A method for detecting the field of view of an optical instrument

Abstract

This invention discloses a method for detecting the field of view of optical instruments, belonging to the field of optical testing technology. The method is based on a fully automated alignment and calibration testing system, where a host computer centrally controls the electrically adjustable support platform, coded display screen, image acquisition module, displacement sensing module, and autofocus lens group. During the testing process, the system automatically completes the parallel alignment, center alignment, and precise positioning of the working distance between the display screen and the optical instrument under test, and achieves automatic focusing of the image. The coded display screen displays a layered striped target image with binary encoding. After image acquisition by the image acquisition module, the stripe features are enhanced through adaptive preprocessing. The host computer accurately identifies the number and spacing of the stripes based on the coded identifiers and calculates the field of view based on the working distance. After multiple tests, outliers are removed using the Grubbs criterion, and the average of the valid data is taken as the final test result. This invention is fully automated, eliminating manual alignment and interpretation errors, and improving testing accuracy, repeatability, and efficiency.

Description

Technical Field

[0001] This application relates to the field of optical detection technology, and in particular to a method for detecting the field of view of an optical instrument. Background Technology

[0002] The field of view is one of the core optical parameters of an optical instrument. With the lens of the optical instrument as the vertex, the angle formed by the two edges of the lens through which the image of the target object can pass is the field of view. It not only reflects the design capabilities of the optical instrument but also indirectly reflects the manufacturing and assembly quality by comparing the actual measured value with the theoretical design value. Therefore, accurate detection of the field of view of an optical instrument is of great significance for its research and development, production, and quality inspection.

[0003] Currently, methods for detecting the field of view of optical instruments are mainly divided into two categories. One is the traditional human eye observation method. This method involves the human eye observing targets such as rulers or concentric rings with the aid of optical instruments. After manually aligning with the center of the target, the reading at the outermost edge that the optical instrument can image is determined, and then the field of view is calculated. This method relies entirely on manual operation, resulting in large measurement errors and poor repeatability. Furthermore, the manual alignment and interpretation process is cumbersome and inefficient. In addition, due to the limitations of human eye resolution, the target scale values ​​are relatively large, further reducing the detection accuracy.

[0004] Another type is the detection method based on machine vision, such as the detection device and method for the field of view of an optical instrument disclosed in patent CN106441212A. The device displays a striped target image on a screen, the image acquisition module acquires the image of the optical instrument under test, and the host computer calculates the field of view based on the image and working distance. This method replaces human observation and interpretation and improves the detection accuracy to a certain extent. However, this method still has many technical shortcomings and cannot meet the requirements of high-precision detection: First, the adjustment of the workstation and the focusing of the lens group are all done manually. The carrier platform is manually adjusted to keep the display screen parallel to the instrument under test and to adjust it to the working distance. At the same time, the lens group is manually adjusted to make the image clear. This process is greatly affected by human factors, the accuracy of alignment and focusing is low, and the operation is still relatively cumbersome, which limits the detection efficiency. Second, this method uses a single alternating bright and dark stripes as the target image. Under the influence of optical distortion, the stripes at the edge of the field of view are prone to blurring and distortion, which leads to the upper computer making errors in counting the number of stripes, such as missing or overcounting, which directly affects the accuracy of the field of view calculation. Third, this method does not perform targeted preprocessing on the acquired images. Environmental noise and stray light from the optical system will reduce the image quality and further aggravate the error in stripe recognition. At the same time, this method only calculates the uncertainty after multiple tests and does not remove abnormal measurement values. Abnormal values ​​will interfere with the calculation of the average value, resulting in poor repeatability and reliability of the test results.

[0005] To address the aforementioned problems in existing technologies, this invention proposes a method for detecting the field of view of optical instruments. By employing fully automated alignment calibration, coded layered target images, adaptive image preprocessing, and outlier removal techniques, this method solves the problems of low precision in manual operation, stripe counting errors, and interference from outliers in the detection results, thereby achieving high-precision and highly repeatable detection of the field of view of optical instruments. Summary of the Invention

[0006] The optical instrument field of view detection method provided in this application adopts the following technical solution:

[0007] A method for detecting the field of view of an optical instrument, based on a fully automatic alignment and calibration detection system, is disclosed. The fully automatic alignment and calibration detection system includes an electrically adjustable support platform, an coded display screen, an image acquisition module, a signal processing module, a host computer, a displacement sensing module, and an autofocus lens group. The displacement sensing module, the electrically adjustable support platform, the autofocus lens group, the image acquisition module, and the signal processing module are all electrically connected to the host computer. The autofocus lens group is positioned between the optical instrument under test and the image acquisition module. The optical instrument under test is placed at a preset position on the electrically adjustable support platform. The method includes the following steps: S1, the host computer controls the position... The motion sensing module collects the relative position information of the coded display screen, the optical instrument under test, and the image acquisition module. Based on the position information, it controls the electrically adjustable support stage to complete fully automatic alignment calibration, ensuring that the display surface of the coded display screen is parallel to the lens of the optical instrument under test, the line connecting the entrance pupil center of the optical instrument under test and the object-side field of view center of the coded display screen is perpendicular to the display surface, and the distance between them is the working distance of the optical instrument under test. Simultaneously, the host computer controls the autofocus lens group to complete automatic focusing, so that the target image after passing through the optical instrument under test is clearly projected onto the image acquisition module; S2, the coded display screen displays a coded layered target image, the target image to... The target image covers less of the nominal field of view of the optical instrument under test, and the stripe extension direction of the target image is perpendicular to the plane where the field of view to be tested is located. The coded layered target image includes a positioning layer, a base layer, and a coding layer. The positioning layer is the crosshair positioning point at the center of the target image. The base layer consists of equally spaced stripes of alternating light and dark colors. The coding layer consists of binary coding identifiers located on the side of each stripe, and the binary coding identifiers correspond one-to-one with the stripes. S3: The image acquisition module acquires the image of the coded layered target image from the optical instrument under test and transmits the acquired image data to the signal processing module. S4: The signal processing module performs adaptive pre-processing on the acquired image data. The process involves processing the image to obtain a clear and effective image, which is then transmitted to the host computer. S5: The host computer extracts features from the effective image, identifying the number of effective stripes and the center-to-center distance between adjacent stripes in the coded layered target image. It then calculates the field of view of the optical instrument under test based on the working distance. The specific process of feature extraction is as follows: the host computer identifies the binary coded identifier in the effective image and determines the number of effective stripes N based on the coded identifier. S6: Steps S3-S5 are repeated multiple times to obtain multiple field of view measurements. After removing outliers using the Grubbs criterion, the average of the remaining measurements is calculated as the final measured value of the field of view of the optical instrument under test.

[0008] Preferably, the adaptive preprocessing includes sequential grayscale adaptive enhancement, median filtering for noise reduction, and Laplacian edge sharpening, wherein the grayscale adaptive enhancement is implemented using gamma transform, and the host computer automatically adjusts the gamma value based on the average grayscale value of the image.

[0009] Preferably, the effective image is processed to grayscale, the grayscale peak curve is extracted, and the distance s between the centers of two adjacent stripes is determined based on the grayscale peak curve.

[0010] Preferably, the formula for calculating the field of view is: Where θ is the field of view of the optical instrument under test, s is the distance between the centers of two adjacent fringes, N is the number of effective fringes, and H is the working distance between the coded display screen and the lens of the optical instrument under test.

[0011] Preferably, the specific process of automatic focusing is as follows: the host computer controls the image acquisition module to acquire a test image, calculates the sharpness evaluation function value of the test image, and controls the lens spacing of the automatic focusing lens group to iteratively adjust according to the function value until the sharpness evaluation function value reaches a preset threshold, thereby completing automatic focusing.

[0012] Preferably, the specific process of using the Grubbs criterion to remove outliers is as follows: calculate the mean and standard deviation of multiple field-of-view measurements, determine the Grubbs critical value based on the number of tests, calculate the Grubbs statistic for each measurement, and determine and remove measurements with a statistic greater than the critical value as outliers.

[0013] Preferably, the coded display screen is a high PPI LCD or OLED display screen, the image acquisition module is a CCD or CMOS image sensor, and the displacement sensing module is a laser displacement sensor.

[0014] In summary, this application includes the following beneficial technical effects:

[0015] 1. This invention realizes fully automatic alignment and calibration of the inspection station and automatic focusing of the lens group, replacing the manual operation in the prior art. The micron-level positioning accuracy of the laser displacement sensor and the precise adjustment of the electric adjustment stage greatly improve the accuracy of alignment and focusing. At the same time, the automated operation simplifies the inspection process, improves the inspection efficiency, and solves the problems of low accuracy and cumbersome operation of manual adjustment in the prior art.

[0016] 2. This invention designs a coded layered target image and performs adaptive preprocessing on the acquired images. The binary identifier of the coded layer enables accurate identification of effective stripes, avoiding counting errors caused by blurred edge stripes. The adaptive preprocessing improves the image quality and edge features of the stripes, further improving the accuracy of stripe identification and ultimately improving the accuracy of the field of view calculation, thus solving the problem of large stripe counting errors in the prior art.

[0017] 3. This invention uses the Grubbs criterion to remove outliers after multiple tests, and then calculates the average value as the final test value. This avoids interference from outlier measurements on the test results, greatly improving the repeatability and reliability of the test results. It solves the problem of poor repeatability of test results caused by only calculating uncertainty without removing outliers in the prior art. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall structure of the present invention.

[0019] Figure 2 This is a schematic diagram of a coded, layered target image structure.

[0020] Figure 3 This is a schematic diagram of the process for detecting the field of view of an optical instrument. Detailed Implementation

[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0022] Reference Figure 1-3This invention provides a method for detecting the field of view of an optical instrument, based on a fully automatic alignment and calibration detection system. The fully automatic alignment and calibration detection system includes an electrically adjustable support platform, an coded display screen, an image acquisition module, a signal processing module, a host computer, a displacement sensing module, and an autofocus lens group. The displacement sensing module, the electrically adjustable support platform, the autofocus lens group, the image acquisition module, and the signal processing module are all electrically connected to the host computer. The autofocus lens group is positioned between the optical instrument under test and the image acquisition module. The optical instrument under test is placed at a preset position on the electrically adjustable support platform. The method includes the following steps: S1, ... The host computer controls the displacement sensing module to collect the relative position information of the coded display screen, the optical instrument under test, and the image acquisition module. Based on the position information, it controls the electrically adjustable support platform to complete fully automatic alignment calibration, ensuring that the display surface of the coded display screen is parallel to the lens of the optical instrument under test, the line connecting the entrance pupil center of the optical instrument under test and the object-side field of view center of the coded display screen is perpendicular to the display surface, and the distance between them is the working distance of the optical instrument under test. Simultaneously, the host computer controls the autofocus lens group to complete automatic focusing, so that the target image after passing through the optical instrument under test is clearly projected onto the image acquisition module; S2, the coded display screen displays a coded layered target image, the target... The image at least covers the nominal field of view of the optical instrument under test, and the stripe extension direction of the target image is perpendicular to the plane containing the field of view angle to be tested. The coded layered target image includes a positioning layer, a base layer, and a coding layer. The positioning layer is the crosshair positioning point at the center of the target image. The base layer consists of equally spaced stripes of alternating light and dark colors. The coding layer consists of binary coding identifiers located on the side of each stripe, and the binary coding identifiers correspond one-to-one with the stripes. S3: The image acquisition module acquires the image of the coded layered target image from the optical instrument under test and transmits the acquired image data to the signal processing module. S4: The signal processing module performs adaptive processing on the acquired image data. Preprocessing is required to obtain a clear and effective image, which is then transmitted to the host computer. S5: The host computer extracts features from the effective image, identifies the number of effective stripes and the center-to-center distance between adjacent stripes in the coded layered target image, and calculates the field of view of the optical instrument under test based on the working distance. The specific process of feature extraction is as follows: the host computer identifies the binary coded identifier in the effective image and determines the number N of effective stripes based on the coded identifier. S6: Repeat steps S3-S5 multiple times to obtain multiple field of view measurements. After removing outliers using the Grubbs criterion, the average of the remaining measurements is calculated as the final detection value of the field of view of the optical instrument under test.

[0023] The optical instrument field of view detection method relies on a fully automated alignment and calibration detection system. This system consists of an electrically adjustable platform, an coded display screen, an image acquisition module, a signal processing module, a host computer, a displacement sensing module, and an autofocus lens assembly. The displacement sensing module, electrically adjustable platform, autofocus lens assembly, image acquisition module, and signal processing module are all electrically connected to the host computer. The autofocus lens assembly is positioned between the optical instrument under test and the image acquisition module, with the optical instrument under test fixed at a preset position on the electrically adjustable platform. After detection begins, the host computer controls the displacement sensing module to acquire the relative position information of the coded display screen, the optical instrument under test, and the image acquisition module. Based on the position data, the host computer drives the electrically adjustable platform to complete fully automated alignment and calibration, ensuring that the display surface of the coded display screen is parallel to the lens of the optical instrument under test, and that the line connecting the entrance pupil center of the optical instrument under test and the object-side field of view center of the coded display screen is perpendicular to the display surface. Simultaneously, the distance between the two is adjusted to the standard working distance of the optical instrument under test. The autofocus lens assembly is also controlled to focus, ensuring that the target image is clearly projected onto the image acquisition module after passing through the optical instrument under test. Subsequently, the coded display screen shows the adapted coded layered target image. The image acquisition module acquires the target image and transmits it to the signal processing module. After adaptive preprocessing to obtain a clear and effective image, it is uploaded to the host computer. The host computer extracts the stripe features and calculates the field of view angle in combination with the working distance. After repeated detection, outliers are removed using the Grubbs criterion, and the average of the effective data is taken as the final detection result. The coded layered target image adopts a three-layer composite structure design, which can provide an accurate visual reference for field of view angle detection. The positioning layer is a crosshair positioning point set in the center of the target image, which can quickly match the field of view center of the optical instrument under test and provide a center positioning reference for the system. The base layer consists of equally spaced stripes of light and dark, which serve as the core basis for field of view angle calculation and undertake the functions of stripe counting and spacing measurement. The coding layer is a binary code identifier on the side of each stripe. Each code uniquely corresponds to the corresponding stripe, and each stripe is distinguished by a dedicated code to avoid counting deviations caused by optical distortion and edge blurring.

[0024] In a preferred embodiment, the adaptive preprocessing includes sequential grayscale adaptive enhancement, median filtering for noise reduction, and Laplacian edge sharpening, wherein the grayscale adaptive enhancement is implemented using gamma transform, and the host computer automatically adjusts the gamma value based on the average grayscale value of the image.

[0025] The adaptive preprocessing of imaging data is achieved through three consecutive steps, aiming to improve imaging quality and stripe feature recognition. First, the image contrast is optimized through grayscale adaptive enhancement. This step is implemented using gamma transform. The host computer automatically adjusts the gamma value according to the grayscale mean of the image to make the grayscale distribution of the image more balanced. Next, median filtering is used to remove image noise caused by environmental interference and stray light, while preserving the complete outline of the stripes. Finally, the edge sharpening is completed through the Laplacian operator to enhance the stripe boundary features and make the stripe outline clearer and more regular.

[0026] In a preferred embodiment, the effective image is converted to grayscale, a grayscale peak curve is extracted, and the distance s between the centers of two adjacent stripes is determined based on the grayscale peak curve.

[0027] Feature extraction of effective imaging revolves around two core parameters: the number of stripes and the spacing. Accurate extraction is achieved by relying on code recognition and grayscale analysis. The host computer first identifies the binary code identifier in the imaging and directly determines the total number N of effective stripes in the field of view based on the uniqueness of the code. Then, the effective imaging is converted into a grayscale image, and the grayscale peak curve is extracted along the detection direction of the field of view angle. The peak of the curve corresponds to the center of the stripe, and the spacing s between adjacent stripe centers is calculated by the difference in the peak position, thus completing the core feature extraction.

[0028] In a preferred embodiment, the field of view is calculated using the following formula: Where θ is the field of view of the optical instrument under test, s is the distance between the centers of two adjacent fringes, N is the number of effective fringes, and H is the working distance between the coded display screen and the lens of the optical instrument under test.

[0029] A right-angled triangular model is constructed with the lens of the optical instrument under test as the vertex, the total width of the stripes on the display screen as the opposite side, and the working distance as the adjacent side. The field angle θ is calculated directly using the formula where s×(N−1) is the total width of the stripes in the field of view and H is the fixed working distance.

[0030] The field of view angle is calculated based on the geometric optical model. Accurate calculation is achieved by combining fringe parameters and working distance. The lens of the optical instrument under test is taken as the vertex, the working distance H between the coded display screen and the lens of the optical instrument under test is taken as the longitudinal reference, and the total width of the fringe in the field of view is taken as the transverse reference. The total width of the fringe is calculated by s×(N-1) from the spacing between adjacent fringe s and the number of effective fringe N. The calculation is then completed by the arctangent function formula, and finally the field of view angle θ of the optical instrument under test is obtained.

[0031] In a preferred embodiment, the specific process of automatic focusing is as follows: the host computer controls the image acquisition module to acquire a test image, calculates the sharpness evaluation function value of the test image, and controls the lens spacing of the automatic focusing lens group to iteratively adjust according to the function value until the sharpness evaluation function value reaches a preset threshold, thereby completing automatic focusing.

[0032] The autofocus uses a closed-loop feedback control method to ensure that the target image is clear throughout the imaging process. The host computer first controls the image acquisition module to acquire test images and calculates the sharpness evaluation function value of the test images. This value is used as the basis for focusing and controls the lens spacing of the autofocus lens group to be adjusted iteratively step by step. Each time it is adjusted, the test images are reacquired and the sharpness value is calculated until the value reaches the preset threshold. After confirming that the full field of view image is clear, the lens group parameters are locked and the autofocus is completed.

[0033] In a preferred embodiment, the specific process of using the Grubbs criterion to remove outliers is as follows: calculate the mean and standard deviation of multiple field-of-view measurements, determine the Grubbs critical value based on the number of tests, calculate the Grubbs statistic for each measurement, and identify and remove measurements whose statistic is greater than the critical value as outliers.

[0034] Outlier removal after multiple tests is performed using the Grubbs criterion to filter out invalid data caused by random errors. The host computer first counts all field-of-view measurements, calculates the mean and standard deviation of the data, matches the corresponding Grubbs critical value with the number of tests, and then calculates the Grubbs statistic for each measurement. Measurements with statistics exceeding the critical value are identified as outliers and removed, retaining only stable and valid data for subsequent calculations.

[0035] In a preferred embodiment, the coded display screen is a high PPI LCD or OLED display screen, the image acquisition module is a CCD or CMOS image sensor, and the displacement sensing module is a laser displacement sensor.

[0036] The core hardware of the detection system uses high-precision compatible models to ensure the accuracy and stability of the detection from the hardware level. The encoding display screen uses a high PPI LCD or OLED display screen, which can output high-precision fine-pitch stripe target images to improve the accuracy of the detection benchmark. The image acquisition module uses a CCD or CMOS image sensor, which has high imaging resolution and good signal-to-noise ratio, and can stably acquire high-quality imaging data. The displacement sensing module uses a laser displacement sensor, and the position detection accuracy can reach the micron level, providing accurate data support for fully automatic alignment calibration.

[0037] The foregoing description, with reference to preferred embodiments, illustrates an exemplary implementation of an optical instrument field-of-view detection method provided by this disclosure. However, those skilled in the art will understand that various modifications and alterations can be made to the above specific embodiments without departing from the spirit of this disclosure, and various combinations can be made to the various technical features and structures proposed in this disclosure without exceeding the protection scope of this disclosure, the protection scope of which is determined by the appended claims.

Claims

1. A method for detecting the field of view of an optical instrument, characterized in that: This method is implemented based on a fully automated alignment calibration and testing system. The fully automated alignment calibration and testing system includes an electrically adjustable support platform, an coded display screen, an image acquisition module, a signal processing module, a host computer, a displacement sensing module, and an autofocus lens assembly. The displacement sensing module, the electrically adjustable support platform, the autofocus lens assembly, the image acquisition module, and the signal processing module are all electrically connected to the host computer. The autofocus lens assembly is positioned between the optical instrument under test and the image acquisition module. The optical instrument under test is placed at a preset position on the electrically adjustable support platform. The method includes the following steps: S1. The host computer controls the displacement sensing module to collect the relative position information of the coded display screen, the optical instrument under test, and the image acquisition module. Based on the position information, it controls the electric adjustment platform to complete fully automatic alignment calibration, so that the display surface of the coded display screen is parallel to the lens of the optical instrument under test, the line connecting the entrance pupil center of the optical instrument under test and the object-side field of view center of the coded display screen is perpendicular to the display surface, and the distance between the two is the working distance of the optical instrument under test. At the same time, the host computer controls the autofocus lens group to complete automatic focusing, so that the target image after passing through the optical instrument under test is clearly projected onto the image acquisition module. S2. The coded display screen displays a coded layered target image. The target image at least covers the nominal field of view of the optical instrument under test, and the stripe extension direction of the target image is perpendicular to the plane where the field of view to be tested is located. The coded layered target image includes a positioning layer, a base layer, and a coding layer. The positioning layer is the cross positioning point at the center of the target image. The base layer consists of equally spaced stripes of alternating light and dark colors. The coding layer consists of binary coding identifiers located on the side of each stripe. The binary coding identifiers correspond one-to-one with the stripes. S3, the image acquisition module acquires the image of the coded layered target from the optical instrument under test, and transmits the acquired image data to the signal processing module; S4. The signal processing module performs adaptive preprocessing on the acquired imaging data to obtain clear and effective images and transmits them to the host computer. S5. The host computer extracts features from the effective image, identifies the number of effective stripes and the center-to-center distance between adjacent stripes in the coded layered target image, and calculates the field of view of the optical instrument under test in combination with the working distance. The specific process of feature extraction is as follows: the host computer identifies the binary code identifier in the effective image and determines the number N of effective stripes based on the code identifier. S6. Repeat steps S3-S5 multiple times to obtain multiple field-of-view angle measurements. After removing outliers using the Grubbs criterion, calculate the average of the remaining measurements as the final measured value of the field-of-view angle of the optical instrument under test.

2. The method for detecting the field of view of an optical instrument according to claim 1, characterized in that: The adaptive preprocessing includes sequential grayscale adaptive enhancement, median filtering for noise reduction, and Laplacian edge sharpening. The grayscale adaptive enhancement is achieved using gamma transform, and the host computer automatically adjusts the gamma value based on the average grayscale value of the image.

3. The method for detecting the field of view of an optical instrument according to claim 1, characterized in that: The effective image is converted to grayscale, the grayscale peak curve is extracted, and the distance s between the centers of two adjacent stripes is determined based on the grayscale peak curve.

4. The method for detecting the field of view of an optical instrument according to claim 1, characterized in that: The formula for calculating the field of view is: Where θ is the field of view of the optical instrument under test, s is the distance between the centers of two adjacent fringes, N is the number of effective fringes, and H is the working distance between the coded display screen and the lens of the optical instrument under test.

5. The method for detecting the field of view of an optical instrument according to claim 1, characterized in that: The specific process of automatic focusing is as follows: the host computer controls the image acquisition module to acquire a test image, calculates the sharpness evaluation function value of the test image, and controls the lens spacing of the automatic focusing lens group to be iteratively adjusted according to the function value until the sharpness evaluation function value reaches the preset threshold, thus completing automatic focusing.

6. The method for detecting the field of view of an optical instrument according to claim 1, characterized in that: The specific process of using the Grubbs criterion to remove outliers is as follows: calculate the mean and standard deviation of multiple field-of-view measurements, determine the Grubbs critical value based on the number of tests, calculate the Grubbs statistic for each measurement, and identify and remove measurements whose statistic is greater than the critical value as outliers.

7. The method for detecting the field of view of an optical instrument according to claim 1, characterized in that: The coded display screen is a high PPI LCD or OLED display screen, the image acquisition module is a CCD or CMOS image sensor, and the displacement sensing module is a laser displacement sensor.

Images