Automatic calibration method and device based on fine inspection camera edge finding and storage medium

Abstract

The invention discloses an automatic calibration method and device based on fine inspection camera edge finding and a storage medium, which are used for improving the calibration efficiency and avoiding artificial errors when a fine inspection camera aligns with a mark point. The method comprises the following steps: obtaining a fixed offset through advanced teaching; according to the fixed offset, the picture center of the fine detection camera falls into a calibration plate through a motion control assembly, and a calibration point is arranged in the calibration plate; the motion control assembly controls the fine detection camera to carry out edge finding motion so as to collect a characteristic pattern of the calibration plate, the linear edge and the angular point of the inner frame of the calibration plate are identified according to the characteristic pattern, and the fine detection camera is guided to carry out edge finding motion and angular point alignment; determining a first mechanical coordinate at the moment; according to the physical parameters of the calibration plate and the first mechanical coordinate, determining a second mechanical coordinate when the picture center of the fine detection camera is aligned with the center of a calibration point on the calibration plate; and calculating an affine transformation relation according to a pre-collected third mechanical coordinate and a pre-collected second mechanical coordinate, and completing calibration.

Description

Technical Field

[0001] The present application relates to the field of machine vision technology, and in particular to an automatic calibration method, device and storage medium based on edge inspection of a precision inspection camera. Background Art

[0002] In the panel industry, there is a composite inspection system consisting of a main inspection camera and a precision inspection camera. The main inspection camera is used to detect the defect location and defect type, and the precision inspection camera is used to further determine the hierarchical position of the defect in the display screen. In order to move the defects detected under the field of view of the main inspection camera to the field of view of the precision inspection camera to further determine the hierarchical position of the defects, it is necessary to calibrate the conversion relationship between the image coordinate system of the main inspection camera and the mechanical coordinate system of the stage. The efficiency and accuracy of the calibration determine to a certain extent whether the precision inspection system can work. Therefore, it is very important to improve the calibration efficiency and calibration accuracy of the image coordinate system of the main inspection camera and the X, Y stage coordinate system that controls the movement of the precision inspection camera.

[0003] Since the field of view of the precision inspection camera is very small, it can only capture part of the calibration plate. The traditional solution first uses the main inspection camera to capture the complete calibration plate image, extracts the image coordinates of the center of the mark point (Mark) on the calibration plate, and then manually adjusts the stage position to align the center of the precision inspection camera with the center of the Mark point. At the same time, the stage position of the Mark point is recorded, and finally the required calibration matrix is ​​solved based on the above coordinates.

[0004] The above calibration process requires manual adjustment of the stage position so that the center of the field of view of the precision inspection camera is aligned with the center of the mark point on the calibration plate. This step is very prone to human error. Minor deviations in human visual judgment and hand operation may affect the accuracy of the alignment, and thus affect the accuracy of the subsequent calibration matrix. The entire calibration process is highly dependent on human participation. For each mark point that needs to be calibrated, manual operation is required, which greatly increases the time and labor cost of the calibration work, and the degree of automation is very low. This not only limits the efficiency of the calibration work, but also increases the uncertainty and risk in the operation process. Summary of the invention

[0005] In order to solve the above technical problems, the present application provides an automatic calibration method, device and storage medium based on edge inspection of a precision inspection camera.

[0006] The technical solution provided in this application is described below: The first aspect of the present application provides an automatic calibration method based on edge inspection of a precision inspection camera, the calibration method comprising: A fixed offset is obtained by teaching in advance, where the fixed offset is the distance from the main inspection camera to the precision inspection camera; According to the fixed offset, the center of the image of the precision inspection camera is made to fall inside the calibration plate through the motion control component, and the calibration point is arranged inside the calibration plate; Control the precision inspection camera to perform patrol motion through the motion control component to collect the characteristic image of the calibration plate, and identify the straight line edge and corner points of the inner frame of the calibration plate according to the characteristic image, and continue to control the precision inspection camera to perform patrol motion and corner point alignment accordingly; Determine a first mechanical coordinate when the center of the image of the precision inspection camera is aligned with the corner point, the first mechanical coordinate being the coordinate of the stage; Determine, according to the physical parameters of the calibration plate and the first mechanical coordinates, a second mechanical coordinate when the center of the image of the precision inspection camera is aligned with the center of the calibration point on the calibration plate, wherein the second mechanical coordinates are the coordinates of the stage; The calibration is completed by calculating the affine transformation relationship based on the pre-collected third mechanical coordinates and the second mechanical coordinates, and the third mechanical coordinates are the image coordinates of the main inspection camera.

[0007] Optionally, after obtaining the fixed offset by teaching in advance, the calibration method further includes: Calibrate the relationship between the precision inspection camera image coordinate system and the X, Y stage coordinate system, and construct a transformation matrix; The calibration plate is randomly placed at the main inspection station, the main inspection camera is controlled to collect images, and the third mechanical coordinates are extracted through the image algorithm, and the third mechanical coordinates are the image coordinates of the main inspection camera.

[0008] Optionally, the calibration of the relationship between the precision inspection camera image coordinate system and the X, Y stage coordinate system to construct a transformation matrix includes: When a corner point of the calibration plate is located in the picture of the precision inspection camera, controlling the precision inspection camera to capture a first image, and extracting first corner point coordinates of the corner point in the first image; The motion control component controls the precision inspection camera to move along the X-axis or the Y-axis separately, and the precision inspection camera collects the second image and the third image, and extracts the second corner point coordinates and the third corner point coordinates of the corner point; Calculating a first offset of the calibration plate after movement along the X-axis and the Y-axis; A transformation matrix is ​​calculated according to the first corner point coordinates, the second corner point coordinates, the third corner point coordinates and the first offset.

[0009] Optionally, the corner points include 5 inner frame corner points; The precision inspection camera is controlled by a motion control component to perform patrol motion to collect a feature map of the calibration plate, and the straight line edge and corner points of the inner frame of the calibration plate are identified according to the feature map, thereby guiding the precision inspection camera to perform patrol motion and corner point alignment, including: The precision inspection camera is controlled by a motion control component to perform patrol motion to collect the feature map of the calibration plate, and the straight edge of the inner frame and the five inner frame corner points of the calibration plate are identified based on the feature map, thereby guiding the precision inspection camera to perform patrol motion and align the five inner frame corner points.

[0010] Optionally, the motion control component is used to control the precision inspection camera to perform patrol motion to collect the feature map of the calibration plate, and the straight edge of the inner frame and five inner frame corner points of the calibration plate are identified according to the feature map, thereby guiding the precision inspection camera to perform patrol motion and align the five inner frame corner points, including: Step 1: Control the precision inspection camera to move along the X-axis or Y-axis direction with a specified step length through the motion control component; Step 2: After each movement, control the precision inspection camera to collect the feature map of the calibration plate, and extract the image features in the feature map through an image processing algorithm; Step 3: Determine whether the image features include straight line edges and inner frame corner points; If the feature map does not contain straight edges and inner frame corner points, return to step 1; If the feature map only includes straight line edges, a special step length is calculated by combining the starting point information of the straight line edges and a pre-constructed transformation matrix, the precision inspection camera is controlled to move with the special step length, and the process returns to step 2 after the movement; If the feature image contains both straight edges and inner frame corners, the inner frame corners are identified, the center of the image of the precision inspection camera is controlled to align with the inner frame corners, and an autofocus operation is performed; Step 4: loop step 1 to step 3 until all five inner frame corner points in the calibration plate are identified.

[0011] Optionally, after step 4, the method further includes: Step 5: Determine whether all five inner frame corner points in the calibration plate are obtained; If yes, stop looping steps 1 to 3; Step 6: If the loop does not stop, recalibrate the relationship between the precision inspection camera image coordinate system and the X, Y stage coordinate system, and update the transformation matrix; Step 7: After determining that there are no corner points in the precision inspection camera image, loop steps 1 to 3 in another direction until all five inner frame corner points in the calibration plate are identified, wherein the other direction indicates a direction different from the last movement direction of the precision inspection camera.

[0012] Optionally, the second mechanical coordinates when the center of the image of the precision inspection camera is aligned with the center of the calibration point on the calibration plate according to the physical parameters of the calibration plate and the first mechanical coordinates, the second mechanical coordinates being the coordinates of the stage, include: Calculating the calibration point coordinates of each calibration point on the calibration plate according to the physical parameters of the calibration plate; Calculate a two-dimensional vector according to the first mechanical coordinates; The second mechanical coordinate is calculated according to the two-dimensional vector, the coordinates of the calibration point and the first mechanical coordinate.

[0013] Optionally, calculating the two-dimensional vector according to the first mechanical coordinates includes: Use the following formula 1 to calculate the two-dimensional vector: Formula 1; in, and Indicates the first mechanical coordinates of two beveled corner points among the five inner frame corner points on the calibration plate on the stage; Represents the vector component in the X-axis direction in two-dimensional space; Represents the vector component in the Y-axis direction in two-dimensional space.

[0014] Optionally, calculating the second mechanical coordinate according to the two-dimensional vector, the coordinates of the calibration point and the first mechanical coordinate includes: The second machine coordinate is calculated using the following formula 2: Formula 2; in, represents the coordinates of the calibration points, that is, the coordinates of the center of each marking point in the coordinate system of the physical calibration board, and i is the number of marking points on the calibration board; Indicates the second mechanical coordinate, that is, the mechanical coordinate when the center of the precision inspection camera's screen is aligned with the center of the mark point.

[0015] Optionally, the step of calculating an affine transformation relationship based on the pre-collected third mechanical coordinates and the second mechanical coordinates to complete the calibration includes: Use the following formula 3 to get the affine transformation relationship: Formula 3; Among them, M represents the affine transformation relationship, Represents the two-dimensional vector obtained by converting the second mechanical coordinates, Represents the two-dimensional vector obtained by converting the third machine coordinate system.

[0016] The second aspect of the present application provides an automatic calibration device based on edge inspection camera inspection, the calibration device comprising: A teaching unit, used to teach in advance to obtain a fixed offset, where the fixed offset is the distance and direction required to move from the main inspection camera to the precision inspection camera; A first control unit, used to make the center of the picture of the precision inspection camera fall inside the calibration plate, wherein the calibration plate is provided with calibration points inside; A second control unit is used to control the precision inspection camera to move along the X-axis or Y-axis direction with a specified step length to collect a feature map of the calibration plate, and identify target corner points in the calibration plate according to the feature map; A first processing unit, used to determine a first mechanical coordinate when the center of the image of the precision inspection camera is aligned with a corner point, wherein the first mechanical coordinate is a coordinate of the stage; A second processing unit is used to determine a second mechanical coordinate when the center of the image of the precision inspection camera is aligned with the center of the calibration point on the calibration plate, wherein the second mechanical coordinate is the coordinate of the stage; The conversion unit is used to calculate the affine transformation relationship and complete the calibration.

[0017] Optionally, the calibration device further includes: The calibration unit is used to calibrate the relationship between the image coordinate system of the precision inspection camera and the X, Y stage coordinate system, and construct a conversion matrix; The extraction unit is used to control the main inspection camera to collect images and extract the third mechanical coordinates through an image algorithm, where the third mechanical coordinates are the image coordinates of the main inspection camera.

[0018] The third aspect of the present application provides an automatic calibration device based on edge inspection camera patrol, the calibration device comprising: Processor, memory, input-output unit, and bus; The processor is connected to the memory, the input and output unit, and the bus; The memory stores a program, and the processor calls the program to execute the first aspect and the optional calibration method of any one of the first aspect.

[0019] A fourth aspect of the present application provides a computer-readable storage medium, on which a program is stored. When the program is executed on a computer, the program executes the first aspect and any optional calibration method in the first aspect.

[0020] It can be seen from the above technical solutions that this application has the following advantages: In this application, a fixed offset is first obtained by teaching in advance. After the main inspection camera with a large field of view at the main inspection station completes the acquisition of the calibration plate image, the fixed offset is used to quickly and accurately adjust the stage position so that the center of the precision inspection camera can accurately fall inside the calibration plate. This process reduces the time and error of manual adjustment and improves the efficiency and stability of calibration. According to the fixed offset, there is no need for tedious manual adjustment or multiple trial and error. The center of the picture of the precision inspection camera can be accurately aligned with the inside of the calibration plate, which also reduces the detection error caused by position deviation.

[0021] The precise control of the motion control component ensures that the precision inspection camera can move stably in the X-axis or Y-axis direction according to the preset specified step size. This high-precision motion control enables the precision inspection camera to capture the feature map of the calibration plate at different positions, providing a data basis for subsequent corner point recognition. Through detailed analysis of the feature map, the target corner points in the calibration plate can be accurately identified. From camera motion control to feature map acquisition, to fully automated processing of corner point recognition, the entire recognition process can be completed automatically without human intervention, improving calibration efficiency.

[0022] By determining the first mechanical coordinate when the center of the precision inspection camera screen is aligned with the target corner point, and ensuring that the first mechanical coordinate is used as the coordinate of the stage, the operation process can be simplified and frequent coordinate conversion or calibration in subsequent steps can be avoided. By combining the physical parameters of the calibration plate and the first mechanical coordinate, the second mechanical coordinate can be accurately calculated, that is, the coordinate of the stage when the center of the precision inspection camera screen is aligned with the center of any calibration point on the calibration plate. Once the second mechanical coordinate is determined, the stage can be quickly moved to the specified position to align the center of the precision inspection camera screen with the center of the calibration point on the calibration plate.

[0023] By calculating the affine transformation relationship, the image coordinates of the main inspection camera can be accurately converted to the actual mechanical coordinates of the stage, or vice versa. This transformation relationship makes it possible to position and calibrate with high precision, ensuring the precise alignment between the main inspection camera and the precision inspection camera, thereby improving the positioning accuracy of the overall system. The affine transformation relationship can be used to perform coordinate conversion and calibration operations without the need for tedious manual adjustments every time, improving calibration efficiency and avoiding the introduction of manual errors when aligning the precision inspection camera to the mark points. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solution in the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1This is a schematic diagram of an embodiment of the automatic calibration method based on edge inspection camera inspection of the present application; Figure 2 A schematic diagram of an embodiment of a method for obtaining a conversion matrix and a third mechanical coordinate in the present application; Figure 3 A schematic diagram of an embodiment of a method for constructing a conversion matrix for the present application; Figure 4 A schematic diagram of an embodiment of a method for identifying all five inner frame corner points in a calibration plate according to the present application; Figure 5 A schematic diagram of an embodiment of a method for obtaining a second mechanical coordinate in the present application; Figure 6 This is a structural schematic diagram of an automatic calibration device based on edge inspection camera inspection in this application; Figure 7 This is another structural schematic diagram of the automatic calibration device based on edge inspection camera inspection of the present application; Figure 8 A schematic diagram of the process of obtaining the offset from the main inspection station to the fine inspection station for teaching this application; Fig. 9 A schematic diagram of the structure of the calibration board for this application; Fig.10 Schematic diagram of the process of calibrating the relationship between the precision inspection camera image coordinate system and the stage coordinate system for this application. DETAILED DESCRIPTION

[0026] The present application discloses an automatic calibration method, device and storage medium based on edge patrol of a precision inspection camera, which are used to improve the calibration efficiency and avoid the introduction of artificial errors when the precision inspection camera aligns the marking points.

[0027] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0028] The method of the present application can be applied to a server, a device, a terminal or other devices with logic processing capabilities, and the present application does not limit this. For the convenience of description, the following description is made by taking the execution subject as an example of a terminal.

[0029] See also Figure 1 The present application first provides an embodiment of an automatic calibration method based on edge inspection of a precision inspection camera, the embodiment comprising: S101, obtaining a fixed offset by teaching in advance, where the fixed offset is the distance and direction required to move from the main inspection camera to the precision inspection camera; In this embodiment, it is first necessary to obtain a fixed offset by teaching in advance. The main inspection station is the preset inspection position of the large-field main inspection camera, the fine inspection station is the preset inspection position of the fine inspection camera, and the fixed offset is the distance and direction that the calibration plate needs to move from the main inspection station to the fine inspection station and the center of the fine inspection camera falls inside the calibration plate.

[0030] After obtaining the fixed offset, the final fixed offset is saved in the system configuration file for use in subsequent calibration processes.

[0031] Please refer to Figure 8 , Figure 8 This is a flow chart showing how to get the offset from the main inspection station to the fine inspection station. The green frame in the figure is the main inspection station. At this time, it shows that the fine inspection camera has not been adjusted.

[0032] Please refer to Fig. 9 , Fig. 9 This is a structural diagram of a calibration plate, which has 9 clear marking points so that the camera can accurately capture and identify them. The inherent physical parameters of the calibration plate are known. The midpoint of the bevel edge of the calibration plate is set, and the physical coordinate system (right-hand coordinate system) of the calibration plate is established with the midpoint. The y-axis of the coordinate system is a unit vector perpendicular to the bevel edge and pointing from the inside of the calibration plate to the outside. The x-axis of the physical coordinate system of the calibration plate can be obtained by rotating the y-axis according to the properties of the right-hand coordinate system. On this basis, the coordinates of the center of each mark point in the physical coordinate system of the calibration plate can be obtained according to the inherent physical parameters of the calibration plate.

[0033] S102, according to the fixed offset, the center of the image of the precision inspection camera is made to fall inside the calibration plate through the motion control component, and the calibration point is set inside the calibration plate; The motion control component consists of a high-precision XYZ platform and three sets of high-precision stepper motors and controllers. The control signal is output by the system end to accurately adjust the spatial shooting position of the main inspection camera and the precision inspection camera.

[0034] The system will read the previously taught and saved fixed offsets from the configuration file; the system parses the fixed offsets and converts them into instructions that the motion control components can understand, such as the number of motor steps, rotation angles, or movement distances of the mobile platform.

[0035] After receiving the command, the motion control component will drive the stage to move according to the specified distance and direction, and stop at the target position; when the stage moves to the target position, the center of the image of the precision inspection camera has accurately fallen inside the calibration plate.

[0036] S103, controlling the precision inspection camera to perform patrol motion through a motion control component to collect a feature map of the calibration plate, and identifying the straight line edge and corner points of the inner frame of the calibration plate according to the feature map, and continuing to control the precision inspection camera to perform patrol motion and corner point alignment accordingly; After ensuring that the center of the image of the precision inspection camera falls inside the calibration plate, the system sends a movement command to the stage through the motion control component to move the center of the image of the precision inspection camera along the X-axis or Y-axis. After each movement into place, the precision inspection camera immediately captures the image of the calibration plate to form a series of feature maps.

[0037] The system detects the inner frame straight line edges and corner points of the feature map, and matches the detected corner points with the preset target corner points on the calibration plate. By comparing the position, shape and other features of the corner points, the corner points that match the target corner points are screened out. The target corner points are preset as the two bevel corner points of the five inner frame corner points of the calibration plate.

[0038] S104, determining the first mechanical coordinates when the center of the image of the precision inspection camera is aligned with the corner point, the first mechanical coordinates being the coordinates of the stage; After the identified corner point is determined as the target corner point, since the corner point has been located in the precision inspection camera coordinate system, a translation vector needs to be calculated so that the center of the picture coincides with the target corner point. The translation vector is defined as the image offset.

[0039] According to the image offset between the current corner point and the image center of the precision inspection camera, the X and Y axis movement of the stage is calculated to move the corner point to the image center of the precision inspection camera, and the stage is moved to align the corner point with the image center of the precision inspection camera. The system records the first mechanical coordinate at this time. , where n represents the number of corner points in the calibration plate.

[0040] S105, determining a second mechanical coordinate when the center of the image of the precision inspection camera is aligned with the center of the calibration point on the calibration plate according to the physical parameters of the calibration plate and the first mechanical coordinate, the second mechanical coordinate being the coordinate of the stage; Based on the calibration plate coordinate system established in the aforementioned step S101, the coordinates of the center points of each mark in the physical calibration plate coordinate system are known according to the inherent parameters of the calibration plate: , where n is the number of Mark points on the calibration board.

[0041] In the aforementioned step S104, the first mechanical coordinates of the preset corner points (two bevel corner points) are extracted. and .

[0042] According to the Mark point coordinates of the physical calibration plate coordinate system on the calibration plate and the first mechanical coordinates, calculate the second mechanical coordinates of each Mark point in the stage coordinate system , where n is the number of Mark points on the calibration board.

[0043] S106 , calculating an affine transformation relationship according to the pre-collected third mechanical coordinates and the second mechanical coordinates, completing the calibration, and the third mechanical coordinates are the main inspection camera image coordinates.

[0044] An affine transformation is a two-dimensional coordinate transformation that keeps straight lines and parallelism unchanged, but can change the size, orientation, and position of a figure. Mathematically, an affine transformation can be represented by a 3x3 matrix, where one element constitutes the rotation and scaling part and the other element constitutes the translation part.

[0045] According to the third mechanical coordinate And the second mechanical coordinate The affine transformation matrix M is converted, and the affine transformation matrix M is used to calibrate the affine transformation relationship between the image coordinate system of the large-field main inspection camera and the stage coordinate system, thereby completing the calibration.

[0046] In this embodiment, a fixed offset is first obtained by teaching in advance. After the main inspection camera with a large field of view at the main inspection station completes the acquisition of the calibration plate image, the fixed offset can be used to quickly and accurately adjust the stage position so that the center of the precision inspection camera can accurately fall inside the calibration plate. This process reduces the time and error of manual adjustment and improves the efficiency and stability of calibration. According to the fixed offset, there is no need for tedious manual adjustment or multiple trial and error. The center of the picture of the precision inspection camera can be accurately aligned with the inside of the calibration plate, which also reduces the detection error caused by position deviation.

[0047] The precise control of the motion control component ensures that the precision inspection camera can move stably in the X-axis or Y-axis direction according to the preset specified step size. This high-precision motion control enables the precision inspection camera to capture the feature map of the calibration plate at different positions, providing a data basis for subsequent corner point recognition. Through detailed analysis of the feature map, the corner points in the calibration plate can be accurately identified. From camera motion control to feature map acquisition, to fully automated processing of corner point recognition, the entire recognition process can be completed automatically without human intervention, improving calibration efficiency.

[0048] By determining the first mechanical coordinate when the center of the precision inspection camera screen is aligned with the corner point, and ensuring that the first mechanical coordinate is used as the coordinate of the stage, the operation process can be simplified and frequent coordinate conversion or calibration in subsequent steps can be avoided. By combining the physical parameters of the calibration plate and the first mechanical coordinate, the second mechanical coordinate can be accurately calculated, that is, the coordinate of the stage when the center of the precision inspection camera screen is aligned with the center of any calibration point on the calibration plate. Once the second mechanical coordinate is determined, the stage can be quickly moved to the specified position to align the center of the precision inspection camera screen with the center of the calibration point on the calibration plate.

[0049] By calculating the affine transformation relationship, the image coordinates of the main inspection camera can be accurately converted to the actual mechanical coordinates of the stage, or vice versa. This transformation relationship makes it possible to position and calibrate with high precision, ensuring the accurate calibration between the image coordinate system of the main inspection camera with a large field of view and the coordinate system of the stage, thereby improving the positioning accuracy of the overall system. The affine transformation relationship can be used to perform coordinate conversion and calibration operations without the need for tedious manual adjustments every time, improving calibration efficiency and avoiding the introduction of artificial errors when aligning the mark points of the precision inspection camera.

[0050] See also Figure 2 In a specific embodiment, after obtaining a fixed offset through advance teaching, the present application provides an embodiment of a method for obtaining a transformation matrix and a third mechanical coordinate, including: S201, calibrate the relationship between the image coordinate system of the precision inspection camera and the X, Y stage coordinate system, and construct a conversion matrix; Place the calibration plate on the stage, and move the stage so that different point features on the calibration plate appear in the field of view of the precision inspection camera in sequence. Point features can be inner frame corners, marker points, or any identifiable points on the marker plate. For each point feature, record its position in the image coordinate system of the precision inspection camera (i.e., image coordinates), as well as the X and Y coordinates (mechanical coordinates) of the stage at this time.

[0051] Using the acquired image coordinates and mechanical coordinates, the transformation matrix between the precision inspection camera image coordinate system and the X, Y stage coordinate system is calculated through mathematical methods (such as the least square method, etc.). This matrix can convert image coordinates into mechanical coordinates, or vice versa.

[0052] S202, randomly placing the calibration plate at the main inspection station, controlling the main inspection camera to collect images, and extracting the third mechanical coordinates through an image algorithm, the third mechanical coordinates being the image coordinates of the main inspection camera.

[0053] The calibration plate is randomly placed on the main inspection station. Here, "random" means that the position and direction of the calibration plate should not be determined in advance to simulate various possible situations in actual work.

[0054] Start the main inspection camera and adjust the parameters to trigger the camera to capture the image of the current position of the calibration plate.

[0055] Use image processing algorithms to identify the marker points in the calibration plate image and calculate the position of each marker point in the image, i.e. the third mechanical coordinate , where n is the number of Mark points on the calibration board.

[0056] In this embodiment, by constructing a transformation matrix, it is possible to accurately convert points in the precision inspection camera image to actual positions on the stage, or to convert points on the stage to positions in the image. Once the transformation matrix is ​​established, coordinate conversion can be performed quickly without the need for tedious manual adjustments each time. By reducing the error introduced by improper coordinate conversion, it is possible to ensure that the system can maintain high-precision positioning capabilities under various conditions.

[0057] By randomly placing calibration plates, various positions and angles that may occur in the actual production environment can be simulated, thus ensuring that the camera system can accurately capture and identify targets under various conditions. The image algorithm can automatically extract the third mechanical coordinate, reducing the workload of manual calibration and data processing, while helping to eliminate the influence of factors such as camera lens distortion and installation errors on the measurement results, thereby simplifying the calibration process.

[0058] See also Figure 3 In a specific embodiment, the present application provides an embodiment of a method for constructing a conversion matrix, including: S301, when a corner point of the calibration plate is located in the picture of the precision inspection camera, controlling the precision inspection camera to capture a first image, and extracting first corner point coordinates of the corner point in the first image; S302, the motion control component controls the precision inspection camera to move along the X-axis or the Y-axis separately, and the precision inspection camera collects the second image and the third image, and extracts the second corner point coordinates and the third corner point coordinates of the corner point; Please refer to Fig.10 , Fig.10 This is a flow chart of calibrating the relationship between the image coordinate system of the precision inspection camera and the stage coordinate system. First, the stage is located at When the precision inspection camera is controlled to collect the first image, the first corner point coordinates of the corner point in the first image are extracted. .

[0059] The motion control component controls the precision inspection camera to move the Y axis independently, collects the second image, and extracts the second corner point coordinates of the corner point The motion control component controls the precision inspection camera to restore the stage position. , then move the X axis alone, collect the third image, and extract the coordinates of the second corner point of the corner point .

[0060] S303, calculating a first offset of the calibration plate after movement along the X-axis and the Y-axis; S304: Calculate a transformation matrix according to the first corner point coordinates, the second corner point coordinates, the third corner point coordinates and the first offset.

[0061] Based on formula 4, the first inner border corner coordinates, the second inner border corner coordinates and the third inner border corner coordinates are calculated: Formula 4; in, is the movement direction and distance of the stage along the X and Y axes, is the first offset of the corner point of the calibration plate in the image coordinate system of the precision inspection camera, It is a transformation matrix that converts the X and Y axis platform offsets into the corresponding point offsets in the precision inspection camera image.

[0062] In this embodiment, the precision inspection camera is controlled to capture the first image when the corner point of the calibration plate is in the picture, and the first corner point coordinates of the corner point are extracted, which provides an accurate initial reference point for subsequent calculations. The precision inspection camera is controlled to move along the X-axis or Y-axis separately through the motion control component, and the second image and the third image are captured, which can accurately simulate the displacement of the camera in different directions. Based on the extracted second corner point coordinates and the third corner point coordinates, combined with the initial first corner point coordinates, the conversion matrix between the precision inspection camera image coordinate system and the stage coordinate system can be accurately calculated.

[0063] The entire process is implemented through programmed control, and steps such as image acquisition, corner point extraction, offset calculation, and conversion matrix calculation can be automatically completed without human intervention. This not only improves the accuracy of the calculation, but also reduces the errors caused by human factors, making the entire system more intelligent and automated.

[0064] See also Figure 4 In a specific embodiment, the corner points of the calibration plate include five inner frame corner points. The present application provides an embodiment of a method for identifying all five inner frame corner points in the calibration plate, including: Step 1: Use the motion control component to control the precision inspection camera to move along the X-axis or Y-axis with a specified step length; The system sets the specified step length of the precision inspection camera movement in advance. This specified step length is usually determined based on actual needs, camera resolution, field of view, and system accuracy requirements.

[0065] According to the calibration requirements, it is decided whether the precision inspection camera moves along the X-axis or Y-axis. The movement direction can be along the X-axis, along the Y-axis, or both.

[0066] Step 2: After each movement, the precision inspection camera is controlled to collect the feature map of the calibration plate, and the image features in the feature map are extracted through the image processing algorithm; After each precision inspection camera movement, the motion control component sends a signal to the system indicating that the precision inspection camera has completed the specified step length of movement.

[0067] After receiving the signal, the system triggers the precision inspection camera to collect images. The precision inspection camera captures the image of the calibration plate through its lens and converts it into a digital signal, namely a feature map. The feature map contains image information such as color, brightness, texture, and shape.

[0068] Before extracting image features, it is usually necessary to preprocess the acquired feature maps. The preprocessing steps may include denoising, contrast enhancement, color balance adjustment, etc. to improve the quality and clarity of the image.

[0069] After preprocessing, image features in the feature map are extracted using image processing algorithms. Image processing algorithms can be edge detection, corner detection, template matching, etc. Image features refer to significant features in an image that can be used to distinguish different objects or scenes, such as edges, corners, texture patterns, etc. The extracted image features will be used for subsequent image matching, recognition, analysis or positioning tasks.

[0070] Step 3: Determine whether the image features contain inner border corner points; If the image features do not contain straight edges and inner border corners, return to step 1; If the image features only include straight line edges, the special step length is calculated by combining the starting point information of the straight line edges and the pre-built transformation matrix, the precision inspection camera is controlled to move with the special step length, and the process returns to step 2 after the movement; If the image features include both straight edges and inner frame corners, the inner frame corners are identified, and the center of the image of the precision inspection camera is controlled to align with the inner frame corners; First, image analysis is performed on the image features extracted from step 2. Image features include edges, corners, textures, etc. In this application, the main focus is on whether straight edges and inner frame corners are included. Straight edges are usually represented by straight line frame in the calibration plate, while inner frame corners are the intersection points of the straight line frame of the calibration plate, usually located on the inner frame of the calibration plate.

[0071] If the image features contain neither straight edges nor inner frame corners, this usually means that the precision inspection camera may not be aligned with the calibration plate frame, or the calibration plate frame is not within the camera's field of view. In this case, the system returns to step 1.

[0072] If the image features only contain straight edges but no inner border corners, this may be because the precision inspection camera is aimed at the calibration plate border but not completely at the border corners of the calibration plate. At this time, it is necessary to calculate the special step length by combining the starting point information of the straight edge and the pre-built transformation matrix. The motion control component can control the precision inspection camera to move along the straight line with this special step length to obtain the inner border corners of the calibration plate more quickly. After the precision inspection camera completes the movement, return to step 2, re-capture the image and extract features to check whether the inner border corners are successfully captured.

[0073] The special step length calculated by equation 5 is: Formula 5; in, Represents a special step size, , Represents the starting point information, Represented as a transformation matrix The inverse matrix of .

[0074] If the image features contain both straight edges and inner frame corners, this means that the precision inspection camera has been aligned with the inner frame of the calibration plate. In this case, the system identifies and locates the inner frame corners. Once the inner frame corners are identified, the motion control component controls the center of the precision inspection camera to align the corners. At the same time, the precision inspection camera's autofocus operation can be used to improve the accuracy of corner recognition and alignment to ensure that the corners are located in the center of the image. The current corner positions are recorded and stored in the system's database.

[0075] Step 4: Repeat steps 1 to 3 until all 5 inner frame corner points of the calibration plate are identified; There are 5 inner frame corner points in the calibration plate, and only 1 inner frame corner point can be collected in one cycle, so multiple cycles are required to identify all 5 inner frame corner points and collect the intersection coordinates of the 5 inner frame corner points to provide data support for subsequent calibration.

[0076] Step 5: Determine whether all five inner frame corner points in the calibration plate are obtained; if so, stop looping steps 1 to 3; In each loop, when the system recognizes the inner border corners, it records the position information of these corners. These recorded corner point information will be saved in a data structure, such as a list or array, for subsequent use.

[0077] The system checks the number of recorded inner border corner points. If the number is equal to 5, it means that all inner border corner points in the calibration plate have been successfully identified and recorded. In addition to checking the number of corner points, the system also performs position verification to ensure that 5 different corner point positions are identified.

[0078] Step 6: If the loop does not stop, recalibrate the relationship between the precision inspection camera image coordinate system and the X, Y stage coordinate system, and update the transformation matrix; If the loop does not stop, it means that the system has not recognized all five inner border corner points.

[0079] Since the autofocus operation is performed after the focus is found in the aforementioned step 3, the Z-axis transformation requires recalibration of the relationship between the image coordinate system of the precision inspection camera and the X, Y stage coordinate system; Based on the current position, the system recalibrates the relationship between the precision inspection camera image coordinate system and the X, Y stage coordinate system, and updates the transformation matrix ; Step 7: After determining that there are no corner points in the precision inspection camera image, loop steps 1 to 3 in the other direction until all 5 inner frame corner points in the calibration plate are identified, and the other direction represents a direction different from the last movement direction of the precision inspection camera.

[0080] Because two straight edges in different directions are generally extracted from the corners of the inner frame of the calibration plate, in order to determine the reference direction for the next edge patrol stage movement, it is necessary to refer to the output detection result of the previous frame of the precision inspection camera screen image. If there is no corner feature in the previous frame of the image, then another straight edge direction that is inconsistent with the output line edge direction of the previous frame of the image is selected as the reference direction for the next edge patrol; Then, based on the starting point information of the other straight line edge and the transformation matrix updated in step 6 Calculate the next movement direction and amount of the stage, and loop steps 1 to 3 to control the precision inspection camera to capture images.

[0081] The system stops looping until all five inner frame corner points of the calibration plate are identified.

[0082] In this embodiment, the motion control component can accurately control the precision inspection camera to move along the X-axis or Y-axis with a specified step length, ensuring that the precision inspection camera can move according to the preset path and speed. After each movement of the precision inspection camera, the feature map of the calibration plate is collected to extract key image features in the feature map, such as edges, corners, etc.

[0083] The system can determine whether the image features contain inner border corners and whether they only contain straight edges. Based on the judgment results of the image features, the system can flexibly adjust the position of the camera. If the image features do not contain straight edges and inner border corners, return to step 1 to reposition the camera; if it only contains straight edges, calculate the special step length and adjust it; if it contains both straight edges and inner border corners, perform corner recognition and camera alignment.

[0084] By looping through steps 1 to 3, the system can ensure that all five inner frame corners in the calibration plate are identified. This loop mechanism ensures the integrity and accuracy of the system and avoids calibration errors or positioning failures caused by missing corners. The loop execution process not only ensures the complete identification of corners, but also improves the efficiency and accuracy of the system through continuous adjustment and calibration. This enables the system to complete calibration in a shorter time and provide more accurate positioning results.

[0085] The system determines whether the recognition task of the inner frame corner points of the calibration plate is completed. If the recognition task is not completed, recalibration is performed and looped in another direction to recognize all 5 inner frame corner points of the calibration plate.

[0086] See also Figure 5 In a specific embodiment, the present application provides an embodiment of a method for obtaining a second mechanical coordinate, including: S501, calculating the calibration point coordinates of each calibration point on the calibration board according to the physical parameters of the calibration board; The physical parameters of the calibration plate include the overall size (such as length, width), shape (such as rectangle, circle, etc.), number of corner points and position relationship, etc.

[0087] The coordinates of the calibration points on the calibration plate coordinate system of each calibration point are calculated according to the physical parameters of the calibration plate.

[0088] S502, calculating and obtaining a two-dimensional vector according to the first mechanical coordinate; Use the following formula 1 to calculate the two-dimensional vector: Formula 1; in, and Indicates the first mechanical coordinates of two beveled corner points among the five inner frame corner points on the calibration plate on the stage; Represents the vector component in the X-axis direction in two-dimensional space; Represents the vector component in the Y-axis direction in two-dimensional space.

[0089] S503, calculating the second mechanical coordinates according to the two-dimensional vector, the coordinates of the calibration point and the first mechanical coordinates.

[0090] The second machine coordinate is calculated using the following formula 2: Formula 2; in, represents the coordinates of the calibration points, that is, the coordinates of the center of each marking point in the coordinate system of the physical calibration board, and i is the number of marking points on the calibration board; Indicates the second mechanical coordinate, that is, the mechanical coordinate when the center of the precision inspection camera's screen is aligned with the center of the mark point.

[0091] In this embodiment, the calibration point coordinates of each calibration point on the calibration plate are calculated according to the physical parameters of the calibration plate; then, using equation 1 and equation 2, the first mechanical coordinates and the calibration point coordinates are combined to finally calculate the second mechanical coordinates.

[0092] The second mechanical coordinate is calculated through the system's preset formula to ensure the accuracy of the data and provide accurate data support for subsequent calibration.

[0093] In a specific embodiment, the system calculates the affine transformation relationship by presetting the following formula 3: Formula 3; Among them, M represents the affine transformation relationship, Represents the two-dimensional vector obtained by converting the second mechanical coordinates, Represents the two-dimensional vector obtained by converting the third machine coordinate system.

[0094] See also Figure 6 The present application provides an embodiment of an automatic calibration device based on edge inspection camera inspection, comprising: The teaching unit 601 is used to teach in advance to obtain a fixed offset, where the fixed offset is the distance and direction required to move from the main inspection camera to the precision inspection camera; A first control unit 602 is used to make the center of the image of the precision inspection camera fall inside the calibration plate, and the calibration plate is provided with calibration points inside; A second control unit 603 is used to control the precision inspection camera to move along the X-axis or Y-axis direction with a specified step length to collect a feature map of the calibration plate, and identify corner points in the calibration plate according to the feature map; A first processing unit 604 is used to determine a first mechanical coordinate when the center of the image of the precision inspection camera is aligned with the corner point, the first mechanical coordinate being the coordinate of the stage; The second processing unit 605 is used to determine the second mechanical coordinates when the center of the image of the precision inspection camera is aligned with the center of the calibration point on the calibration plate, and the second mechanical coordinates are the coordinates of the stage; The conversion unit 606 is used to calculate the affine transformation relationship and complete the calibration.

[0095] Optionally, the calibration device further includes: The calibration unit 607 is used to calibrate the relationship between the precision inspection camera image coordinate system and the X, Y stage coordinate system to construct a conversion matrix; The extraction unit 608 is used to control the main inspection camera to collect images and extract the third mechanical coordinates through an image algorithm. The third mechanical coordinates are the image coordinates of the main inspection camera.

[0096] See also Figure 7 The present application also provides an automatic calibration device based on edge inspection camera inspection, comprising: Processor 701, memory 702, input and output unit 703, bus 704; The processor 701 is connected to the memory 702, the input and output unit 703 and the bus 704; The memory 702 stores a program, and the processor 701 calls the program to execute any of the above calibration methods.

[0097] The present application also relates to a computer-readable storage medium, on which a program is stored. When the program is run on a computer, the computer executes any of the above calibration methods.

[0098] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0099] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0100] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0101] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0102] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), disk or optical disk, etc. Various media that can store program codes.

Claims

1. An automatic calibration method based on edge inspection camera, characterized in that: The calibration method comprises: A fixed offset is obtained by teaching in advance, where the fixed offset is the distance and direction required to move from the main inspection camera to the precision inspection camera; According to the fixed offset, the center of the image of the precision inspection camera is made to fall inside the calibration plate through the motion control component, and the calibration point is arranged inside the calibration plate; Control the precision inspection camera to perform patrol motion through a motion control component to collect a feature map of the calibration plate, and identify the straight line edge and corner points of the inner frame of the calibration plate according to the feature map, and continue to control the precision inspection camera to continue patrol motion and corner point alignment accordingly; Determine a first mechanical coordinate when the center of the image of the precision inspection camera is aligned with the corner point, the first mechanical coordinate being the coordinate of the stage; Determine, according to the physical parameters of the calibration plate and the first mechanical coordinates, a second mechanical coordinate when the center of the image of the precision inspection camera is aligned with the center of the calibration point on the calibration plate, wherein the second mechanical coordinates are the coordinates of the stage; The calibration is completed by calculating the affine transformation relationship based on the pre-collected third mechanical coordinates and the second mechanical coordinates, and the third mechanical coordinates are the image coordinates of the main inspection camera.

2. The automatic calibration method based on edge inspection of a precision inspection camera according to claim 1, characterized in that: After the fixed offset is obtained by advance teaching, the calibration method further includes: Calibrate the relationship between the precision inspection camera image coordinate system and the X, Y stage coordinate system, and construct a transformation matrix; The calibration plate is randomly placed at the main inspection station, the main inspection camera is controlled to collect images, and the third mechanical coordinates are extracted through the image algorithm, and the third mechanical coordinates are the image coordinates of the main inspection camera.

3. The automatic calibration method based on edge inspection camera according to claim 2, characterized in that: The calibration of the relationship between the image coordinate system of the precision inspection camera and the X, Y stage coordinate system to construct a transformation matrix includes: When a corner point of the calibration plate is located in the picture of the precision inspection camera, controlling the precision inspection camera to capture a first image, and extracting first corner point coordinates of the corner point in the first image; The motion control component controls the precision inspection camera to move along the X-axis or the Y-axis separately, and the precision inspection camera collects the second image and the third image, and extracts the second corner point coordinates and the third corner point coordinates of the corner point; Calculating a first offset of the calibration plate after movement along the X-axis and the Y-axis; A transformation matrix is ​​calculated according to the first corner point coordinates, the second corner point coordinates, the third corner point coordinates and the first offset.

4. The automatic calibration method based on edge inspection camera according to claim 1, characterized in that: The corner points include 5 inner frame corner points; The precision inspection camera is controlled by a motion control component to perform patrol motion to collect a feature map of the calibration plate, and the straight line edge and corner points of the inner frame of the calibration plate are identified according to the feature map, thereby guiding the precision inspection camera to perform patrol motion and corner point alignment, including: The precision inspection camera is controlled by a motion control component to perform patrol motion to collect the feature map of the calibration plate, and the straight edge of the inner frame and the five inner frame corner points of the calibration plate are identified based on the feature map, thereby guiding the precision inspection camera to perform patrol motion and align the five inner frame corner points.

5. The automatic calibration method based on edge inspection camera according to claim 4, characterized in that: The motion control component controls the precision inspection camera to perform patrol motion to collect the characteristic image of the calibration plate, and identifies the straight edge of the inner frame and five inner frame corner points of the calibration plate according to the characteristic image, thereby guiding the precision inspection camera to perform patrol motion and align the five inner frame corner points, including: Step 1: Control the precision inspection camera to move along the X-axis or Y-axis direction with a specified step length through the motion control component; Step 2: After each movement, control the precision inspection camera to collect the feature map of the calibration plate, and extract the image features in the feature map through an image processing algorithm; Step 3: Determine whether the image features include straight line edges and inner frame corner points; If the image feature does not include straight line edges and inner frame corner points, return to step 1; If the image feature only includes a straight edge, a special step length is calculated by combining the starting point information of the straight edge and a pre-constructed transformation matrix, the precision inspection camera is controlled to move with the special step length, and the process returns to step 2 after the movement; If the image features include both straight edges and inner frame corners, the inner frame corners are identified, the center of the image of the precision inspection camera is controlled to align with the inner frame corners, and an automatic focusing operation is performed; Step 4: loop step 1 to step 3 until all five inner frame corner points in the calibration plate are identified.

6. The automatic calibration method based on edge inspection of a precision inspection camera according to claim 5, characterized in that: After step 4, the method further includes: Step 5: Determine whether all five inner frame corner points in the calibration plate are obtained; If yes, stop looping steps 1 to 3; Step 6: If the loop does not stop, recalibrate the relationship between the precision inspection camera image coordinate system and the X, Y stage coordinate system, and update the transformation matrix; Step 7: After determining that there are no corner points in the precision inspection camera image, loop steps 1 to 3 in another direction until all five inner frame corner points in the calibration plate are identified, wherein the other direction indicates a direction different from the last movement direction of the precision inspection camera.

7. The automatic calibration method based on edge inspection of a precision inspection camera according to any one of claims 1 to 6, characterized in that: The method of determining the second mechanical coordinate when the center of the image of the precision inspection camera is aligned with the center of the calibration point on the calibration plate according to the physical parameters of the calibration plate and the first mechanical coordinate comprises: Calculating the calibration point coordinates of each calibration point on the calibration plate according to the physical parameters of the calibration plate; Calculate a two-dimensional vector according to the first mechanical coordinates; The second mechanical coordinate is calculated according to the two-dimensional vector, the coordinates of the calibration point and the first mechanical coordinate.

8. The automatic calibration method based on edge inspection of a precision inspection camera according to claim 7, characterized in that: The calculating and obtaining a two-dimensional vector according to the first mechanical coordinates includes: Use the following formula 1 to calculate the two-dimensional vector: Formula 1; in, and Indicates the first mechanical coordinates of two beveled corner points among the five inner frame corner points on the calibration plate on the stage; Represents the vector component in the X-axis direction in two-dimensional space; Represents the vector component in the Y-axis direction in two-dimensional space.

9. The automatic calibration method based on edge inspection of a precision inspection camera according to claim 8, characterized in that: The step of calculating the second mechanical coordinate according to the two-dimensional vector, the coordinates of the calibration point and the first mechanical coordinate comprises: The second machine coordinate is calculated using the following formula 2: Formula 2; in, represents the coordinates of the calibration points, that is, the coordinates of the center of each marking point in the coordinate system of the physical calibration board, and i is the number of marking points on the calibration board; Indicates the second mechanical coordinate, that is, the mechanical coordinate when the center of the precision inspection camera's screen is aligned with the center of the mark point.

10. The automatic calibration method based on edge inspection camera according to claim 2, characterized in that: The step of calculating an affine transformation relationship based on the pre-collected third mechanical coordinate and the second mechanical coordinate to complete the calibration includes: Use the following formula 3 to get the affine transformation relationship: Formula 3; Among them, M represents the affine transformation relationship, Represents the two-dimensional vector obtained by converting the second mechanical coordinates, Represents the two-dimensional vector obtained by converting the third machine coordinate system.

11. An automatic calibration device based on edge inspection camera, characterized in that: The device comprises: A teaching unit, used to obtain a fixed offset by teaching in advance, wherein the fixed offset is the distance and direction required to move from the main inspection camera to the precision inspection camera; A first control unit, configured to make the center of the image of the precision inspection camera fall inside the calibration plate through a motion control component according to the fixed offset, wherein the calibration plate is provided with calibration points inside; A second control unit is used to control the precision inspection camera to perform patrol motion through a motion control component to collect a feature map of the calibration plate, and identify the straight line edges and corner points of the inner frame of the calibration plate according to the feature map, and continue to control the precision inspection camera to continue patrol motion and corner point alignment accordingly; A first processing unit, used to determine a first mechanical coordinate when the center of the image of the precision inspection camera is aligned with a corner point, wherein the first mechanical coordinate is a coordinate of the stage; A second processing unit is used to determine a second mechanical coordinate when the center of the image of the precision inspection camera is aligned with the center of the calibration point on the calibration plate according to the physical parameters of the calibration plate and the first mechanical coordinate, wherein the second mechanical coordinate is the coordinate of the stage; The conversion unit is used to calculate an affine transformation relationship according to the pre-collected third mechanical coordinates and the second mechanical coordinates to complete the calibration, wherein the third mechanical coordinates are the image coordinates of the main inspection camera.

12. An automatic calibration device based on edge inspection camera, characterized in that: The device comprises: Processor, memory, input-output unit, and bus; The processor is connected to the memory, the input and output unit, and the bus; The memory stores a program, and the processor calls the program to execute the calibration method according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program, and when the program is executed on a computer, the calibration method according to any one of claims 1 to 10 is executed.

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