according to the extracted feature points or feature lines, wherein the three-dimensional point cloud data includes the three-dimensional shape and position information of the optical surface, and obtaining a three-dimensional surface model by performing surface fitting on the point cloud data; In this embodiment, it should be specifically explained that the point coordinates of the three-dimensional point cloud data in step S4 are expressed as a matrix Q, which is specifically expressed as: , where N represents the number of points in the point cloud data, (x i ,y i , z i ) is represented as the three-dimensional coordinates of the i-th point.

[0029] In this embodiment, it should be specifically explained that the expression of the three-dimensional surface model is specifically: , where S(x, y) represents the output value of the three-dimensional surface model, (x, y) represents the coordinates of the point on the image surface, (x i ,y i ) represents the coordinates of the i-th point in the point cloud, N represents the number of points in the point cloud data, i represents the number of the point cloud data point, λ i Expressed as the fitting surface coefficient of the i-th point, It is expressed as a radial basis function, that is, the surface point (x, y) and the i-th data point (x i ,y i ), where .

[0030] Step S5: Determine the coordinates of the center point of the optical surface: construct the three-dimensional surface model of the image according to the step S4, and determine the coordinates of the center point of the optical surface; In this embodiment, it should be specifically explained that the specific model for determining the coordinates of the center point of the optical surface is: , , , where (C x , C y , C z ) represents the pixel coordinates of the center point of the optical surface, N represents the number of points in the point cloud data, i represents the number of the point cloud data point, and x i Represented as the horizontal coordinate of the i-th point in the point cloud, y i Represented as the ordinate of the i-th point in the point cloud, w i Expressed as the weight of the i-th point, S(x i ,y i ) is represented by the point in the point cloud at position (x i ,y i ) on the fitted surface.

[0031] Step S6: Calculate the center distance of the optical surface: Calculate the center distance of the optical surface in the lens according to the coordinates of the center points of the optical surface determined in step S5; In this embodiment, it should be specifically explained that the calculation model of the center distance of the optical surfaces in the lens is specifically: , where d is the center pixel spacing of the optical surface in the lens, (C x1 , C y1 , C z1 )、(C x2 , C y2 , C z2 ) are represented as the pixel coordinates of the center points of the two optical surfaces; Convert pixel spacing to actual spacing, specifically: ,in, It is expressed as the center distance of the optical surfaces in the lens, Cr is the camera resolution, and Mm is the magnification of the microscope.

[0032] Step S7: performing error correction on the center distance: performing multiple verifications on the center distance of the optical surface in the lens calculated in step S6 and performing error correction; In this embodiment, it should be specifically explained that the step of performing error correction on the center distance in step S7 is specifically as follows: Step S71: Calculate the error value caused by temperature change on the measurement , the calculation model is as follows: , where d0 represents the design value of the center distance of the optical surface, α represents the linear expansion rate of the optical element when the temperature changes, T represents the actual temperature during measurement, and T0 represents the preset ideal temperature; Step S72: Calculate the average deviation value of the measurement , the calculation model is as follows: , where m represents the number of measurements, j represents the number of measurements, and Mv j It is expressed as the center distance of the optical surface measured at the jth time; Step S72: Calculate the measured value after error correction , the calculation model is as follows: ,in, Expressed as the optical surface center distance value after error correction, Expressed as the measured mean deviation value, It is expressed as the error caused by temperature change during the jth measurement.

[0033] Step S8: Perform human-computer interaction: used to establish a user interface to visualize the measurement results, verification reports, and error correction results on a mobile device for personnel reference.

[0034] Example 2 See also Figure 2 As shown, the present invention provides a non-contact measurement system for the center distance of optical surfaces in a lens, including an optical surface image acquisition module, an optical surface image preprocessing module, an image feature extraction module, an image three-dimensional surface model construction module, a center point coordinate determination module, a center distance calculation module, an error correction module and a human-computer interaction module.

[0035] The optical surface image acquisition module uses a high-resolution camera to capture the optical surface image of the lens to be tested, and transmits the image to the optical surface image preprocessing module; The optical surface image preprocessing module is used to preprocess the optical surface image of the lens to be tested acquired by the optical surface image acquisition module; The image feature extraction module is used to extract feature points or feature lines of the optical surface from the image information preprocessed by the optical surface image preprocessing module using image processing software; The module for constructing a three-dimensional surface model of an image generates three-dimensional point cloud data of the lens to be tested by using a three-dimensional reconstruction algorithm according to the extracted feature points or feature lines. The three-dimensional point cloud data includes the three-dimensional shape and position information of the optical surface, and obtains a three-dimensional surface model by performing surface fitting on the point cloud data. The module for determining the center point coordinates determines the coordinates of the center point of the optical surface according to the three-dimensional surface model of the module for constructing the image three-dimensional surface model; The center distance calculation module calculates the center distance of the optical surface in the lens according to the coordinates of the center point of the optical surface determined by the center point coordinate determination module; The error correction module verifies the center distance of the optical surface in the lens calculated by the center distance calculation module for multiple times and performs error correction; The human-computer interaction module is used to establish a user interface to visually display the measurement results, verification reports and error correction results on the mobile device for personnel reference.

[0036] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0037] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A non-contact measurement method for the center distance of optical surfaces in a lens, characterized in that: The following steps are involved: Step S1: Capturing an image of the optical surface of the lens to be tested: using a high-resolution camera to capture an image of the optical surface of the lens to be tested; Step S2: preprocessing the optical surface image: preprocessing the optical surface image of the lens to be tested collected in step S1; Step S3: extracting features of the optical surface image: extracting feature points or feature lines of the optical surface from the pre-processed image using image processing software; Step S4: constructing a three-dimensional surface model of the image: generating three-dimensional point cloud data of the lens to be tested by using a three-dimensional reconstruction algorithm according to the extracted feature points or feature lines, wherein the three-dimensional point cloud data includes the three-dimensional shape and position information of the optical surface, and obtaining a three-dimensional surface model by performing surface fitting on the point cloud data; Step S5: Determine the coordinates of the center point of the optical surface: construct the three-dimensional surface model of the image according to the step S4, and determine the coordinates of the center point of the optical surface; Step S6: Calculate the center distance of the optical surface: Calculate the center distance of the optical surface in the lens according to the coordinates of the center points of the optical surface determined in step S5; Step S7: performing error correction on the center distance: performing multiple verifications on the center distance of the optical surface in the lens calculated in step S6 and performing error correction; Step S8: Perform human-computer interaction: used to establish a user interface to visualize the measurement results, verification reports, and error correction results on a mobile device for personnel reference.

2. The non-contact measurement method for the center distance of optical surfaces in a lens according to claim 1, characterized in that: The mathematical model for denoising the optical surface image in step S2 is specifically expressed as: , where I(x0, y0) represents the pixel value of the filtered image at position (x0, y0), and M represents the total number of pixels in the neighborhood. For a filtering window of (2k+1)×(2k+1), , k represents the radius of the filter window, that is, the distance from the center pixel to the edge of the window, i and j represent the indexes in the horizontal and vertical directions respectively, which are used to traverse all pixels in the filter window, and I (x0+i, y0+i) represents the pixel value of the original image at position (x0+i, y0+i), where (x0+i, y0+i) is the position of the neighborhood pixel relative to the center pixel (x0, y0).

3. The non-contact measurement method for the center distance of optical surfaces in a lens according to claim 1, characterized in that: The characteristic points of the optical surface include corner points, edge points, intersection points, intersection points, inflection points and extreme points; the characteristic lines of the optical surface include edge lines and contour lines.

4. The non-contact measurement method for the center distance of optical surfaces in a lens according to claim 1, characterized in that: The expression of the three-dimensional surface model is specifically: , where S(x, y) represents the output value of the three-dimensional surface model, (x, y) represents the coordinates of the point on the image surface, (x i ,y i ) represents the coordinates of the i-th point in the point cloud, N represents the number of points in the point cloud data, i represents the number of the point cloud data point, λ i Expressed as the fitting surface coefficient of the i-th point, It is expressed as a radial basis function, that is, the surface point (x, y) and the i-th data point (x i ,y i ), where .

5. The non-contact measurement method for the center distance of optical surfaces in a lens according to claim 1, characterized in that: The specific model for determining the coordinates of the center point of the optical surface is: , , , where (C x , C y , C z ) represents the pixel coordinates of the center point of the optical surface, N represents the number of points in the point cloud data, i represents the number of the point cloud data point, and x i Represented as the horizontal coordinate of the i-th point in the point cloud, y i Represented as the ordinate of the i-th point in the point cloud, w i Expressed as the weight of the i-th point, S(x i ,y i ) is represented by the point in the point cloud at position (x i ,y i ) on the fitted surface.

6. The non-contact measurement method for the center distance of optical surfaces in a lens according to claim 1, characterized in that: The calculation model of the center distance of the optical surfaces in the lens is specifically: , where d is the center pixel spacing of the optical surface in the lens, (C x1 , C y1 , C z1 )、(C x2 , C y2 , C z2 ) are represented as the pixel coordinates of the center points of the two optical surfaces; Convert pixel spacing to actual spacing, specifically: ,in, It is expressed as the center distance of the optical surfaces in the lens, Cr is the camera resolution, and Mm is the magnification of the microscope.

7. The non-contact measurement method for the center distance of optical surfaces in a lens according to claim 1, characterized in that: The step of performing error correction on the center distance in step S7 is specifically as follows: Step S71: Calculate the error value caused by temperature change on the measurement , the calculation model is as follows: , where d0 represents the design value of the center distance of the optical surface, α represents the linear expansion rate of the optical element when the temperature changes, T represents the actual temperature during measurement, and T0 represents the preset ideal temperature; Step S72: Calculate the average deviation value of the measurement , the calculation model is as follows: , where m represents the number of measurements, j represents the number of measurements, and Mv j It is expressed as the center distance of the optical surface measured at the jth time; Step S72: Calculate the measured value after error correction , the calculation model is as follows: ,in, Expressed as the optical surface center distance value after error correction, Expressed as the measured mean deviation value, It is expressed as the error caused by temperature change during the jth measurement.

8. A non-contact measurement system for the center distance between optical surfaces in a lens, used to implement the non-contact measurement method for the center distance between optical surfaces in a lens as described in any one of claims 1 to 7, characterized in that: It includes: optical surface image acquisition module, optical surface image preprocessing module, image feature extraction module, image three-dimensional surface model building module, center point coordinate determination module, center distance calculation module, error correction module and human-computer interaction module; The optical surface image acquisition module uses a high-resolution camera to capture the optical surface image of the lens to be tested, and transmits the image to the optical surface image preprocessing module; The optical surface image preprocessing module is used to preprocess the optical surface image of the lens to be tested acquired by the optical surface image acquisition module; The image feature extraction module is used to extract feature points or feature lines of the optical surface from the image information preprocessed by the optical surface image preprocessing module using image processing software; The module for constructing a three-dimensional surface model of an image generates three-dimensional point cloud data of the lens to be tested by using a three-dimensional reconstruction algorithm according to the extracted feature points or feature lines. The three-dimensional point cloud data includes the three-dimensional shape and position information of the optical surface, and obtains a three-dimensional surface model by performing surface fitting on the point cloud data. The module for determining the center point coordinates determines the coordinates of the center point of the optical surface according to the three-dimensional surface model of the module for constructing the image three-dimensional surface model; The center distance calculation module calculates the center distance of the optical surface in the lens according to the coordinates of the center point of the optical surface determined by the center point coordinate determination module; The error correction module verifies the center distance of the optical surface in the lens calculated by the center distance calculation module for multiple times and performs error correction; The human-computer interaction module is used to establish a user interface to visually display the measurement results, verification reports and error correction results on the mobile device for personnel reference.

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