An improved endoscope optical performance testing method based on machine vision

Abstract

The present application relates to the technical field of endoscope optical performance testing, and particularly relates to an improved endoscope optical performance testing method based on machine vision. The present application changes the traditional manual operation of endoscope optical performance testing into automatic measurement, and specifically: the images of the endoscope under different test conditions are measured by using a machine vision system to calculate various optical indexes of the endoscope; in the process of measuring the illumination effectiveness index, the Canny edge detection algorithm is combined with the corresponding physical target to improve the calculation accuracy; in the process of calculating the field angle and a value, the imaging of the target is analyzed by using a high-precision camera, and the calculation rate is improved by calculating the geometric parameters and image features; in the process of measuring the sensitive indexes such as effective luminosity, unit relative distortion and color rendering index, the data obtained by the machine vision system are processed by using software to avoid human errors.

Description

Technical Field

[0001] This invention relates to the field of endoscope optical performance testing technology, and in particular to a method for testing endoscope optical performance based on machine vision improvement. Background Technology

[0002] Traditional methods for testing the optical performance of endoscopes often rely on manual operation, which introduces certain errors and has low testing efficiency. With the continuous development of endoscope technology, the requirements for its optical performance are becoming increasingly stringent. Currently, there is no readily available and operational testing method in China for this purpose, thus necessitating a more efficient and accurate testing method. Summary of the Invention

[0003] The purpose of this invention is to provide an improved endoscope optical performance testing method based on machine vision, which improves the accuracy and efficiency of testing by automating the testing of optical indicators.

[0004] An improved endoscope optical performance testing method based on machine vision, characterized by comprising the following steps:

[0005] Step 1: Obtain images of the test target under different test conditions using an endoscope;

[0006] Step 2: Use a machine vision system to measure the test target image obtained in Step 1 to obtain the optical parameters of the endoscope. The optical parameters include: viewing angle, entrance pupil field of view, field of view, a value, angular resolution, effective depth of field, illumination effectiveness, overall luminous efficacy, effective photometric rate, unit relative distortion, and color rendering index.

[0007] Step 3: Determine whether all the indicators obtained in Step 2 are within the range of internationally specified index values. If so, it means that the optical performance of the endoscope meets the requirements. If any one of them is not within the range of internationally specified index values, it indicates that there is an abnormality in that item, and the abnormality needs to be recorded and dealt with.

[0008] Furthermore, the method for calculating the viewing angle and entrance pupil field of view indices includes the following steps:

[0009] In the camera window of the machine vision system, draw a standard concentric circle and a crosshair to align the test target. The center point of the crosshair is aligned with and coincides with the center of the standard concentric circle to assist aiming.

[0010] Align the test target with the crosshair, and measure the distance between the crosshair and the target;

[0011] The viewing angle and entrance pupil field of view are calculated based on the distance between the crosshair and the target using the following formula:

[0012]

[0013] Among them, W p R1 represents the viewing angle and entrance pupil field of view, R2 is the maximum radius of the concentric circles drawn in the camera window, R1 is the minimum radius of the concentric circles drawn in the camera window, d1 is the distance of the test target relative to the endoscope lens before it moves, and d2 is the distance of the test target relative to the endoscope lens after it moves.

[0014] Furthermore, the method for measuring the field of view angle and α-value is as follows:

[0015] Based on the formula for the diameter of the differentiation ring, concentric circles are drawn in the test target image with the center of the camera window of the machine vision system as the center. Then, rays are drawn along a specified direction starting from the center of each circle, intersecting with the various scale rings of the concentric circles. The expression for the formula for the diameter of the differentiation ring is: Where β is the angle between adjacent concentric circles, and d is the optical working distance;

[0016] The Canny edge detection algorithm is used to obtain the arc lines of each dividing ring of the concentric circle. The number of intersections between the ray and each dividing ring of the concentric circle is counted. The field of view angle is obtained by multiplying the number of intersections with the preset concentric circle scale value.

[0017] The value of a is calculated using the formula a = d2 - 2d1, where d1 is the distance of the test target relative to the endoscope lens before it moves, and d2 is the distance of the test target relative to the endoscope lens after it moves.

[0018] Furthermore, the measurement methods for the angular resolution index and the effective depth of field index are as follows:

[0019] Read the line pair readings on the test target image, obtain the corresponding line pair number based on the line pair readings, and use the lookup table method to find the corresponding angular resolution value in the angular resolution table specified in the national standard based on the line pair number, the actual size of the test target, and the imaging parameters of the camera.

[0020] Move the angular resolution test target back and forth relative to the endoscope lens and record its range of movement; calculate the effective depth of field based on the angular resolution value and the range of movement value.

[0021] The formula for calculating the effective depth of field is as follows:

[0022]

[0023] Where d is the optical working distance, a is the value of a in the specification, and r a (d) represents the angular resolution value.

[0024] Furthermore, the test method for the lighting effectiveness index is as follows:

[0025] Luminous flux values ​​at multiple locations were measured using a luminous flux meter, and the edge uniformity U was calculated based on these values. L and illumination mirror body light effect IL eR ;

[0026] Edge uniformity U L The calculation formula is:

[0027]

[0028] Among them, E i E represents the luminous flux value at position i. j This represents the luminous flux value at position j;

[0029] Illumination mirror body light effect IL eR The calculation formula is:

[0030]

[0031] Where is the average brightness at the field of view angle ω, and L0 is the brightness in the direction of the center of the field of view.

[0032] Furthermore, the comprehensive light efficiency index includes the comprehensive endoscopic light efficiency SL of the endoscope. eR Combined edge lighting effect SL e-z A photometer is used to measure photometric values ​​at multiple locations, and the overall lens luminous efficacy (SL) can be calculated based on the obtained photometric values. eR and edge lighting effects SL e-z ;

[0033] Integrated mirror body light effect SL eR The calculation formula is:

[0034] SL eR =IL eR ·OL eR

[0035]

[0036]

[0037] In the formula, IL eR For the lighting effect of the mirror body, OL eR Imaging lens light effect To match the field of view w p Average light transmittance of the full entrance pupil in the same direction, τ v-0 φ is the full entrance pupil transmittance in the direction of the center of the field of view. o and φ i These are the photometric values ​​of the light source before and after the endoscope;

[0038] Edge lighting effects SL e-z The calculation formula is:

[0039] SL e-z =SL sR ·LL e-z ·LL' e-z

[0040]

[0041] In the formula, ω is the field of view angle, ω p Let z be the entrance pupil field of view angle, and z represent the spherical field of view shape of the endoscope image, with a value of [value missing]. When the vertical line of sight is a plane, z = ∞, take LL. e-z =cos 4 ω,LL' e-z =cos 4 ω p .

[0042] Furthermore, the test method for the effective photometric rate index is as follows:

[0043] The endoscope field of view is captured by a camera, and the exit pupil field of view and effective photometric rate of the endoscope are calculated using machine vision algorithms based on the endoscope field of view.

[0044] The formula for calculating the exit pupil field of view is:

[0045]

[0046] The formula for calculating the effective photometric rate is:

[0047]

[0048] Where L is the object surface luminance of the cosine radiator, in cd / m². 2 ),φ′ represents the luminous flux of the endoscope exit pupil, measured in lumens (lm).

[0049] Furthermore, the test method for the unit relative distortion index is as follows:

[0050] Five standard circles are drawn in the camera window. One of the five standard circles is called the center circle. The centers of the other four circles are distributed in the four directions above, below, left and right of the center circle. The clusters from the center of the two upper and lower circles to the center of the center circle, as well as from the center of the two left and right circles to the center of the center circle, are all equal.

[0051] All five standard circles drawn in the camera window are taken as ideal circles. It is assumed that the distortion of the test target image is minimal when it is located in the center position. The test image with minimal distortion is aligned with the center circle of the camera window.

[0052] Subsequently, machine vision technology was used to detect the difference between the remaining test target images and each ideal circle, and the unit relative distortion index could be calculated using the following formula.

[0053] The formula for calculating unit relative distortion is:

[0054]

[0055] In the formula, distortion δy'0 is defined as the difference between the actual image size y'0 and the ideal image size y' of the target. p The ratio of .

[0056] Furthermore, the test method for the color rendering index is as follows:

[0057] Test data were obtained at both the fiber optic end and the eyepiece end using the spectrometer's accompanying software. Based on this data, the color rendering index Ra was calculated for the following conditions: under standard A light source, under D65 standard light source, at the fiber optic output end, and at the eyepiece end. A special color rendering index R0 was also calculated. a The calculation formula is:

[0058]

[0059] In the formula, R i The colorimetric index is given for 8 test color samples.

[0060] This invention provides a machine vision-based method for testing the optical performance of endoscopes, transforming the traditional manual operation into automated measurement. Specifically, it uses a machine vision system to measure images of the endoscope under different test conditions to calculate the endoscope's optical parameters, including viewing angle, entrance pupil field of view, field of view, angular resolution, effective depth of field, illumination effectiveness, overall luminous efficacy, effective photometric rate, unit relative distortion, and color rendering index. In measuring illumination effectiveness, an algorithm such as Canny edge detection combined with a corresponding physical target is used to improve calculation accuracy. In calculating parameters such as field of view and α-value, a high-precision camera is used to analyze the target image, improving calculation speed by calculating geometric parameters and image features. For sensitive parameters such as effective photometric rate, unit relative distortion, and color rendering index, software processes the data obtained by the machine vision system, avoiding human error. Attached Figure Description

[0061] Figure 1 A schematic diagram of a standard concentric circle and crosshair drawn in the camera window is provided as an example.

[0062] Figure 2 This is a schematic diagram illustrating the alignment of the test target and the crosshair of the camera window in an embodiment.

[0063] Figure 3 A schematic diagram showing the intersection of a ray and concentric circles at the center of the camera window in an embodiment is provided.

[0064] Figure 4 This is a schematic diagram illustrating the use of Canny edge detection to obtain concentric circular arcs in an example.

[0065] Figure 5 This is a view of the camera window magnified 16 times during the target reading process in an example embodiment;

[0066] Figure 6 The following is a schematic diagram of the endoscopic field of view imaging and coordinates used in calculating the pupil field of view for an example;

[0067] Figure 7 A schematic diagram showing the arrangement of five standard circles in the camera window for an example embodiment;

[0068] Figure 8 This is a schematic diagram showing the alignment of the center circle of the target in the embodiment with the standard center circle;

[0069] Figure 9 This is a schematic diagram illustrating the import and output of color rendering index data in an example.

[0070] Figure 10 The flowchart illustrates the machine vision-based improved endoscope optical performance testing method as an example. Detailed Implementation

[0071] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0072] like Figure 10 As shown in the figure, this embodiment provides a machine vision-based improved endoscope optical performance testing method, which includes the following steps:

[0073] Step 1, preparations before testing, including: adjusting the brightness of the light source according to the testing requirements, removing background impurities and interference, adjusting the optical working distance between the vision devices in the vision measurement system, such as the camera and the endoscope, and calibrating the machine vision system to ensure the accuracy of the measurement.

[0074] Step 2: Use a CCD camera to acquire images of the test target under different test conditions.

[0075] Step 3: Use a machine vision system to measure the test target image obtained in Step 1 to obtain the optical parameters of the endoscope. The optical parameters include: viewing angle, entrance pupil field of view, field of view, α value, angular resolution, effective depth of field, illumination effectiveness, overall luminous efficacy, effective photometric rate, unit relative distortion, and color rendering index.

[0076] Step 4: Determine whether all the indicators obtained in Step 2 are within the range of internationally specified index values. If so, it means that the optical performance of the endoscope meets the requirements. If any one of them is not within the range of internationally specified index values, it indicates that there is an abnormality in that item, and the abnormality needs to be recorded and dealt with.

[0077] This embodiment introduces a machine vision system, combining machine vision algorithms with a physical target to measure various optical parameters, effectively improving the accuracy and efficiency of endoscope performance measurement. The methods used for measuring each optical parameter in this embodiment are as follows:

[0078] The method for calculating the viewing angle and entrance pupil field of view includes the following steps:

[0079] In the camera window of the machine vision system, a standard concentric circle and a crosshair are drawn to align the test target. The center point of the crosshair is aligned with and coincides with the center of the standard concentric circle. (See reference for the specific implementation of drawing the standard concentric circle and crosshair in the camera window in this embodiment.) Figure 1 The test target should be aligned with the crosshair of the camera window (see reference). Figure 2 , to aid in aiming;

[0080] Align the test target with the crosshair, and measure the distance between the crosshair and the target;

[0081] The viewing angle and entrance pupil field of view are calculated based on the distance between the crosshair and the target using the following formula:

[0082]

[0083] Among them, W p R1 represents the viewing angle and entrance pupil field of view, R2 is the maximum radius of the concentric circles drawn in the camera window, R1 is the minimum radius of the concentric circles drawn in the camera window, d1 is the distance of the test target relative to the endoscope lens before it moves, and d2 is the distance of the test target relative to the endoscope lens after it moves.

[0084] The method for measuring the field of view and α-value is as follows:

[0085] Based on the formula for the diameter of the differentiation ring, concentric circles are drawn in the test target image with the center of the camera window of the machine vision system as the center. Then, rays are drawn along a specified direction starting from the center of the circle, and the rays intersect with the various scale rings of the concentric circles. A schematic diagram of the ray intersecting the concentric circles in this embodiment is shown below. Figure 3 The expression for the differentiation ring diameter formula is: Where β is the angle between adjacent concentric circles, and d is the optical working distance;

[0086] The Canny edge detection algorithm is used to obtain the arc lines of each dividing ring of the concentric circle. In this embodiment, the concentric arc lines obtained by Canny edge detection are as follows: Figure 4 As shown, the number of intersections between the counted ray and each of the concentric rings is multiplied by the preset concentric circle scale value to obtain the field of view angle.

[0087] The value of a is calculated using the formula a = d2 - 2d1, where d1 is the distance of the test target relative to the endoscope lens before it moves, and d2 is the distance of the test target relative to the endoscope lens after it moves.

[0088] The measurement methods for the angular resolution index and the effective depth of field index are as follows:

[0089] The camera window is magnified 16 times, and the view after magnification is shown in the figure. Read the line pair readings on the test target image, obtain the corresponding line pair number based on the line pair readings, and use the lookup table method to find the corresponding angular resolution value in the angular resolution table specified in the national standard based on the line pair number, the actual size of the test target, and the imaging parameters of the camera.

[0090] Table 1 shows the angular resolution values ​​retrieved from the national standard line pair table based on the line pair numbering in this embodiment:

[0091]

[0092] Move the angular resolution test target back and forth relative to the endoscope lens and record its range of movement; calculate the effective depth of field based on the angular resolution value and the range of movement value.

[0093] The formula for calculating the effective depth of field is as follows:

[0094]

[0095] Where d is the optical working distance, a is the value of a in the specification, and r a (d) represents the angular resolution value.

[0096] The test method for the lighting effectiveness index is as follows:

[0097] Luminous flux values ​​at multiple locations were measured using a luminous flux meter, and the edge uniformity U was calculated based on these values. L and illumination mirror body light effect IL eR ;

[0098] Edge uniformity U L The calculation formula is:

[0099]

[0100] Among them, E i E represents the luminous flux value at position i. j This represents the luminous flux value at position j;

[0101] Illumination mirror body light effect IL eR The calculation formula is:

[0102]

[0103] Where is the average brightness at the field of view angle ω, and L0 is the brightness in the direction of the center of the field of view. The brightness is obtained in this embodiment as follows: an integrating sphere is used to illuminate the light source. When the light source enters the small hole of the integrating sphere through the cosine transmission material, the illuminance value is measured using an illuminance meter. At this time, there is a linear relationship between the illuminance value and the brightness value, and the contribution value of the optical mirror illumination path to the edge light effect, i.e., the brightness, can be obtained.

[0104] The overall light efficiency index includes the overall endoscopic light efficiency SL of the endoscope. eR Combined edge lighting effect SL e-z A photometer is used to measure photometric values ​​at multiple locations, and the overall lens luminous efficacy (SL) can be calculated based on the obtained photometric values. eR and edge lighting effects SL e-z ;

[0105] Integrated mirror body light effect SL eR The calculation formula is:

[0106] SL eR =IL eR ·OL eR

[0107]

[0108] In the formula, IL eR For the lighting effect of the mirror body, OL eR Imaging lens light effect To match the field of view w p Average light transmittance of the full entrance pupil in the same direction, τ v-0 φ is the full entrance pupil transmittance in the direction of the center of the field of view. o and φ i These are the photometric values ​​of the light source before and after the endoscope;

[0109] Edge lighting effects SL e-z The calculation formula is:

[0110] SL e-z =SL sR ·LL e-z ·LL' e-z

[0111]

[0112] In the formula, ω is the field of view angle, ω p Let z be the entrance pupil field of view angle, and z represent the spherical field of view shape of the endoscope image, with a value of [value missing]. When the vertical line of sight is a plane, z = ∞, take LL. e-z =cos 4 ω,LL' e-z =cos 4 ω p .

[0113] The test method for the effective photometric rate index is as follows:

[0114] An endoscopic field-of-view image is acquired via a camera. Based on this image, a machine vision algorithm is used to calculate the exit pupil field-of-view angle and effective photometric rate of the endoscope. A schematic diagram of the endoscopic field-of-view image used in calculating the exit pupil field-of-view angle in this embodiment is shown below. Figure 6 As shown.

[0115] The formula for calculating the exit pupil field of view is:

[0116]

[0117] The formula for calculating the effective photometric rate is:

[0118]

[0119] Where L is the object surface luminance of the cosine radiator, in cd / m². 2 ),φ′ represents the luminous flux of the endoscope exit pupil, measured in lumens (lm).

[0120] The test method for the unit relative distortion index is as follows:

[0121] Draw five standard circles in the camera window. One of these circles is designated as the center circle. The centers of the other four circles are distributed around this center circle in four directions: top, bottom, left, and right. The distances from the centers of the top and bottom circles to the center circle, and from the centers of the left and right circles to the center circle, are all equidistant. The final image can be referenced. Figure 7 ;

[0122] Five standard circles drawn in the camera window are considered ideal circles. Assuming the target image at the center has the least distortion, the test image with the least distortion is aligned with the center circle of the camera window. (See...) Figure 8 .

[0123] Subsequently, machine vision technology was used to detect the difference between the remaining test target images and each ideal circle, and the unit relative distortion index could be calculated using the following formula.

[0124] The formula for calculating unit relative distortion is:

[0125]

[0126] In the formula, distortion δy'0 is defined as the difference between the actual image size y'0 and the ideal image size y' of the target. p The ratio of .

[0127] The test method for the color rendering index is as follows:

[0128] like Figure 9 As shown, test data were obtained at both the fiber optic end and the eyepiece end using the spectrometer's accompanying software. Using this data, the color rendering index Ra was calculated for the A standard illuminant, D65 standard illuminant, fiber optic output end, and eyepiece end. A special color rendering index R0 was also calculated. a The calculation formula is:

[0129]

[0130] In the formula, R i The colorimetric index is given for 8 test color samples.

[0131] It should be noted that the endoscope optical performance testing method based on machine vision provided in this embodiment will use some auxiliary tools in the process of testing various optical indicators, such as target fixation devices / test targets for various indicators, endoscope fixation devices, CCD camera connection structure, movable and rotatable light box light source structure, matching photometer, luminous flux meter, integrating sphere, cosine projection material, spectrometer, illuminance meter, industrial control computer and other existing devices. The operation of these devices can be carried out in accordance with existing operations.

[0132] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for testing the optical performance of an improved endoscope based on machine vision, characterized in that, The method comprises the following steps: Step 1, obtaining test target images of an endoscope under different test conditions; Step 2, measuring the test target images obtained in step 1 by using a machine vision system to obtain optical indexes of the endoscope, the optical indexes comprising an entrance pupil field angle, a field angle, an a value, an angular resolution, an effective depth of field, an illumination effectiveness, a comprehensive light efficiency, an effective luminosity rate, a unit relative distortion, and a color rendering index; The field angle and the a value are measured by the following method: According to the differentiation ring diameter formula, a camera window center of the machine vision system is taken as a circle center, concentric circles are drawn in a test target image, then a ray is drawn along a specified direction from the circle center, and the ray intersects with each scale ring of the concentric circles; an expression of the differentiation ring diameter formula is: wherein β is an angle number of adjacent concentric circle intervals, and d is an optical working distance. The Canny edge detection algorithm is used to obtain circular arc lines of each differentiation ring of the concentric circles, the number of intersection points of the rays and each differentiation ring of the concentric circles is counted, and the field angle is obtained by multiplying the number of intersection points by a preset concentric circle scale value; The a value is calculated by the formula a = d2-2d1, wherein d1 is a distance before the test target moves relative to the lens of the endoscope, and d2 is a distance after the test target moves relative to the lens of the endoscope; The comprehensive light efficiency index comprises a comprehensive scope light efficiency SL of the endoscope eR The comprehensive light efficiency index comprises a comprehensive scope light efficiency SL of the endoscope e-z The comprehensive light efficiency index comprises a comprehensive scope light efficiency SL of the endoscope eR The comprehensive light efficiency index comprises a comprehensive scope light efficiency SL of the endoscope e-z ; The comprehensive mirror body light efficiency SL eR The calculation formula is: SL eR = IL eR • OL eR In the formula, IL eR For the lighting effect of the mirror body, OL eR Imaging lens light effect To match the field of view w p Average light transmittance of the full entrance pupil in the same direction, τ v-0 The full entrance pupil transmittance is the light transmittance in the direction of the center of the field of view. and These are the photometric values ​​of the light source before and after the endoscope; Edge comprehensive light effect SL e-z The calculation formula is: SL e-z = SL sR • LL e-z • LL' e-z where ω is the field of view angle, ω p is the entrance pupil field of view angle, and z represents the spherical field of view shape of the endoscope imaging, which takes a value of When the vertical view axis is a plane, z = ∞, take LL e-z = cos 4 ω, LL' e-z = cos 4 ω p ; Step 3, determining whether each index obtained in step 2 is within an international index value range, if yes, it indicates that the optical performance of the endoscope meets the requirements, and if any one of the indexes is not within the international index value range, it indicates that the index is abnormal, and the abnormality needs to be recorded and processed.

2. The method for testing the optical performance of an endoscope based on improved machine vision according to claim 1, characterized in that, The calculation method of the entrance pupil field angle index comprises the following steps: A standard concentric circle and a crosshair for aligning the test target are drawn in a camera window of the machine vision system, and the center point of the crosshair is aligned with and coincides with the center of the standard concentric circle to assist aiming; The test target is aligned with the crosshair, and the distance between the crosshair and the target is measured; The entrance pupil field angle is calculated according to the distance between the crosshair and the target according to the following formula: wherein W p represents the entrance pupil field angle, R2 is the maximum radius of the concentric circles drawn in the camera window, R1 is the minimum radius of the concentric circles drawn in the camera window, d1 is the distance of the test target before moving relative to the endoscope lens, and d2 is the distance of the test target after moving relative to the endoscope lens.

3. The method of claim 1, wherein, The measurement method of the angular resolution index and the effective depth of field index comprises the following steps: A line pair reading on the test target image is read, a corresponding line pair number is obtained according to the line pair reading, and a corresponding angular resolution value is found in a national standard angular resolution table by using a lookup table method based on the line pair number, the actual size of the test target, and imaging parameters of the camera; The angular resolution test target is moved relative to the lens of the endoscope before and after, and a moving range value is recorded; and the effective depth of field is calculated according to the angular resolution value and the moving range value; The calculation formula of the effective depth of field is as shown in the following formula: where d is the optical working distance, a is the a value in the index, and r a (d) is the angular resolution value.

4. The method for testing the optical performance of an endoscope based on improved machine vision according to claim 1, characterized in that, The test method of the illumination effectiveness index comprises the following steps: measuring the luminous flux values at a plurality of positions using a luminous flux meter, calculating the edge uniformity U from the luminous flux values L and the illumination mirror body light efficiency IL eR ; Edge uniformity U L The formula for calculating the edge uniformity U is: where E i represents the luminous flux value at position i, E j represents the luminous flux value at position j; Light mirror body light efficiency IL eR The calculation formula is: where L ω is the average luminance of the field of view ω, and L0is the luminance in the direction of the center of the field of view.

5. The method for testing the optical performance of an endoscope based on improved machine vision according to claim 1, characterized in that, The test method of the effective luminosity rate index comprises the following steps: An endoscope field of view imaging image is obtained by using a camera, and the exit pupil field angle and the effective luminosity rate of the endoscope are calculated by using a machine vision algorithm based on the endoscope field of view imaging image; The calculation formula of the exit pupil field angle is as shown in the following formula: The calculation formula of the effective luminosity rate is as shown in the following formula: where L is the luminance of the cosine radiator in candela per square meter (cd / m 2 ), and φ' is the luminous flux of the endoscope exit pupil in lumens (lm).

6. The method for testing the optical performance of an endoscope based on improved machine vision according to claim 1, characterized in that, The test method of the unit relative distortion index comprises the following steps: Five standard circles are drawn in the camera window, one of the five standard circles is recorded as a center circle, and the centers of the other four circles are distributed in four directions of up, down, left and right around the center circle, and the distances from the centers of the upper and lower circles to the center of the center circle and the distances from the centers of the left and right circles to the center of the center circle are equal; The five standard circles drawn in the camera window are all regarded as ideal circles, and it is assumed that the distortion of the test target image located at the center position is the smallest, and the distortion test image with the smallest distortion is aligned with the center circle of the camera window; Then, the machine vision technology is used to detect the difference between the remaining test target image and each ideal circle, and the unit relative distortion index can be calculated according to the following formula: The calculation formula of the unit relative distortion is as follows: where the distortion δy'0is defined as the ratio of the actual image size y'0of the side-mark target to the ideal image size y'0. p where the distortion δy'0is defined as the ratio of the actual image size y'0of the side-mark target to the ideal image size y'0.

7. The method of claim 1, wherein the method is based on machine vision improvement. The test method of the color rendering index is as follows: The test data of the fiber end and the eyepiece end are obtained by using the software of the spectrometer, and the color rendering index Ra values under the A standard light source, the D65 standard light source, the fiber output end and the eyepiece end are calculated by using the test data of the fiber end and the eyepiece end, respectively. The calculation formula of the color rendering index R a is: wherein R i is the color rendering index under 8 test color samples.

Images