VSCEL far field test method and device

Abstract

The invention discloses a VSCEL far-field test method and device, and the method comprises the steps: providing an excitation signal for a target product, so as to enable the target product to project a laser spot to an optical screen; a distribution image of the laser spots on the optical screen is shot through an infrared camera module, a sampling image is obtained, and the shooting center of the infrared camera module is aligned with the laser emission center of the target product; preprocessing the sampling image to obtain a first intermediate image, the preprocessing including flat field correction and distortion removal processing; performing data intensity extraction on the first intermediate image to obtain energy distribution test data; determining laser divergence angle test data according to the energy distribution test data and a preset relation model; and performing image convolution and numerical operation processing on the first intermediate image to determine human eye safety test data. According to the invention, multiple test data can be obtained through the first intermediate image, multiple tests can be completed at a time, and the test efficiency can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of chip testing, and in particular to a VSCEL far-field testing method and equipment. Background Art

[0002] VCSEL (vertical cavity surface emitting laser) chip modules are widely used in products such as face recognition, 3D modeling and lidar. VCSEL chip modules need to be tested during the production stage. For example, a beam analyzer is used to measure the far-field spot distribution of the VCSEL chip module. However, due to the high complexity of the beam analyzer and the high geometric alignment requirements, the beam analyzer cannot meet the needs of situations that require fast feedback or high-speed production environments. In addition, the beam analyzer is highly integrated. Due to its own design limitations, it has restrictions on the measured spot size or divergence angle, and cannot meet the testing requirements of VCSEL chip modules with large emission angles. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention proposes a VSCEL far-field test method and device, which can complete multiple tests at one time and improve the test efficiency.

[0004] On the one hand, an embodiment of the present invention provides a VSCEL far-field testing method, which is applicable to a VSCEL far-field testing device having a light screen and an infrared camera module, wherein the infrared camera module and the target product are distributed on opposite sides of the light screen, and the VSCEL far-field testing method includes: Providing an excitation signal to the target product so that the target product projects a laser spot onto the light screen; The infrared camera module is used to capture a distribution image of the laser spot on the light screen to obtain a sampling image, wherein the capturing center of the infrared camera module is aligned with the laser emission center of the target product; Preprocessing the sampled image to obtain a first intermediate image, wherein the preprocessing includes flat field correction and de-distortion processing; Performing data intensity extraction on the first intermediate image to obtain energy distribution test data; Determining laser divergence angle test data according to the energy distribution test data and a preset relationship model; Perform image convolution and numerical calculation processing on the first intermediate image to determine human eye safety test data.

[0005] According to some embodiments of the present invention, the step of photographing a distribution image of the laser spot on the light screen by the infrared camera module to obtain a sampling image includes: Based on a preset exposure time, the infrared camera module is used to capture a distribution image of the laser spot on the light screen to obtain a sampling image, wherein the exposure time is an integer multiple of the frequency value of the target product and the pixel value of the brightest point in the sampling image is less than the upper limit of the pixel range of the image captured by the infrared camera module.

[0006] According to some embodiments of the present invention, performing data intensity extraction on the first intermediate image to obtain energy distribution test data includes: Establishing a rectangular coordinate system with the image center of the first intermediate image; The X-axis intensity data and the Y-axis intensity data of the first intermediate image are extracted to obtain energy distribution test data.

[0007] According to some embodiments of the present invention, performing data intensity extraction on the first intermediate image to obtain energy distribution test data further includes: At least one of a thermal diagram, a curve trend diagram and an intensity distribution diagram is output according to the X-axis intensity data and the Y-axis intensity data.

[0008] According to some embodiments of the present invention, determining the laser divergence angle test data according to the energy distribution test data and a preset relationship model includes: Determine the first half-width data of the X dimension according to the X-axis intensity data; Determine the second half-width at half maximum data of the Y dimension according to the Y-axis intensity data; Laser divergence angle test data is determined according to the first half-width data, the second half-width data and a preset relationship model.

[0009] According to some embodiments of the present invention, the laser divergence angle test data includes horizontal divergence angle test data and vertical divergence angle test data, and determining the laser divergence angle test data according to the first half-width data, the second half-width data and a preset relationship model includes: Determine the horizontal divergence angle test data of the laser according to the first half-width data and a preset relationship model; Determining the vertical divergence angle test data of the laser according to the second half-width data and a preset relationship model; Wherein, the mathematical expression of the relationship model is: , where θ is used to characterize the divergence angle test data, W is used to characterize the half-height width data, and L is used to characterize the distance between the emission end of the target product and the light screen.

[0010] According to some embodiments of the present invention, performing image convolution and numerical operation processing on the first intermediate image to determine eye safety test data includes: Generate a convolution kernel according to a preset image circle diameter, wherein the image circle diameter is proportional to the size of the human eye pupil; Convolving the first intermediate image based on the convolution kernel to obtain a second intermediate image, wherein pixel values ​​of the second intermediate image are used to represent an average value of all pixel values ​​within a range of a diameter of the image circle centered at each pixel point of the first intermediate image; determining a maximum value of pixels in the second intermediate image; The total power corresponding to the pixel maximum value is determined according to the pixel maximum value, the image circle diameter, a preset power coefficient and a preset exposure time. The total power is used to characterize the sum of the powers within the range of the image circle diameter centered on the pixel point of the pixel maximum value.

[0011] According to some embodiments of the present invention, determining the total power corresponding to the pixel maximum value according to the pixel maximum value, the image circle diameter, a preset power coefficient and a preset exposure time includes: The mathematical expression of the power sum is: Where Vmax is used to represent the maximum value of the pixel, KernelW is used to represent the image circle diameter, K is used to represent the power coefficient, and E1 is used to represent the exposure time.

[0012] According to some embodiments of the present invention, the method further comprises: determining the total power corresponding to the maximum pixel value according to the maximum pixel value, the image circle diameter, a preset power coefficient and a preset exposure time, and then further comprising: Outputting the power sum as eye safety test data; Alternatively, the power sum is compared with a preset human eye safety power threshold, and the comparison result is used as personnel safety test data.

[0013] On the other hand, an embodiment of the present invention provides a VSCEL far-field testing device, including a light screen, an infrared camera module and a controller, wherein the controller is used to execute the above-mentioned VSCEL far-field testing method.

[0014] The embodiments of the present invention have at least the following beneficial effects: By preprocessing the sampled image to obtain a first intermediate image with higher quality, performing data intensity extraction on the first intermediate image to obtain energy distribution test data, determining laser divergence angle test data based on the energy distribution test data, and performing image convolution and numerical calculation on the first intermediate image to determine human eye safety test data, multiple test data can be obtained through the first intermediate image, and multiple tests can be completed at one time, which is conducive to improving test efficiency.

[0015] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which: Figure 1 A schematic diagram of the steps of a VSCEL far-field test method according to an embodiment of the present invention; Figure 2 This is a VSCEL far-field test principle diagram of an embodiment of the present invention; Figure 3 is one of the schematic diagrams of the first intermediate image according to an embodiment of the present invention; Figure 4 A schematic diagram of a curve trend chart of an embodiment of the present invention; Figure 5 Schematic diagram of a convolution kernel according to an embodiment of the present invention; Figure 6 This is a second schematic diagram of the first intermediate image according to an embodiment of the present invention. DETAILED DESCRIPTION

[0017] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0018] In the description of the present invention, "several" means one or more, "multiple" means more than two, greater than, less than, and exceeding are understood as not including the number itself, and "above", "below", and "within" are understood as including the number itself. If there is a description of "first", "second", etc., it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0019] In the description of the present invention, unless otherwise clearly defined, words such as “setting”, “installation” and “connection” should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above words in the present invention based on the specific content of the technical solution.

[0020] Please refer to Figure 1 and Figure 2This embodiment discloses a VSCEL far-field test method, which is applicable to a VSCEL far-field test device having a light screen 110 and an infrared camera module 120. The infrared camera module 120 and the target product 10 are distributed on opposite sides of the light screen 110. The VSCEL far-field test method includes steps S100 to S600. It should be noted that the steps in this embodiment are numbered only for the convenience of review and understanding, and do not limit the execution order of the steps. The contents of each step are described in detail below: S100, providing an excitation signal to the target product 10, so that the target product 10 projects a laser spot onto the light screen 110; S200, photographing a distribution image of the laser spot on the light screen 110 through the infrared camera module 120 to obtain a sampling image, wherein the photographing center of the infrared camera module 120 is aligned with the laser emission center of the target product 10; S300, preprocessing the sampled image to obtain a first intermediate image, the preprocessing including flat field correction and de-distortion processing; S400, extracting data intensity from the first intermediate image to obtain energy distribution test data; S500, determining laser divergence angle test data according to energy distribution test data and a preset relationship model; S600: Perform image convolution and numerical calculation processing on the first intermediate image to determine human eye safety test data.

[0021] For example, the target product 10 is a VCSEL chip module, and a laser can be projected to the light screen 110 through the transmitting end to form a light spot on the light screen 110. The distance between the target product 10 and the light screen 110 is a fixed distance (such as Figure 2 As shown by the mark L in the middle, the laser emitted by the target product 10 may form a certain angle (i.e., divergence angle, such as Figure 2 As shown by the mark θ in the figure, the light spot falls within a certain area of ​​the light screen 110 (i.e., the projection area of ​​the light spot, such as Figure 2 The triangle area formed by the dotted lines on the left side of the middle light screen 110 is shown in FIG. 1 . It should be noted that the shooting area of ​​the infrared camera module 120 (such as Figure 2 The infrared camera module 120 is aligned with the laser emission center of the target product 10 (as shown in the triangle area formed by the dotted line on the right side of the middle light screen 110). Figure 2), which can ensure the symmetry of the captured image, reduce interference factors in image processing, and improve the convenience of image processing. The infrared camera module 120 uses thermal imaging technology to visualize invisible heat on the image. Before extracting data intensity, the noise of the sampled image can be reduced by preprocessing the sampled image. For example, due to the structural limitations of the infrared camera module 120, the center of the lens receives more light than the edge of the lens, resulting in the center of the image being brighter than the edge, presenting a halo effect, causing the original sampled image to be distorted. The distortion of the image can be reduced by flat field correction. For example, during the photo shooting process, the light passing through the lens of the infrared camera module 120 will produce barrel distortion, thereby causing image distortion. The distortion of the image can be reduced by de-distortion processing.

[0022] The image distortion of the first intermediate image obtained after preprocessing is low. The analysis using the first intermediate image can improve the accuracy of the analysis. Among them, the sampling image is obtained by shooting with the infrared camera module 120, and the sampling image contains the light intensity information of the light spot. Then the first intermediate image after preprocessing also contains the light intensity information. The data intensity is extracted from the first intermediate image to obtain the energy distribution test data, so as to observe the light spot distribution characteristics of the laser emitted by the target product 10. On the basis of the energy distribution test data, the laser divergence angle test data can be determined according to the preset relationship model, so that the energy distribution test and the laser divergence angle test can be completed quickly, and the test efficiency is high. In addition, the human eye safety test can also be performed according to the first intermediate image. For example, the human eye safety test data can be determined by performing image convolution and numerical operation processing on the first intermediate image, and the energy distribution test, the laser divergence angle test and the human eye safety test can be completed at one time. The test operation difficulty is low and the test efficiency is high.

[0023] By preprocessing the sampled image to obtain a first intermediate image with higher quality, performing data intensity extraction on the first intermediate image to obtain energy distribution test data, determining laser divergence angle test data based on the energy distribution test data, and performing image convolution and numerical calculation on the first intermediate image to determine human eye safety test data, multiple test data can be obtained through the first intermediate image, and multiple tests can be completed at one time, which is conducive to improving test efficiency.

[0024] Step S200, using the infrared camera module 120 to capture a distribution image of the laser spot on the light screen 110 to obtain a sampling image, including: S210. Based on the preset exposure time, the distribution image of the laser spot on the light screen 110 is captured by the infrared camera module 120 to obtain a sampling image, wherein the exposure time value is an integer multiple of the frequency value of the target product 10 and the pixel value of the brightest point in the sampling image is less than the upper limit value of the pixel range of the image captured by the infrared camera module 120.

[0025] For example, it was found in the experiment that the image collected by the infrared camera module 120 is prone to unevenness on the left and right, dark on one side and bright on the other, and the collected data is inaccurate. Research has found that this phenomenon is caused by the stroboscopic phenomenon caused by the inconsistency between the sampling time of the infrared camera module 120 and the infrared frequency of the target product 10. Therefore, before taking pictures, the exposure time of the infrared camera module 120 needs to be configured. In addition, the exposure time should not be set too high, and the pixel value of the brightest spot of the collected image (i.e., the sampled image) should be less than (i.e., not greater than or equal to) the upper limit of the pixel value range, otherwise the sampled data will be distorted. For example, the resolution of the infrared camera module 120 is 8192 columns × 5468 rows, and the bit depth of each pixel is 10 bits, that is, the range of each pixel value is 2 to the 12th power, and the pixel value range is: 0~4096, that is, the pixel value of the brightest spot of the sampled image should be less than the upper limit of 4096.

[0026] Step S400, extracting data intensity from the first intermediate image to obtain energy distribution test data, including: S410, establishing a rectangular coordinate system with the image center of the first intermediate image; S420, extracting X-axis intensity data and Y-axis intensity data of the first intermediate image to obtain energy distribution test data.

[0027] For example, please refer to Figure 3 , one example of the first intermediate image is shown in the figure, and the crosshairs in the figure are used to illustrate the rectangular coordinate system. The first intermediate image is an image composed of pixels. For example, the resolution of the infrared camera module 120 is 8192 columns × 5468 rows, so the resolution of the first intermediate image is also 8192 columns × 5468 rows, that is, the pixel point at the center of the image of the first intermediate image is used as the coordinate origin, and the Y axis is established in the column direction. The Y axis has 8192 pixels, and each pixel can extract an intensity data of the Y axis. Similarly, the X axis is established in the row direction. The X axis has 5468 pixels, and each pixel can extract an intensity data of the X axis. By extracting the X-axis intensity data and the Y-axis intensity data of the first intermediate image, the energy distribution test data is obtained, thereby realizing the energy distribution test of the laser in the far field.

[0028] Step S400, extracting data intensity from the first intermediate image to obtain energy distribution test data, and then further comprising: S430, outputting at least one of a thermal map, a curve trend map and an intensity distribution map according to the X-axis intensity data and the Y-axis intensity data.

[0029] Exemplarily, the X-axis intensity data and the Y-axis intensity data are combined and output in the form of a heat map, so that the spot distribution characteristics of the laser emitted by the target product 10 in the X-axis direction and the Y-axis direction can be intuitively observed, wherein the X-axis pixel point sequence number of the first intermediate image is used as the horizontal axis of the heat map, and the Y-axis pixel point sequence number is used as the vertical axis of the heat map, and the intensity data is distinguished by different colors. The curve trend chart is divided into an X-axis curve trend chart and a Y-axis curve trend chart, such as Figure 4 As shown in the figure, the curve trend graph uses the pixel number of the first intermediate image as the horizontal axis and the intensity data as the vertical axis. The intensity distribution graph is a three-dimensional graph and can be regarded as a three-dimensional representation of the heat map. According to the needs of the actual application, one or more of the heat map, curve trend graph and intensity distribution graph are output to enhance the visualization effect of the data.

[0030] Step S500, determining laser divergence angle test data according to energy distribution test data and a preset relationship model, including: S510, determining the first half-width data of the X dimension according to the X-axis intensity data; S520, determining the second half-width at half maximum data of the Y dimension according to the Y-axis intensity data; S530, determining laser divergence angle test data according to the first half-width data, the second half-width data and a preset relationship model.

[0031] For example, please refer to Figure 2 , the figure is a test principle diagram from a top view, assuming that the distance between the target product 10 and the light screen 110 is L (known value), the horizontal divergence angle of the target product 10 is θ, the width of the light spot projected by the laser emitted by the target product 10 on the light screen 110 is W, and the shooting area of ​​the infrared camera module 120 can cover the width range of the projected light spot. According to trigonometric functions and inverse trigonometric functions, it can be determined that: θ=2*arctan[(W / 2) / L). In this way, it is only necessary to determine the width W of the projected light spot to determine the horizontal divergence angle θ. Similarly, the vertical divergence angle of each target product 10 can be determined. Among them, the projection spot width W is proportional to the half-height width of the X-axis intensity data. According to the X-axis intensity data, the first half-height width data of the X dimension can be determined to determine the horizontal divergence angle of the laser. Similarly, according to the Y-axis intensity data, the second half-height width data of the Y dimension can be determined to determine the vertical divergence angle of the laser, that is, the laser divergence angle test data can be determined.

[0032] That is, the laser divergence angle test data includes horizontal divergence angle test data and vertical divergence angle test data. Step S530, according to the first half-height width data, the second half-height width data and the preset relationship model, determines the laser divergence angle test data, including: S531, determining the horizontal divergence angle test data of the laser according to the first half-width data and a preset relationship model; S532, determining the vertical divergence angle test data of the laser according to the second half-width data and a preset relationship model; Among them, the mathematical expression of the relational model is: , where θ is used to characterize the divergence angle test data, W is used to characterize the half-height width data, and L is used to characterize the distance between the emission end of the target product 10 and the light screen 110.

[0033] In order to improve the accuracy of data analysis, before determining the first half-height width data and the second half-height width data, it is necessary to smooth the X-axis intensity data and the Y-axis intensity data to remove noise interference. For example, if the X-axis intensity data and the Y-axis intensity data have large fluctuations, a sliding average filter is required to make the curve smoother. The maximum value of the one-dimensional data (X-axis intensity data or Y-axis intensity data) after sliding smoothing is solved, that is, the maximum value Y' is determined imax , then determine half of the maximum value, which is 50%*Y' imax The value of, the coordinate on the horizontal axis, such as Figure 4 The horizontal coordinate difference between the points X1 and X2 is ΔX. The distance unit obtained at this time is the pixel of the image, and there is a proportional relationship between the image pixel distance and the actual distance (assuming the proportional coefficient is k), then the half-height width W=ΔX*k. Therefore, according to the half-height width data and the relationship model, the horizontal divergence angle test data of the laser can be determined. Similarly, the vertical divergence angle test data of the laser can also be determined.

[0034] Step S600, performing image convolution and numerical calculation processing on the first intermediate image to determine eye safety test data, including: S610, generating a convolution kernel according to a preset image circle diameter, where the image circle diameter is proportional to the size of a human eye pupil; S620, convolve the first intermediate image based on the convolution kernel to obtain a second intermediate image, where the pixel values ​​of the second intermediate image are used to represent the average value of all pixel values ​​within the range of the image circle diameter centered at each pixel point of the first intermediate image; S630, determining a maximum pixel value in the second intermediate image; S640, determining the total power corresponding to the pixel maximum value according to the pixel maximum value, the image circle diameter, the preset power coefficient and the preset exposure time, where the total power is used to represent the sum of the powers within the range of the image circle diameter centered on the pixel point of the pixel maximum value.

[0035] Exemplarily, each time the target product 10 is tested, the image is captured, and then preprocessed such as flat field correction and de-distortion processing is performed. The position of the maximum energy in the 7mm range (human eye pupil size) is found on the preprocessed image (i.e., the first intermediate image), and the corresponding power value is calculated using the K coefficient conversion. For example, an infrared camera module 120 is used to capture an infrared spot intensity distribution image of the target product 10, wherein the exposure time of the infrared camera module 120 is set to a multiple of the frequency of the target product 10, and the exposure time is recorded as E1. The captured image is subjected to flat field correction and de-distortion processing, and the resulting image is recorded as Y1. Image Y1 is convolved so that each pixel value after the convolution represents the mean of all pixel values ​​within the 7mm range of its surrounding area. The specific steps include: determining the size of the convolution kernel, and determining the diameter of the image circle corresponding to 7mm KernerlW=7 / PixelSize, wherein PixelSize is the proportional coefficient. The convolution kernel is generated using the diameter parameter KernerlW, and the length and width of the convolution kernel are both KernerlW, such as Figure 5 As shown, the value of the white area is Kv=1 / (KernerlW*KernerlW*π), and the value of the black area is 0. The convolution kernel is used to perform a convolution operation on image Y1. The convolved image is recorded as Yc (i.e., the second intermediate image). Each pixel value after convolution represents the average value of all pixel values ​​within the 7mm range around it. Find the maximum pixel value in image Yc and get the maximum pixel value V max , using the calibrated power coefficient K and pixel maximum value V max , calculate the sum of the power in the 7mm range represented by the maximum value, that is: Step S640, determining the total power corresponding to the maximum pixel value according to the maximum pixel value, the image circle diameter, the preset power coefficient and the preset exposure time, including: The mathematical expression for the total power is: Where Vmax is used to represent the maximum value of the pixel, KernelW is used to represent the image circle diameter, K is used to represent the power coefficient, and E1 is used to represent the exposure time.

[0036] Step S640, determining the total power corresponding to the maximum pixel value according to the maximum pixel value, the image circle diameter, the preset power coefficient and the preset exposure time, and then further comprising: Output the total power as eye safety test data; Alternatively, the total power is compared with a preset eye safety power threshold, and the comparison result is used as personnel safety test data.

[0037] Exemplarily, the power sum can be output as the final test result. For example, the maximum pixel value and the coordinate data of the maximum pixel value are determined in the second intermediate image, and a graphic annotation is performed in the first intermediate image according to the coordinate data of the maximum pixel value, such as Figure 6 The circle mark and / or cross mark in the middle include the location of the maximum pixel value and the total power, so that users can intuitively understand the maximum test result. Figure 6 For illustration only, Figure 6 The font size in is adjusted according to the actual application requirements. In this embodiment, Figure 6 The text shown is only an example of the location and does not represent the actual meaning. In some application scenarios, the total power can be compared with a preset threshold and then the comparison result can be output, wherein the preset human eye safety power threshold can refer to the relevant international standards for infrared laser radiation.

[0038] The present embodiment provides a VSCEL far-field test device, including a light screen 110, an infrared camera module 120 and a controller, and the controller is used to execute the above-mentioned VSCEL far-field test method. By preprocessing the sampled image, a first intermediate image with higher quality is obtained, and the data intensity of the first intermediate image is extracted to obtain energy distribution test data, and the laser divergence angle test data is determined according to the energy distribution test data, and the image convolution and numerical operation are performed on the first intermediate image to determine the human eye safety test data. Multiple test data can be obtained through the first intermediate image, and multiple tests can be completed at one time, which is conducive to improving the test efficiency.

[0039] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of ordinary technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. A VSCEL far-field test method, applicable to a VSCEL far-field test device having a light screen and an infrared camera module, wherein the infrared camera module and the target product are distributed on opposite sides of the light screen, characterized in that: The VSCEL far-field test method comprises: Providing an excitation signal to the target product so that the target product projects a laser spot onto the light screen; The infrared camera module is used to capture a distribution image of the laser spot on the light screen to obtain a sampling image, wherein the capturing center of the infrared camera module is aligned with the laser emission center of the target product; Preprocessing the sampled image to obtain a first intermediate image, wherein the preprocessing includes flat field correction and de-distortion processing; Performing data intensity extraction on the first intermediate image to obtain energy distribution test data; Determining laser divergence angle test data according to the energy distribution test data and a preset relationship model; Perform image convolution and numerical calculation processing on the first intermediate image to determine human eye safety test data.

2. The VSCEL far-field testing method according to claim 1, characterized in that: The step of photographing the distribution image of the laser spot on the light screen by the infrared camera module to obtain a sampling image includes: Based on a preset exposure time, the infrared camera module is used to capture a distribution image of the laser spot on the light screen to obtain a sampling image, wherein the exposure time is an integer multiple of the frequency value of the target product and the pixel value of the brightest point in the sampling image is less than the upper limit of the pixel range of the image captured by the infrared camera module.

3. The VSCEL far-field testing method according to claim 1 or 2, characterized in that: The step of extracting data intensity from the first intermediate image to obtain energy distribution test data includes: Establishing a rectangular coordinate system with the image center of the first intermediate image; The X-axis intensity data and the Y-axis intensity data of the first intermediate image are extracted to obtain energy distribution test data.

4. The VSCEL far-field testing method according to claim 3, characterized in that: The step of extracting data intensity from the first intermediate image to obtain energy distribution test data further includes: At least one of a thermal diagram, a curve trend diagram and an intensity distribution diagram is output according to the X-axis intensity data and the Y-axis intensity data.

5. The VSCEL far-field testing method according to claim 3, characterized in that: Determining the laser divergence angle test data according to the energy distribution test data and a preset relationship model includes: Determine the first half-width data of the X dimension according to the X-axis intensity data; Determine the second half-width at half maximum data of the Y dimension according to the Y-axis intensity data; Laser divergence angle test data is determined according to the first half-width data, the second half-width data and a preset relationship model.

6. The VSCEL far-field testing method according to claim 5, characterized in that: The laser divergence angle test data includes horizontal divergence angle test data and vertical divergence angle test data, and the laser divergence angle test data is determined according to the first half-width data, the second half-width data and a preset relationship model, including: Determine the horizontal divergence angle test data of the laser according to the first half-width data and a preset relationship model; Determining the vertical divergence angle test data of the laser according to the second half-width data and a preset relationship model; Wherein, the mathematical expression of the relationship model is: , where θ is used to characterize the divergence angle test data, W is used to characterize the half-height width data, and L is used to characterize the distance between the emission end of the target product and the light screen.

7. The VSCEL far-field testing method according to any one of claims 1, 2, 4 to 6, characterized in that: The performing image convolution and numerical calculation processing on the first intermediate image to determine the human eye safety test data includes: Generate a convolution kernel according to a preset image circle diameter, wherein the image circle diameter is proportional to the size of the human eye pupil; Convolving the first intermediate image based on the convolution kernel to obtain a second intermediate image, wherein pixel values ​​of the second intermediate image are used to represent an average value of all pixel values ​​within a range of a diameter of the image circle centered at each pixel point of the first intermediate image; determining a maximum value of pixels in the second intermediate image; The total power corresponding to the pixel maximum value is determined according to the pixel maximum value, the image circle diameter, a preset power coefficient and a preset exposure time. The total power is used to characterize the sum of the powers within the range of the image circle diameter centered on the pixel point of the pixel maximum value.

8. The VSCEL far-field testing method according to claim 7, characterized in that: The determining the total power corresponding to the maximum pixel value according to the maximum pixel value, the image circle diameter, a preset power coefficient and a preset exposure time includes: The mathematical expression of the sum of the powers is: Where Vmax is used to represent the maximum value of the pixel, KernelW is used to represent the image circle diameter, K is used to represent the power coefficient, and E1 is used to represent the exposure time.

9. The VSCEL far-field testing method according to claim 7, characterized in that: The method further comprises: determining the power sum corresponding to the pixel maximum value according to the pixel maximum value, the image circle diameter, a preset power coefficient and a preset exposure time, and then further comprising: Outputting the power sum as eye safety test data; Alternatively, the power sum is compared with a preset human eye safety power threshold, and the comparison result is used as personnel safety test data.

10. A VSCEL far-field testing device, comprising a light screen, an infrared camera module and a controller, wherein the controller is used to execute the VSCEL far-field testing method according to any one of claims 1 to 9.

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