M 2 Measurement system and its laser spot image acquisition method and device

Abstract

The present disclosure provides an M2 measurement system and a laser spot image acquisition method and device thereof, the laser spot image acquisition method comprising: collecting a current frame laser spot image of a first optical path displacement point in a beam propagation direction of a laser system to be measured, the first optical path displacement point being any optical path displacement point; identifying a laser spot in the current frame laser spot image; determining a peak gray value of a laser spot area in the current frame laser spot image; judging whether the peak gray value of the laser spot area meets a predetermined exposure requirement; if the peak gray value of the laser spot area does not meet the predetermined exposure requirement, determining a target exposure time, adjusting an exposure time of a camera to the target exposure time, collecting a next frame laser spot image at the first optical path displacement point under the target exposure time, and sending the next frame laser spot image to an upper computer of the M2 measurement system; and if the peak gray value of the laser spot area meets the predetermined exposure requirement, sending the current frame laser spot image to the upper computer of the M2 measurement system. The present disclosure can quickly adjust the exposure time of the camera to meet the M2 measurement requirement.

Description

Technical Field

[0001] This disclosure relates to the field of laser measurement technology, and particularly to an M 2 Measurement system and its laser spot image acquisition method and device. Background Technology

[0002] In fields such as laser processing, optical communication, and precision measurement, beam quality (also known as the M² factor, hereinafter referred to as M²) is a key parameter for evaluating the performance of a laser system. 2 The measurement system can be used to measure the M² factor of a laser beam.

[0003] M 2 The measurement system needs to acquire laser spot images at multiple locations along the beam propagation direction. By analyzing these images, the change in laser spot size along the beam propagation direction is obtained to determine the M² factor of the laser system. Therefore, the image quality of the laser spot directly affects M². 2 The accuracy of the M² factor obtained by the measurement system, that is, the image quality of the spot area in the laser spot image, directly affects M. 2 Measurement accuracy of the measurement system. Due to the highly uneven energy distribution of the laser spot, the brightness difference between the central and edge regions can reach several orders of magnitude. Therefore, the camera exposure parameters of the beam analyzer in the M² measurement system are a key factor affecting the image quality of the spot region in the laser spot image.

[0004] In M² measurement systems, laser spot images need to be acquired rapidly and continuously at multiple locations along the beam propagation path. This necessitates that automatic exposure control be completed within an extremely short timeframe; any significant delay directly impacts the throughput, efficiency, and accuracy of the entire measurement system. Therefore, automatic exposure technology becomes a core component of M² measurement systems. Through automatic exposure, the camera exposure parameters of the beam analyzer in the M² measurement system can be automatically and rapidly adjusted to the optimal state at different displacement points, ensuring that the laser spot image is neither overexposed nor underexposed, thus providing reliable data for the accurate calculation and analysis of the M² factor.

[0005] Currently, automatic exposure techniques mainly include automatic exposure methods based on global image grayscale statistics and automatic exposure methods based on fixed regions of interest. Automatic exposure methods based on global image grayscale statistics often sacrifice the imaging quality of the bright spot area, failing to meet the requirements of M... 2 The measurement system has requirements for the image quality of the spot area. However, automatic exposure methods based on a fixed region of interest assume that the laser spot always appears within a preset fixed area, and they cannot adapt to the movement of the spot within the field of view. Once M... 2During the measurement process, the laser spot moves within the field of view due to factors such as collimation errors. This causes the spot area in the laser spot image to deviate from the preset fixed area, making exposure adjustment impossible for that area. Consequently, the goal of improving the image quality of the spot area in the laser spot image cannot be achieved; instead, it may further degrade the image quality of the spot area, affecting M. 2 Measurement accuracy of the measurement system.

[0006] In summary, a method is needed for application to M. 2 The spot image acquisition method of the measurement system can adaptively adjust the exposure time during M² measurement, accurately and quickly improving the image quality of the spot area in the laser spot image, thereby improving M² measurement efficiency. 2 Measurement accuracy of the measurement system. Summary of the Invention

[0007] In view of this, this disclosure provides an M 2 Measurement system and its laser spot image acquisition method, device, and camera.

[0008] According to a first aspect of this disclosure, a method for acquiring laser spot images of an M² measurement system is provided, the laser spot image acquisition method being applied to a camera of the M² measurement system, the laser spot image acquisition method comprising: Acquire the current frame laser spot image of the first optical path displacement point in the beam propagation direction of the laser system under test. The first optical path displacement point is any optical path displacement point among all optical path displacement points of the M² measurement system. Identify the laser spot in the current frame image to obtain the pixel set of the spot region; The peak gray level of the spot region in the current frame laser spot image is determined using the pixel set of the spot region. Based on the peak grayscale of the spot region in the current frame laser spot image, determine whether the spot region of the current frame laser spot image meets the predetermined exposure requirements; If the spot area in the current frame laser spot image does not meet the exposure requirements, determine the target exposure time, adjust the camera's exposure time to the target exposure time, and acquire the next frame laser spot image at the first optical path displacement point under the target exposure time and send it to the host computer of the M² measurement system. If the spot area in the current frame laser spot image meets the exposure requirements, the current frame laser spot image is sent to the host computer of the M² measurement system.

[0009] In some embodiments of the first aspect of this disclosure, identifying the spot in the current frame laser spot image to obtain a spot region pixel set includes: obtaining a spot region binary mask of the current frame laser spot image through connected component analysis; extracting spot contour points using an edge detection algorithm based on the spot region binary mask of the current frame laser spot image; fitting the spot contour points to obtain the spot region boundary; and extracting spot region pixels in the current frame laser spot image through the spot region boundary to obtain the spot region pixel set.

[0010] In some embodiments of the first aspect of this disclosure, the method further includes: determining the position of the centroid of the spot in the current frame laser spot image using the pixel set of the spot region; determining the peak gray level of the spot region in the current frame laser spot image using the pixel set of the spot region includes: sampling a pixel sequence passing through the centroid of the spot along a predetermined direction from the pixel set of the spot region according to the position of the centroid of the spot in the current frame laser spot image, wherein the predetermined direction is the major axis direction or the minor axis direction passing through the centroid of the spot; fitting a light intensity distribution curve using the pixel sequence, determining the peak value of the light intensity distribution curve, wherein the gray level value corresponding to the peak value is the peak gray level of the spot region in the current frame laser spot image.

[0011] In some embodiments of the first aspect of this disclosure, the target exposure time is calculated as follows: the current exposure time is determined using a pre-calibrated linear response model of the camera and the peak grayscale of the spot region in the current frame laser spot image; the current exposure time is reduced to a first exposure time; the camera's exposure time is adjusted to the first exposure time to acquire a single-frame spot image at a first optical path displacement point under the first exposure time, and the peak grayscale of the spot region in the single-frame spot image is determined; the exposure time corresponding to the target peak grayscale is calculated based on the peak grayscale of the spot region in the single-frame spot image and the linear response model, and the exposure time corresponding to the target peak grayscale is the target exposure time.

[0012] In some embodiments of the first aspect of this disclosure, the target exposure time is calculated as follows: acquiring historical exposure data, which includes the exposure times and peak grayscale values ​​of the spot area at N optical path displacement points before the first optical path displacement point, where N is an integer greater than or equal to 1 and less than the total number of optical path displacement points in the M² measurement system; determining the predicted maximum grayscale value of the spot area at the first optical path displacement point based on the historical exposure data and a pre-built position grayscale model; calculating the predicted exposure time value at the first optical path displacement point using a pre-calibrated linear response model of the camera and the predicted maximum grayscale value of the spot area; determining an exposure time modification amount based on the predicted maximum grayscale value of the spot area and a preset target peak grayscale value; and determining the target exposure time based on the exposure time modification amount and the predicted exposure time value.

[0013] In some embodiments of the first aspect of this disclosure, determining whether the spot region of the current frame laser spot image meets the predetermined exposure requirements based on the peak grayscale of the spot region in the current frame laser spot image includes: determining whether the peak grayscale of the spot region in the current frame laser spot image is within a predetermined target brightness range; if the peak grayscale of the spot region in the current frame laser spot image is within the target brightness range, then determining that the spot region in the current frame laser spot image meets the exposure requirements; if the peak grayscale of the spot region in the current frame laser spot image is less than the lower limit of the target brightness range or greater than the upper limit of the target brightness range, then determining that the spot region in the current frame laser spot image does not meet the exposure requirements.

[0014] In some embodiments of the first aspect of this disclosure, the method further includes: performing bad pixel detection and correction on the current frame laser spot image before identifying the spot in the current frame laser spot image to obtain the spot region pixel set.

[0015] According to a second aspect of this disclosure, a laser spot image acquisition device is provided, the laser spot image acquisition device being applied to a camera in an M² measurement system, the laser spot image acquisition device comprising: The image acquisition unit is used to acquire the current frame laser spot image of the first optical path displacement point in the beam propagation direction of the laser system under test, wherein the first optical path displacement point is any optical path displacement point among all optical path displacement points of the M² measurement system; and to acquire the next frame laser spot image at the first optical path displacement point at the target exposure time. A spot recognition unit is used to identify spots in the current frame laser spot image to obtain a pixel set of spot regions. A grayscale determination unit is used to determine the peak grayscale of the spot region in the current frame laser spot image using the pixel set of the spot region. An exposure detection unit is used to determine whether the spot area of ​​the current frame laser spot image meets the predetermined exposure requirements based on the peak gray level of the spot area in the current frame laser spot image. An exposure adjustment unit is used to determine the target exposure time and adjust the camera's exposure time to the target exposure time when the spot area in the current frame laser spot image does not meet the exposure requirements. The image transmission unit is configured to send the current frame laser spot image to the host computer of the M² measurement system when the spot area in the current frame laser spot image meets the exposure requirements; and to send the next frame laser spot image at the first optical path displacement point acquired at the target exposure time to the host computer of the M² measurement system.

[0016] According to a third aspect of this disclosure, a camera is provided for use in an M² measurement system, the camera including a processor and a memory, the memory storing a computer program that, when read by the processor, executes the method described above.

[0017] According to a fourth aspect of this disclosure, an M² measurement system is provided, comprising a host computer, an automated displacement platform, auxiliary optical elements, and a camera. The automated displacement platform, auxiliary optical elements, and camera are respectively connected to the host computer. The automated displacement platform carries the camera and, under the control of the host computer, moves the camera to multiple predetermined optical path displacement points along the beam propagation direction of the laser system under test. The auxiliary optical elements assist the camera in capturing laser spot images of the laser system under test. The camera acquires laser spot images of the laser system under test at multiple predetermined optical path displacement points along the beam propagation direction using the above method and sends them to the host computer. The host computer uses the laser spot images at the multiple predetermined optical path displacement points to determine the M² factor of the laser system under test.

[0018] As can be seen from the above technical solution, the embodiments of this disclosure require only a maximum of two image acquisition iterations at each displacement point to rapidly adjust the spot brightness to the ideal exposure time. This allows for quick and automatic adjustment of the exposure time to a suitable range, significantly shortening the automatic exposure adjustment time and meeting the application requirements for automated real-time measurement of the M² factor. Furthermore, the entire process of these embodiments requires no manual intervention and can be quickly and effectively applied to automated M² factor measurement, making the automated M² factor measurement process faster and more accurate to a certain extent. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 M provided for the embodiments of this disclosure 2 Schematic diagram of an automated measurement system; Figure 2 M provided for the embodiments of this disclosure 2 A flowchart illustrating the method for acquiring laser spot images in an automated measurement system; Figure 3 This is an example grayscale image of the laser spot image involved in the embodiments of this disclosure; Figure 4 This is an example diagram of the light intensity distribution curve obtained by fitting the long axis direction of the light spot centroid in an embodiment of this disclosure; Figure 5 This is an example diagram of the light intensity distribution curve obtained by fitting the long axis direction of the centroid of the light spot according to an embodiment of this disclosure.

[0021] Figure 6 This is a schematic diagram of a camera linear response model according to an embodiment of the present disclosure; Figure 7 This is another schematic diagram of the camera linear response model involved in the embodiments of this disclosure; Figure 8 This is a schematic diagram of the structure of the laser spot image acquisition device provided in the embodiments of this disclosure. Detailed Implementation

[0022] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0023] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure. The singular forms “a,” “the,” and “the” as used in the embodiments of this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0024] As mentioned earlier, the image quality of the spot region in a laser beam image directly affects the measurement accuracy of an M² measurement system. Currently, laser beam imaging solutions in related technologies face the following major challenges in automated M² measurement: 1) Extremely large dynamic range of light intensity: The energy distribution of the laser spot is highly uneven, and the brightness difference between the central and edge regions can reach several orders of magnitude. If the exposure time is too long, the core region of the spot is prone to saturation overexposure, resulting in the loss of true energy distribution information and distortion of the spot diameter calculation; if the exposure time is too short, the signal at the edge of the spot is weak and difficult to extract effectively from the background noise, which also introduces measurement error.

[0025] 2) Complex measurement environment: The interference of ambient stray light and background light will change the overall gray-scale distribution of the image, causing traditional automatic exposure algorithms that rely on global gray-scale statistics, such as mean or histogram matching, to frequently fail and make it difficult to stably optimize for the light spot itself.

[0026] 3) Stringent real-time requirements: In the M² automated measurement system, images need to be acquired quickly and continuously at multiple locations along the beam propagation path. This requires that automatic exposure control must be completed in an extremely short time. Any significant delay will directly affect the throughput, efficiency and accuracy of the entire measurement system.

[0027] Therefore, automatic exposure technology has become a core component of high-performance laser beam imaging M2 factor automated measurement systems. Its purpose is to automatically and quickly adjust the camera exposure parameters to the optimal state at different displacement points, ensuring that the captured laser spot image is neither overexposed to retain central details nor underexposed to clearly separate from the background, thus providing reliable data for the accurate calculation and analysis of the spot diameter.

[0028] Currently, existing automatic exposure technologies are mainly divided into two categories: automatic exposure methods based on global image grayscale statistics and automatic exposure methods based on fixed regions of interest.

[0029] The existing automatic exposure technique, namely the automatic exposure method based on global image grayscale statistics, mainly consists of the following: Technical Overview: Automatic exposure based on global image grayscale statistics is the most common and widely used automatic exposure strategy, applied in ordinary cameras. This method acquires images in real time, considers all pixels of the entire frame, calculates its average brightness or grayscale histogram distribution, compares this average brightness with a preset target brightness value, and iteratively and dynamically adjusts the exposure time or gain through feedback control such as a PID controller to make the global average brightness approach the target value.

[0030] The specific implementation method is as follows: The camera captures a frame image with the current exposure parameters, calculates the global average gray value of the frame image, calculates the error between the global average gray value of the frame image and the target brightness, and adjusts the exposure time according to the magnitude and direction of the error between the global average gray value of the frame image and the target brightness according to a preset proportional coefficient to obtain new exposure parameters. The new exposure parameters are then applied to the camera, and the camera continues to capture the next frame, and this process is repeated until convergence.

[0031] The main drawbacks are: Automatic exposure methods based on global image grayscale statistics cannot specifically optimize the laser spot because the laser spot typically occupies only a tiny area in the image. When the background is dark, even if the spot is severely overexposed, the global average brightness may be very low, causing the algorithm to incorrectly continue increasing the exposure and completely lose the detailed information at the center of the spot. Conversely, when the background is bright, significantly increasing the exposure to improve overall brightness will cause the already bright spot area to become completely saturated. Furthermore, automatic exposure methods based on global image grayscale statistics have poor adaptability to high-contrast scenes because the laser spot and background usually constitute a scene with extremely high contrast. To balance this contrast, the global algorithm often sacrifices the imaging quality of the spot area, failing to meet the stringent requirements of laser measurement for spot area quality.

[0032] The existing automatic exposure technique 2, based on a fixed region of interest, mainly consists of the following: Technical Description: Automatic exposure based on a fixed region of interest recognizes the limitations of global methods. Therefore, a fixed rectangular region in the image is preset as the region of interest (ROI), and exposure decisions are made only based on the pixel statistics within this ROI. This ROI is usually set in the center of the image, assuming that the laser spot will appear at this location.

[0033] Specific implementation method: A fixed ROI is predefined in the image coordinate system. After the image is acquired, only the average brightness of all pixels in the ROI is calculated. The subsequent control process is similar to the aforementioned global statistical method, but the goal is to adjust the average brightness in the ROI to the ideal range.

[0034] Main drawbacks: Automatic exposure methods based on fixed regions of interest (ROIs) rely on prior knowledge of the laser spot's position. Because this method heavily depends on the laser spot always appearing within a pre-defined, fixed area, if the spot moves off-target during the M² measurement process due to collimation errors or other factors, the exposure system will lose its correct control target, potentially leading to completely incorrect exposure. Automatic exposure methods based on fixed ROIs are susceptible to local background interference. If there are bright or dark background obstructions unrelated to the laser spot, such as reflective points or dust, within the ROI, the method will misinterpret them as targets requiring optimization, resulting in incorrect exposure adjustments. Furthermore, automatic exposure methods based on fixed ROIs lack robustness and cannot adapt to the movement of the laser spot within the field of view, limiting their use in dynamic application scenarios.

[0035] In view of this, the present disclosure provides the following M2 measurement system and its laser spot image acquisition method, device and camera, which provide a more intelligent, robust and accurate automatic exposure scheme for camera-type laser M² automated measurement system. It can quickly and automatically adjust the exposure time to a suitable range, meet the requirements of accurate M² factor measurement, and solve the technical problem that existing automatic exposure technology cannot meet the requirements of M² automated measurement.

[0036] Figure 1 The M provided in the embodiments of this disclosure is shown. 2 A schematic diagram of the measurement system. (See also...) Figure 1 The M provided in the embodiments of this disclosure 2 The measurement system 100 may include: a host computer 110, an automated displacement platform 120, an auxiliary optical element 130, and a camera 140. The automated displacement platform 120, the auxiliary optical element 130, and the camera 140 are respectively connected to the host computer 110. The automated displacement platform 120 is used to carry the camera 140 and, under the control of the host computer 110, moves the camera 140 to multiple predetermined optical path displacement points along the beam propagation direction of the laser system under test. The auxiliary optical element 130 is used to assist the camera 140 in capturing laser spot images of the laser system under test. The camera 140 can be used to acquire laser spot images of multiple predetermined optical path displacement points in the beam propagation direction of the laser system under test through the laser spot image acquisition method of the M² measurement system described below and send them to the host computer 110. The host computer 110 can be used to determine the M² factor of the laser system under test using the laser spot images of multiple predetermined optical path displacement points.

[0037] For example, see Figure 1The aforementioned multiple predetermined optical path displacement points may include displacement point 1, displacement point 2, displacement point 3, and displacement point 4, all of which are located in the propagation direction of the laser beam emitted by the laser system under test. The automated displacement platform 120, under the control of the host computer 110, moves along the beam propagation direction of the laser system under test to move the camera 140 to displacement points 1, 2, 3, and 4 respectively. The camera 140 uses the laser spot image acquisition method described herein to acquire laser spot images at these four displacement points and sends them to the host computer 110. The host computer 110 uses the laser spot images at these four displacement points to determine the M² factor of the laser system under test.

[0038] In specific applications, camera 140 can be an optical analysis camera 140, which integrates a high dynamic range image sensor and includes components such as the image sensor's drive circuit. The light-assisted optical element 130 can include, but is not limited to, a focusing lens and an attenuator. The automated displacement platform 120 can be, but is not limited to, a high-precision electric linear translation stage, including a guide rail driven by a high-precision ball screw or linear motor. The host computer 110 can be used to control the automated displacement platform 120 and trigger camera 140 to acquire laser spot images at each predetermined optical path displacement point. For M... 2 The specific structure and implementation of each part of the measurement system are not limited in the embodiments disclosed herein.

[0039] Figure 2 This diagram illustrates a flowchart of a laser spot image acquisition method for an M2 measurement system provided in this embodiment. This method can be applied to the camera in the aforementioned M2 measurement system. (See also...) Figure 2 The method for acquiring laser spot images of the M2 measurement system may include the following steps: Step 201: Acquire the current frame laser spot image of the first optical path displacement point in the beam propagation direction of the laser system under test. The first optical path displacement point is any optical path displacement point among all optical path displacement points of the M² measurement system. Step 202: Identify the laser spot in the current frame image to obtain the pixel set of the spot region; Step 203: Determine the peak gray level of the spot region in the current frame laser spot image using the pixel set of the spot region; Step 204: Determine whether the spot area of ​​the current frame laser spot image meets the predetermined exposure requirements based on the peak gray level of the spot area in the current frame laser spot image; Step 205: If the spot area in the current frame laser spot image does not meet the exposure requirements, determine the target exposure time, adjust the camera's exposure time to the target exposure time, and acquire the next frame laser spot image at the first optical path displacement point under the target exposure time and send it to the host computer of the M² measurement system. Step 206: If the spot area in the current frame laser spot image meets the exposure requirements, send the current frame laser spot image to the host computer of the M² measurement system.

[0040] The laser spot image acquisition method of this disclosure acquires laser spot images at each optical path displacement point, performs spot recognition and positioning and brightness analysis, and dynamically adjusts the camera's exposure time based on the spot brightness when the exposure requirements are not met. The adjusted exposure time is then used to re-acquire the laser spot image at the current optical path displacement point and send it to the host computer of the M² measurement system. When the exposure requirements are met, the currently acquired laser spot image is sent to the host computer of the M² measurement system. Thus, at each displacement point, only a maximum of two image acquisition iterations are needed to quickly adjust the spot brightness to the ideal exposure time. This allows for rapid and automatic adjustment of the exposure time to a suitable range, significantly shortening the automatic exposure adjustment time and meeting the application requirements of automated real-time measurement of the M² factor. It overcomes the inherent defects of existing technologies and provides a high-performance automatic exposure solution for laser applications. Furthermore, the entire process of this disclosure requires no manual intervention and can be quickly and effectively applied to automated M² factor measurement, making the automated M² factor measurement process faster and more accurate to a certain extent.

[0041] In step 201, the camera is triggered when the automated displacement platform moves it to the first optical path displacement point. The image sensor integrated within the camera acquires the current frame laser spot image at the first optical path displacement point in the beam propagation direction of the laser system under test in real time. Specifically, the high dynamic range image sensor integrated within the camera captures the current frame laser spot image of the laser beam on the imaging plane when the automated displacement platform moves the camera to a certain optical path displacement point. The exposure parameters of the image sensor when capturing the current frame laser spot image are recorded simultaneously. These exposure parameters may include, but are not limited to, the exposure time. Initially, the image sensor integrated within the camera can acquire the first laser spot image using the default exposure parameters.

[0042] In some implementations, prior to step 202, defect detection and correction can be performed on the current frame laser spot image. Defect detection and correction can prevent defects from affecting the accuracy of spot recognition, improve the accuracy of spot recognition and the rationality of exposure time adjustment, and avoid situations such as erroneously reducing the exposure time. In some examples, defect detection and correction may include: calculating the mean square distance between the center pixel and a predetermined neighborhood; if the mean square distance exceeds a preset mean square distance threshold, it is determined to be a defective pixel, and the arithmetic mean of the effective neighboring pixels is used to replace the defective pixel. If the mean square distance does not exceed the preset mean square distance threshold, the center pixel is determined not to be a defective pixel and no processing is required. For example, the predetermined neighborhood may be, but is not limited to, a 3×3 neighborhood area. In specific applications, any other applicable methods can be used to perform defect detection and correction on the current frame laser spot image; this disclosure does not limit such methods.

[0043] In some implementations, step 202 can automatically identify the laser spot in the current frame image based on connected component analysis and morphological features. Specifically, a binary mask of the laser spot region in the current frame image is obtained through connected component analysis. Based on the binary mask of the laser spot region in the current frame image, an edge detection algorithm is used to extract the spot contour points. The boundary of the spot region is obtained by fitting the spot contour points. The pixel points of the spot region in the current frame image are then extracted through the boundary of the spot region to obtain the pixel set of the spot region.

[0044] In practical applications, connected component analysis can employ algorithms such as, but is not limited to, two-pass scanning and seed filling. Edge detection algorithms can include, but are not limited to, the Canny operator and the Suzuki algorithm, with the Canny operator being preferred as it effectively eliminates noise and background interference. The boundary of the light spot region can be obtained by fitting the light spot contour points using algorithms such as, but are not limited to, the least squares method.

[0045] In some examples, a binary mask of the laser spot region in the current frame image can be obtained first through connected component analysis. Then, the Canny operator is used to automatically identify the spot contour region from the binary mask, thereby extracting the spot contour points. Based on the spot contour points, the boundary of the spot region is obtained by least-squares ellipse fitting. The spot region boundary may include, but is not limited to, parameters such as center point coordinates, major axis length, minor axis length, rotation angle, ellipticity, and aspect ratio. Finally, the pixel set of the spot region is obtained by extracting the pixel points of the spot region in the current frame image through the spot region boundary. Here, the center point coordinates represent the coordinates of the geometric symmetry center point of the spot shape. Figure 3 An example grayscale image of a laser beam is shown. Figure 3 In the example, the elliptical shape represents the boundary of the light spot region.

[0046] As described above, the embodiments of this disclosure employ real-time image processing technology to automatically identify and locate the actual position of the laser spot in each frame of the laser spot image. The spot region is obtained through connected component analysis and morphological feature recognition. By dynamically and automatically identifying and locating the true position of the laser spot in each frame of the image, the problem of the fixed ROI method in related technologies failing due to spot movement is solved, eliminating the dependence on the fixed position of the spot. At the same time, it can effectively distinguish the laser spot from other bright noise or interference in the image, improving the accuracy and reliability of exposure control, thereby realizing an exposure control mechanism based on dynamic spot recognition.

[0047] In step 203, various applicable methods can be used to determine the peak gray level of the spot area.

[0048] In some implementations, step 203 can determine the peak grayscale of the spot region through brightness analysis. Specifically, peak coordinate points can be obtained by performing peak coordinate detection on the pixel set of the spot region, and the grayscale value at the peak coordinate point is the grayscale of the spot region. Peak coordinate detection can include: finding the point with the largest pixel value in the pixel set of the spot region, determining the cluster center coordinate point of the point with the largest pixel value, using the cluster center coordinate point as the peak coordinate point of the pixel set of the spot region, and the grayscale value of the peak coordinate point is the peak grayscale of the spot region.

[0049] In some implementations, the position of the spot centroid in the current frame laser spot image can be determined first using the pixel set of the spot region. In step 203, based on the position of the spot centroid in the current frame laser spot image, a pixel sequence passing through the spot centroid along a predetermined direction can be sampled from the pixel set of the spot region. The predetermined direction is either the major axis direction or the minor axis direction passing through the spot centroid. The light intensity distribution curve is obtained by fitting the pixel sequence, and the peak value of the light intensity distribution curve is determined. The gray value corresponding to this peak value is the peak gray value of the spot region in the current frame laser spot image.

[0050] In some examples, the precise center coordinates of the spot in the image can be obtained by performing sub-pixel-level precise localization of the pixel set of the spot region. These precise center coordinates are the position of the spot centroid in the current frame of the laser spot image.

[0051] In some examples, the major or minor axis direction passing through the centroid of the light spot can be determined by calculating the second moment of the beam profile of the pixel set in the light spot region. Specifically, three second moments of the beam profile are calculated based on the pixel set of the light spot region. These three second moments are the variance in the X direction, the variance in the Y direction, and the covariance of X and Y. The covariance of X and Y indicates whether the light spot is tilted. Using these three second moments, a covariance matrix is ​​constructed. Solving for the eigenvectors of this matrix yields the directions of two eigenvectors. These two eigenvectors represent the physical directions of the major and minor axes, i.e., the major and minor axis directions passing through the centroid of the light spot. Here, the X direction refers to the horizontal direction of the camera's image sensor, i.e., the column direction of the image, and the Y direction refers to the vertical direction of the camera's image sensor, i.e., the row direction of the image.

[0052] By fitting a light intensity distribution curve along either the major or minor axis of the spot's centroid, the peak grayscale of the spot region is determined. This method uses physical laws (i.e., Gaussian distribution) to correct the discrete, noisy data acquired by the camera's image sensor, obtaining a peak intensity closest to the real physical world. This not only eliminates noise interference but also improves the accuracy of the peak grayscale. Therefore, precise exposure control centered on the spot can be achieved, ensuring that exposure decisions are always based on the actual brightness characteristics of the laser spot region itself, rather than the global or fixed local area. This prioritizes the image quality of the spot region under all circumstances.

[0053] In some implementations, light intensity distribution curves can be fitted along the major axis and minor axis of the spot centroid and their peak values ​​can be determined. The average of these two peak values ​​can be taken as the peak gray level of the spot region in the current frame laser spot image.

[0054] Figure 4 A visualization example of the light intensity distribution curve obtained by fitting along the major axis of the light spot centroid is shown. Figure 5 A visualization example of the light intensity distribution curve obtained by fitting along the major axis of the light spot centroid is shown. Specifically, in Figure 3 The grayscale distribution curve (i.e., the light intensity distribution curve mentioned earlier) obtained by extracting pixels along the major axis of the dashed rectangular region shown in the figure, normalizing them, and then performing curve fitting is as follows: Figure 4 As shown, in Figure 3 The grayscale distribution curve (i.e., the light intensity distribution curve mentioned earlier) obtained by extracting pixels along the minor axis of the dashed rectangular region, normalizing them, and then performing curve fitting is shown below. Figure 5 As shown, Figure 4 The peak value B1 level in the image is the peak gray level along the major axis. Figure 5The peak B2 level is the peak gray level in the short axis direction. The peak gray level in the current frame laser spot image can be any one of the peak B1 level, peak B2 level, or the average of peak B1 level and peak B2 level, which is the maximum gray level value of the spot area in the current frame laser spot image. Figure 4 and Figure 5 The A level indicates the position of the pixel with a normalized grayscale value of 1.

[0055] In some implementations, step 204 can determine whether the spot area of ​​the current frame laser spot image meets the predetermined exposure requirements by: determining whether the peak grayscale of the spot area in the current frame laser spot image is within the predetermined target brightness range; if the peak grayscale of the spot area in the current frame laser spot image is within the target brightness range, then the spot area in the current frame laser spot image meets the exposure requirements; if the peak grayscale of the spot area in the current frame laser spot image is less than the lower limit of the target brightness range or greater than the upper limit of the target brightness range, then the spot area in the current frame laser spot image does not meet the exposure requirements. Therefore, by comparing the peak grayscale of the spot area in the current frame laser spot image with the target brightness range, it is possible to determine whether the current exposure is appropriate. This allows for efficient, fast, and accurate determination of whether the current frame laser spot image meets the exposure requirements, and also accurately determines whether the current frame laser spot image is overexposed or underexposed.

[0056] In practical applications, the target brightness range can be taken as an empirical value. In different application scenarios, the target brightness range can also be flexibly adjusted based on the actual application situation. This disclosure does not limit the specific value of the target brightness range.

[0057] In step 205, the target exposure time can be calculated in various ways.

[0058] In some implementations, the target exposure time in step 205 can be calculated using the following first method: Determine the current exposure time using a pre-calibrated linear response model of the camera and the peak grayscale of the spot region in the current frame laser spot image; reduce the current exposure time to a first exposure time; adjust the camera's exposure time to the first exposure time to acquire a single-frame spot image at the first optical path displacement point under the first exposure time, and determine the peak grayscale of the spot region in the single-frame spot image; calculate the exposure time corresponding to the target peak grayscale based on the peak grayscale of the spot region in the single-frame spot image and the linear response model. The exposure time corresponding to this target peak grayscale is the target exposure time. Here, the camera's linear response model refers to the camera's response model between exposure time and spot brightness. By performing a single exposure reduction sampling and utilizing the proportional relationship of the camera's linear response model, the exposure time that enables the spot region to achieve ideal brightness can be calculated accurately, quickly, and without iteration. This achieves single-frame fast exposure correction based on the spot brightness distribution characteristics, significantly improving the efficiency and reliability of light control while ensuring information integrity. This method eliminates the need for iterative exploration, avoiding the multiple sampling processes of trial and error and adjustment required in traditional automatic exposure, making it particularly suitable for M² measurement systems that require rapid response.

[0059] The first exposure time can be obtained by multiplying the current exposure time by a preset scaling factor, which is greater than 0 and less than 0.5.

[0060] The linear response model of a camera can be expressed as follows:

[0061] in, This represents the peak gray level of the spot region in a single frame of the spot image. Indicates the first exposure time. This represents the slope of the linear response.

[0062] The exposure time corresponding to the target peak gray level can be calculated using the following formula:

[0063] This indicates the exposure time corresponding to the target peak grayscale. Indicates the target peak gray level.

[0064] Therefore, based on the camera's linear response model, a suitable exposure time can be calculated through a single underexposure sampling. This exposure time ensures that the peak gray level of the laser spot region in the laser spot image reaches the preset target peak gray level.

[0065] In some implementations, the target exposure time in step 205 can also be calculated in the following second way: acquiring historical exposure data, which may include the exposure time and peak gray value of the spot area of ​​N optical path displacement points before the first optical path displacement point, where N is an integer greater than or equal to 1 and less than the total number of optical path displacement points of the M² measurement system; determining the maximum gray value prediction of the spot area of ​​the first optical path displacement point based on the historical exposure data and the pre-built position gray value model; calculating the exposure time prediction value of the first optical path displacement point using the pre-calibrated linear response model of the camera and the maximum gray value prediction of the spot area; determining the exposure time modification amount based on the maximum gray value prediction of the spot area and the preset target peak gray value; and determining the target exposure time based on the exposure time modification amount and the exposure time prediction value.

[0066] Therefore, by leveraging the camera's exposure parameters and the response model of the spot brightness, and through iterative learning to optimize the parameter adjustment strategy, the optimal exposure parameters for the next frame are predicted based on historical exposure data and the dynamic change trend of the spot during continuous measurement. A feedback control mechanism is introduced to dynamically adjust the exposure time, achieving rapid convergence to the optimal exposure state. This minimizes the exposure time while ensuring the image quality of the spot, improves the system frame rate, and meets the real-time spot diameter calculation requirements of the M² measurement system.

[0067] In some examples, a convolutional neural network can be used to directly learn the mapping relationship between image features and optimal exposure parameters, and the target exposure time can be determined through this convolutional neural network. This method is highly adaptable and can handle complex scenes. In some examples, the target exposure time can also be predicted based on historical data. For example, the exposure effect of the previous few frames can be used to predict the target exposure time of the next frame. This method is smoother and more stable, but it is slower to respond to rapidly changing scenes. Of course, other methods can also be used to determine the target exposure time, and the specific method for determining the target exposure time is not limited in the embodiments of this disclosure.

[0068] In some implementations, if the peak gray level of the spot region in the current frame laser spot image is greater than the upper limit of the target brightness range, the spot region in the current frame laser spot image is determined to be overexposed. If overexposed, the target exposure time can be determined by the first method described above, the camera's exposure time can be adjusted to the target exposure time, and the laser spot image at the first optical path displacement point can be acquired again at the target exposure time to ensure that the beam core energy region and the background noise region of the laser spot image are well distinguished on the image.

[0069] In some implementations, if the peak gray level of the spot region in the current frame laser spot image is less than the lower limit of the target brightness range, it is determined that the spot region in the current frame laser spot image is underexposed. The target exposure time can be determined by the second method mentioned above, the camera's exposure time can be adjusted to the target exposure time, and the laser spot image at the first optical path displacement point can be acquired again at the target exposure time to ensure that the beam core energy region and the background noise region of the laser spot image are well distinguished on the image.

[0070] Figure 6 A schematic diagram of the camera's linear response model is shown. Figure 7 Another schematic diagram of the camera's linear response model is shown. Figure 6 and Figure 7 In the diagram, the vertical axis represents the normalized grayscale value, the horizontal axis represents the exposure time, and the black dashed diagonal line represents the camera's linear response model. If the normalized grayscale value exceeds 1.0, it indicates that the target brightness range is exceeded. Figure 6 An example of an overexposure point is given. When the peak grayscale of the spot area in the current frame of the laser spot image reaches the grayscale value of the overexposure point, the exposure time of the overexposure point can be multiplied by a scaling factor between 0 and 0.5 to obtain a shorter first exposure time. Using this first exposure time, a new frame of the laser spot image is acquired at the current optical path displacement point, and bad pixel correction is performed. The peak grayscale of the spot area in this new laser spot image is... Figure 7 The grayscale value of data point 1 is shown. Based on this grayscale value and the first exposure time, the target exposure time corresponding to the target peak grayscale is obtained through the camera's linear response model, which is to obtain... Figure 6 and Figure 7 The target point shown.

[0071] In steps 205 and 206, while sending the laser beam image that meets the exposure requirements to the host computer of the M² measurement system, the exposure time of the laser beam image can also be sent to the M² measurement system simultaneously.

[0072] As described above, the embodiments of this disclosure adjust the camera's exposure time and other parameters in real time through adaptive fast exposure technology, which can quickly optimize the brightness of the light spot at each measurement position to the camera's optimal response range, thereby overcoming the brightness mismatch problem caused by position changes and effectively suppressing the critical overexposure phenomenon that occurs near the waist, ensuring the accuracy and reliability of the measurement data used by the M² measurement system.

[0073] As can be seen from the above, the laser spot acquisition method of the M² measurement system provided in this disclosure allows the camera to perform spot imaging when the automated displacement platform moves the camera to a preset optical path displacement point. For spot imaging that does not meet the exposure requirements, such as overexposure near the beam waist after focusing the lens, the spot brightness can be accurately adjusted to a suitable range for imaging in as little as one frame of image iteration, which greatly shortens the automatic exposure adjustment time and meets the real-time accurate measurement requirements of beam diameter in the M² measurement system.

[0074] The embodiments disclosed herein can achieve the following technical effects: 1) The exposure convergence speed is significantly improved: In overexposure correction scenarios, the method of this disclosure embodiment can adjust the exposure time to a suitable range in as little as 1 frame of image acquisition iteration, while the prior art requires at least 4 to 5 frame iterations.

[0075] 2) M² measurement repeatability: Tests showed that the M² measurement repeatability improved from ±5% to ±1%.

[0076] 3) Spot stability: The exposure time adjustment is more precise, the spot brightness is appropriate, the spot diameter measurement is more accurate and the stability is higher. The spot diameter measurement error of the prior art is ±10%, while the spot diameter measurement error of the method of the present disclosure embodiment is ±1%.

[0077] This disclosure utilizes innovative spot recognition and exposure control algorithms to significantly improve response speed while maintaining high precision. It is particularly suitable for industrial applications requiring real-time measurement, providing reliable technical support for laser processing and quality inspection. By acquiring and intelligently analyzing laser spot images in real time, combined with connected component analysis and morphological feature recognition, the system can quickly and accurately locate the spot and analyze its brightness distribution. Based on rapid exposure correction and adaptive parameter optimization using single-frame images, it effectively avoids the inefficiency caused by repeated trial and error in traditional exposure methods. This significantly improves the accuracy and efficiency of laser beam quality (i.e., M² factor) measurement, making it particularly suitable for rapid diagnosis and online monitoring of high-power lasers.

[0078] Figure 8 A schematic diagram of a laser spot image acquisition device provided in an embodiment of this disclosure is shown. This laser spot image acquisition device is applied to the camera of an M² measurement system. See [link to relevant documentation]. Figure 8 The laser spot image acquisition device may include: The image acquisition unit 801 is used to acquire the current frame laser spot image of the first optical path displacement point in the beam propagation direction of the laser system under test, wherein the first optical path displacement point is any optical path displacement point among all optical path displacement points of the M² measurement system; and to acquire the next frame laser spot image at the first optical path displacement point at the target exposure time. The spot recognition unit 802 is used to identify the spot in the current frame laser spot image to obtain the spot region pixel set; Gray level determination unit 803 is used to determine the peak gray level of the spot region in the current frame laser spot image using the pixel set of the spot region; The exposure detection unit 804 is used to determine whether the spot area of ​​the current frame laser spot image meets the predetermined exposure requirements based on the peak gray level of the spot area in the current frame laser spot image; The exposure adjustment unit 805 is used to determine the target exposure time and adjust the camera's exposure time to the target exposure time when the spot area in the current frame laser spot image does not meet the exposure requirements. The image transmission unit 806 is used to send the current frame laser spot image to the host computer of the M² measurement system when the spot area in the current frame laser spot image meets the exposure requirements; and to send the next frame laser spot image at the first optical path displacement point acquired at the target exposure time to the host computer of the M² measurement system.

[0079] In some implementations, the spot recognition unit 802 can specifically be used to obtain a binary mask of the spot region of the current frame laser spot image through connected component analysis; extract spot contour points using an edge detection algorithm based on the binary mask of the spot region of the current frame laser spot image; obtain the spot region boundary by fitting the spot contour points; and extract the spot region pixels in the current frame laser spot image through the spot region boundary to obtain the spot region pixel set.

[0080] In some embodiments, the spot recognition unit 802 can also be used to determine the position of the spot centroid in the current frame laser spot image using the spot region pixel set; the grayscale determination unit can specifically be used to: sample a pixel sequence passing through the spot centroid along a predetermined direction from the spot region pixel set according to the position of the spot centroid in the current frame laser spot image, the predetermined direction being the major axis direction or the minor axis direction passing through the spot centroid; use the pixel sequence to fit a light intensity distribution curve, determine the peak value of the light intensity distribution curve, and the grayscale value corresponding to the peak value is the peak grayscale of the spot region in the current frame laser spot image.

[0081] In some implementations, the exposure adjustment unit 805 may specifically be used to calculate the target exposure time in the following manner: determine the current exposure time using a pre-calibrated linear response model of the camera and the peak gray level of the spot region in the current frame laser spot image; reduce the current exposure time to a first exposure time; adjust the camera's exposure time to the first exposure time to acquire a single-frame spot image at the first optical path displacement point under the first exposure time, and determine the peak gray level of the spot region in the single-frame spot image; calculate the exposure time corresponding to the target peak gray level based on the peak gray level of the spot region in the single-frame spot image and the linear response model, and the exposure time corresponding to the target peak gray level is the target exposure time.

[0082] In some implementations, the exposure adjustment unit 805 can specifically be used to calculate the target exposure time in the following manner: acquiring historical exposure data, which includes the exposure time and peak gray value of the spot area at N optical path displacement points before the first optical path displacement point, where N is an integer greater than or equal to 1 and less than the total number of optical path displacement points in the M² measurement system; determining the predicted maximum gray value of the spot area at the first optical path displacement point based on the historical exposure data and a pre-built position gray value model; calculating the predicted exposure time at the first optical path displacement point using a pre-calibrated linear response model of the camera and the predicted maximum gray value of the spot area; determining the exposure time modification amount based on the predicted maximum gray value of the spot area and a preset target peak gray value; and determining the target exposure time based on the exposure time modification amount and the predicted exposure time value.

[0083] In some implementations, the exposure detection unit 804 may specifically be used to: determine whether the peak grayscale of the spot region in the current frame laser spot image is within a predetermined target brightness range; if the peak grayscale of the spot region in the current frame laser spot image is within the target brightness range, then determine that the spot region in the current frame laser spot image meets the exposure requirements; if the peak grayscale of the spot region in the current frame laser spot image is less than the lower limit of the target brightness range or greater than the upper limit of the target brightness range, then determine that the spot region in the current frame laser spot image does not meet the exposure requirements.

[0084] In some embodiments, the laser spot image acquisition device may further include: a bad pixel correction unit 807, used to perform bad pixel detection and correction on the current frame laser spot image, so that the spot recognition unit can identify the spot in the current frame laser spot image to obtain the spot region pixel set.

[0085] In practical applications, the laser spot image acquisition device can be implemented as software, hardware, or a combination of both. For example, the laser spot image acquisition device can be deployed in the camera of the aforementioned M² measurement system. Other technical details of the laser spot image acquisition device can be found in the methods section above, and will not be repeated here.

[0086] This disclosure also provides a camera applied to an M² measurement system. The camera includes a processor and a memory. The memory stores a computer program, which, when read by the processor, executes the aforementioned laser spot image acquisition method for the M² measurement system. The camera can be, but is not limited to, an optical analysis camera. In specific applications, the camera may also include, but is not limited to, the aforementioned image sensor and its driving circuitry. Furthermore, the camera may include other components. This disclosure does not limit the specific type and structure of the camera.

[0087] This disclosure also provides a computer-readable storage medium storing a computer program thereon, the program including instructions that, when executed by one or more processors, execute the steps of the aforementioned laser spot image acquisition method for the M² measurement system.

[0088] Embodiments of this disclosure also provide a computer program product, which includes computer program instructions that, when executed by a processor, cause the processor to perform the steps in the aforementioned laser spot image acquisition method for the M² measurement system.

[0089] The technical solutions provided in this disclosure have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this disclosure. The descriptions of the embodiments above are only for the purpose of helping to understand the methods and core ideas of this disclosure. Furthermore, those skilled in the art will recognize that, based on the ideas of this disclosure, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this disclosure.

[0090] The above description is merely a preferred embodiment of this disclosure and is not intended to limit this disclosure. Any modifications or equivalent substitutions made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for acquiring laser spot images in an M² measurement system, characterized in that, The laser spot image acquisition method is applied to the camera of the M² measurement system, and the laser spot image acquisition method includes: Acquire the current frame laser spot image of the first optical path displacement point in the beam propagation direction of the laser system under test. The first optical path displacement point is any optical path displacement point among all optical path displacement points of the M² measurement system. Identify the laser spot in the current frame image to obtain the pixel set of the spot region; The peak gray level of the spot region in the current frame laser spot image is determined using the pixel set of the spot region. Based on the peak grayscale of the spot region in the current frame laser spot image, determine whether the spot region of the current frame laser spot image meets the predetermined exposure requirements; If the spot area in the current frame laser spot image does not meet the exposure requirements, determine the target exposure time, adjust the camera's exposure time to the target exposure time, and acquire the next frame laser spot image at the first optical path displacement point under the target exposure time and send it to the host computer of the M² measurement system. If the spot area in the current frame laser spot image meets the exposure requirements, the current frame laser spot image is sent to the host computer of the M² measurement system.

2. The method according to claim 1, characterized in that, The step of identifying the laser spot in the current frame image to obtain the pixel set of the spot region includes: The binary mask of the laser spot region in the current frame image is obtained through connected component analysis; Based on the current frame of the laser spot image, the edge detection algorithm is used to extract the spot contour points using a binary mask of the spot region, and the spot region boundary is obtained by fitting the spot contour points. The pixel set of the laser spot region is obtained by extracting the pixels of the laser spot region in the current frame image by the boundary of the spot region.

3. The method according to claim 1, characterized in that, The method further includes: using the pixel set of the spot region to determine the position of the spot centroid in the current frame of the laser spot image; Determining the peak grayscale of the spot region in the current frame laser spot image using the pixel set of the spot region includes: Based on the position of the spot centroid in the current frame of the laser spot image, a pixel sequence passing through the spot centroid along a predetermined direction is obtained from the pixel set of the spot region. The predetermined direction is either the major axis direction or the minor axis direction passing through the spot centroid. The light intensity distribution curve is obtained by fitting the pixel sequence, and the peak value of the light intensity distribution curve is determined. The gray value corresponding to the peak value is the peak gray value of the spot region in the current frame laser spot image.

4. The method according to claim 1, characterized in that, The target exposure time is calculated as follows: The current exposure time is determined using the pre-calibrated linear response model of the camera and the peak gray level of the spot region in the current frame laser spot image; Reduce the current exposure time to the first exposure time; The camera's exposure time is adjusted to the first exposure time to acquire a single-frame spot image at the first optical path displacement point under the first exposure time, and the peak gray level of the spot region in the single-frame spot image is determined. The exposure time corresponding to the target peak gray level is calculated based on the peak gray level of the spot region in the single-frame spot image and the linear response model. The exposure time corresponding to the target peak gray level is the target exposure time.

5. The method according to claim 1, characterized in that, The target exposure time is calculated as follows: Acquire historical exposure data, which includes the exposure time and peak grayscale of the spot area of ​​N optical path displacement points before the first optical path displacement point, where N is an integer greater than or equal to 1 and less than the total number of optical path displacement points of the M² measurement system. Based on the historical exposure data and the pre-built position grayscale model, the maximum grayscale prediction value of the spot area at the first optical path displacement point is determined. The exposure time prediction value of the first optical path displacement point is calculated using the pre-calibrated linear response model of the camera and the maximum gray level prediction value of the spot area; The exposure time modification amount is determined based on the maximum grayscale prediction value of the light spot area and the preset target peak grayscale, and the target exposure time is determined based on the exposure time modification amount and the exposure time prediction value.

6. The method according to claim 1, characterized in that, The step of determining whether the spot region of the current frame laser spot image meets the predetermined exposure requirements based on the peak grayscale of the spot region in the current frame laser spot image includes: Determine whether the peak grayscale of the spot region in the current frame laser spot image is within the predetermined target brightness range; If the peak grayscale of the spot region in the current frame laser spot image is within the target brightness range, then the spot region in the current frame laser spot image is determined to meet the exposure requirements. If the peak gray level of the spot region in the current frame laser spot image is less than the lower limit of the target brightness range or greater than the upper limit of the target brightness range, then it is determined that the spot region in the current frame laser spot image does not meet the exposure requirements.

7. The method according to claim 1, characterized in that, The method further includes: performing bad pixel detection and correction on the current frame laser spot image before identifying the spot in the current frame laser spot image to obtain the spot region pixel set.

8. A laser spot image acquisition device, characterized in that, The laser spot image acquisition device is used in the camera of the M² measurement system, and the laser spot image acquisition device includes: The image acquisition unit is used to acquire the current frame laser spot image of the first optical path displacement point in the beam propagation direction of the laser system under test, wherein the first optical path displacement point is any optical path displacement point among all optical path displacement points of the M² measurement system; and to acquire the next frame laser spot image at the first optical path displacement point at the target exposure time. A spot recognition unit is used to identify spots in the current frame laser spot image to obtain a pixel set of spot regions. A grayscale determination unit is used to determine the peak grayscale of the spot region in the current frame laser spot image using the pixel set of the spot region. An exposure detection unit is used to determine whether the spot area of ​​the current frame laser spot image meets the predetermined exposure requirements based on the peak gray level of the spot area in the current frame laser spot image. An exposure adjustment unit is used to determine the target exposure time and adjust the camera's exposure time to the target exposure time when the spot area in the current frame laser spot image does not meet the exposure requirements. The image transmission unit is configured to send the current frame laser spot image to the host computer of the M² measurement system when the spot area in the current frame laser spot image meets the exposure requirements; and to send the next frame laser spot image at the first optical path displacement point acquired at the target exposure time to the host computer of the M² measurement system.

9. A camera, characterized in that, The camera is used in an M² measurement system. The camera includes a processor and a memory. The memory stores a computer program that, when read by the processor, executes the method according to any one of claims 1 to 7.

10. An M² measurement system, characterized in that, The M² measurement system includes a host computer, an automated displacement platform, auxiliary optical elements, and a camera. The automated displacement platform, auxiliary optical elements, and camera are respectively connected to the host computer. The automated displacement platform is used to carry the camera and, under the control of the host computer, moves the camera to multiple predetermined optical path displacement points along the beam propagation direction of the laser system under test. The auxiliary optical elements are used to assist the camera in capturing laser spot images of the laser system under test. The camera is used to acquire laser spot images of the laser system under test at multiple predetermined optical path displacement points in the beam propagation direction using the method described in any one of claims 1 to 7 and send them to the host computer. The host computer is used to determine the M² factor of the laser system under test using the laser spot images of the multiple predetermined optical path displacement points.

Images