Calibration method and device of automatic optical detection equipment, equipment and medium

Abstract

The embodiment of the invention discloses a calibration method and device for automatic optical detection equipment, the equipment and a medium. Under the condition that the 3D AOI equipment is provided with a plurality of side cameras, in the calibration process, a plurality of calibration plates are borne and fixed through a calibration support and sequentially enter a detection area to complete projection and image acquisition of each calibration plate. The calibration plate is in different pose states, the center camera and the plurality of side cameras are controlled to complete image acquisition in each pose state, and calibration is carried out based on respective corresponding image acquisition results, so that the calibration plate can be used in the subsequent detection process. Various conversion matrixes required when the surface morphological parameters of the measured object are generated based on optical detection, so that the low efficiency caused by manually adjusting the orientation of the calibration plate in the calibration process is avoided, and the calibration efficiency is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of industrial inspection technology, and in particular to calibration methods, devices, equipment and media for automatic optical inspection equipment. Background Art

[0002] In the field of optical inspection, the first type of 3D AOI (Automated Optical Inspection) equipment generally includes a central camera and four side projections. Each side projection and a central camera form a subsystem. The second type of 3D AOI equipment includes a central camera, a central projection and four side cameras. Each side camera and the central projection form a subsystem. The height map generated by each subsystem needs to be converted into the central camera pixel coordinate system to finally complete the inspection. Regardless of the first or second solution, to achieve accurate inspection, it is necessary to adopt a calibration method corresponding to the specific hardware solution. The entire 3D AOI equipment must first be optically calibrated based on the calibration plate to achieve accurate inspection of the shape of the inspection target.

[0003] The inventor found that when calibrating the 3D AOI equipment, compared with the calibration of the 3D AOI equipment implemented by the first solution, which only requires the calibration plate to remain stationary, the calibration of the 3D AOI equipment implemented by the second solution requires multiple manual adjustments of the orientation of the calibration plate, so that the calibration plate is in a more stringent angle state before the calibration can be completed. The process of manually adjusting the calibration plate, which requires high operating accuracy, makes the calibration process more complicated. Summary of the invention

[0004] The present invention provides a calibration method, device, equipment and medium for automatic optical inspection equipment to solve the technical problem that the calibration process of the existing 3D AOI equipment including a central camera, a central projection and four side cameras is relatively complicated.

[0005] In a first aspect, an embodiment of the present application provides a calibration method for an automatic optical inspection device, wherein the automatic optical inspection device includes a central camera and a central projection that share a lens, and a plurality of side cameras arranged around the central camera. The calibration method for the automatic optical inspection device includes:

[0006] A plurality of sinusoidal fringes are encoded based on a preset frequency and a preset number of steps, and the plurality of sinusoidal fringes are sequentially projected onto a calibration plate in each posture state through central projection, a plurality of calibration points are drawn on the surface of the calibration plate, and the calibration plate in each posture state is fixed to a calibration bracket and faces a central camera or different side cameras respectively, and the calibration bracket is used to carry the calibration plate into the detection area sequentially during the calibration process;

[0007] In each posture state, the first image of the calibration plate under the illumination of the light source is collected by the central camera and the side camera, and the second image of the calibration plate under the projection of the sinusoidal stripes is collected by the side camera each time;

[0008] According to the associated images corresponding to the side camera, the center camera and the center projection in the image set, the transformation matrices from the pixel coordinate systems corresponding to the side camera, the center camera and the center projection to the corresponding target coordinate systems are respectively confirmed, and the transformation matrices are used as the calibration results of the automatic optical detection equipment; the image set includes the projection contents of the first image, the second image and the center projection.

[0009] As mentioned above, when the 3D AOI equipment is equipped with multiple side cameras, during the calibration process, multiple calibration plates are carried and fixed by the calibration bracket, and enter the detection area in turn to complete the projection and image acquisition of each calibration plate, so that the calibration plate can be quickly and accurately placed in different postures, and in each posture, the central camera and multiple side cameras are controlled to complete image acquisition respectively, and calibration is performed based on their corresponding image acquisition results, so that various transformation matrices required for generating surface morphological parameters of the object to be measured based on optical detection in subsequent detection processes can be obtained, thereby avoiding the inefficiency of manually adjusting the orientation of the calibration plate during the calibration process and improving the calibration efficiency.

[0010] Wherein, a homography matrix between the pixel coordinate system of each side camera and the world coordinate system is determined according to the first image, and a first transformation matrix from the corresponding pixel coordinate system of each side camera to the world coordinate system is determined according to the homography matrix;

[0011] The phase of the center point coordinates of each calibration point in the first image is solved by the second image corresponding to each side camera, and the coordinates of each center point in each posture state are converted to the pixel coordinate system corresponding to the central projection according to the phase to obtain the corresponding projection point coordinates;

[0012] Determine a second transformation matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera according to the pixel point coordinates and the projection point coordinates of each calibration point in the first image acquired by the central camera in the corresponding pixel coordinate system;

[0013] According to the projection point coordinates and the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system, a third transformation matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system is determined.

[0014] In the above, by driving the calibration bracket carrying the calibration plate to move, the calibration plates at different angles enter the detection area in turn to obtain images in various posture states required for calibration, and the calibration process is quickly completed based on the images.

[0015] Wherein, determining the homography matrix between the pixel coordinate system of each side camera and the world coordinate system according to the first image, and determining the first transformation matrix from the corresponding pixel coordinate system of each side camera to the world coordinate system according to the homography matrix, comprises:

[0016] The intrinsic and extrinsic parameters of each side camera are obtained by calibrating the first image corresponding to each side camera by Zhang Dingyou;

[0017] According to the product of the intrinsic parameter and the extrinsic parameter corresponding to each side camera, the first transformation matrix from the corresponding pixel coordinate system to the world coordinate system of each side camera is obtained.

[0018] As mentioned above, by solving the intrinsic and extrinsic parameters through the homography matrix of the side camera, the calibration of the side camera can be completed quickly.

[0019] Among them, according to the pixel point coordinates and projection point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system, confirming the second transformation matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera includes:

[0020] According to the pixel point coordinates and projection point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system, a second transformation matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera is determined by the least squares method.

[0021] As mentioned above, the calibration of the center camera can be quickly confirmed by the least squares method.

[0022] The phase of the center point coordinates of each calibration point in the first image is calculated by using the second image corresponding to each side camera, including:

[0023] The wrapping phase of each side camera at each frequency is confirmed by using a second image corresponding to the sinusoidal fringes of each frequency collected by each side camera;

[0024] The wrapped phase corresponding to the target frequency is unfolded to obtain the unfolded phase of the sinusoidal fringe within one period, and the target frequency is the frequency with the largest value.

[0025] As described above, the phase included in the image corresponding to the sinusoidal stripes of each frequency can be quickly confirmed as the unfolded phase.

[0026] Among them, according to the projection point coordinates and the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system, the third transformation matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system is determined, including:

[0027] The third transformation matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system is confirmed by the telecentric lens imaging model.

[0028] As mentioned above, the central projection can be accurately calibrated through the telecentric lens imaging model.

[0029] In a second aspect, an embodiment of the present application provides a calibration device for an automatic optical detection device, wherein the automatic optical detection device includes a central camera and a central projection that share a lens, and a plurality of side cameras arranged around the central camera, and the calibration device for the automatic optical detection device includes:

[0030] A fringe encoding unit is used to encode a plurality of sinusoidal fringes based on a preset frequency and a preset number of steps, and to sequentially project the plurality of sinusoidal fringes onto a calibration plate in each posture state through central projection, wherein a plurality of calibration points are drawn on the surface of the calibration plate, and the calibration plate in each posture state is fixed to a calibration bracket and faces a central camera or different side cameras respectively, and the calibration bracket is used to carry the calibration plate to sequentially enter the detection area during the calibration process;

[0031] An image acquisition unit is used to acquire a first image of the calibration plate under the illumination of the light source through a central camera and a side camera in each posture state, and to acquire a second image of the calibration plate under the projection of sinusoidal fringes through a side camera each time;

[0032] A matrix confirmation unit is used to confirm the transformation matrix from the pixel coordinate system corresponding to the side camera, the center camera and the center projection to the corresponding target coordinate system according to the associated images corresponding to the side camera, the center camera and the center projection in the image set, and use the transformation matrix as the calibration result of the automatic optical detection equipment; the image set includes the projection content of the first image, the second image and the center projection.

[0033] Wherein, the matrix confirmation unit includes:

[0034] A first conversion confirmation module is used to confirm the homography matrix between the pixel coordinate system of each side camera and the world coordinate system according to the first image, and confirm the first conversion matrix from the corresponding pixel coordinate system of each side camera to the world coordinate system according to the homography matrix;

[0035] A coordinate confirmation module is used to solve the phase of the center point coordinates of each calibration point in the first image through the second image corresponding to each side camera, and convert each center point coordinate in each posture state into the pixel coordinate system corresponding to the central projection according to the phase to obtain the corresponding projection point coordinates;

[0036] A second conversion confirmation module is used to confirm a second conversion matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera according to the pixel point coordinates and the projection point coordinates of each calibration point in the first image acquired by the central camera in the corresponding pixel coordinate system;

[0037] The third conversion confirmation module is used to confirm the third conversion matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system according to the projection point coordinates and the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system.

[0038] Wherein, the first conversion confirmation module includes:

[0039] A parameter confirmation submodule, used to obtain the intrinsic parameters and extrinsic parameters of each side camera by calibrating the first image corresponding to each side camera through Zhang Dingyou;

[0040] The product confirmation submodule is used to obtain the first transformation matrix from the corresponding pixel coordinate system to the world coordinate system of each side camera according to the product of the intrinsic parameter and the extrinsic parameter corresponding to each side camera.

[0041] Wherein, the second conversion confirmation module includes:

[0042] The least squares processing submodule is used to confirm the second transformation matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera by the least squares method based on the pixel point coordinates and projection point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system.

[0043] Among them, the coordinate confirmation module includes:

[0044] A first phase confirmation submodule is used to confirm the wrapping phase corresponding to each frequency of each side camera through a second image corresponding to the sinusoidal stripes of each frequency collected by each side camera;

[0045] The second phase confirmation submodule is used to unfold the wrapped phase corresponding to the target frequency to obtain the unfolded phase of the sinusoidal fringe within one cycle, and the target frequency is the frequency with the largest value.

[0046] Wherein, the third conversion confirmation module includes:

[0047] The imaging model application submodule is used to confirm the third transformation matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system through the telecentric lens imaging model.

[0048] In a third aspect, an embodiment of the present application further provides an electronic device, the electronic device comprising:

[0049] one or more processors;

[0050] a memory for storing one or more computer programs;

[0051] When one or more computer programs are executed by one or more processors, the electronic device implements the calibration method of the automatic optical detection device as described in the first aspect.

[0052] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the calibration method of the automatic optical inspection device as in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A method flow chart of a calibration method for automatic optical inspection equipment provided in an embodiment of the present application.

[0054] Figure 2 A schematic diagram of the structure of a calibration device for automatic optical inspection equipment provided in an embodiment of the present application.

[0055] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only the parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0057] It should be noted that due to space limitations, this application description does not list all optional implementation methods. After reading this application description, those skilled in the art should be able to understand that as long as the technical features do not contradict each other, any combination of technical features can constitute an optional implementation method.

[0058] The following is a detailed description of the various embodiments of the present invention.

[0059] In the field of automatic optical inspection, 3D AOI equipment mainly includes a central camera and four side projections, each side projection and a central camera form a subsystem architecture (hereinafter referred to as the first architecture); and an architecture including a central camera, a central projection and four side cameras (hereinafter referred to as the second architecture). For 3D AOI equipment implemented by the first architecture, the calibration can be completed by simply keeping the calibration plate still. During the calibration of the 3D AOI equipment implemented by the second architecture, it is necessary to manually adjust the orientation of the calibration plate multiple times so that the calibration plate is in a state with stricter requirements for angles before the calibration can be completed. During the calibration process, the process of manually adjusting the calibration plate, which requires high operating accuracy, makes the calibration process more complicated.

[0060] In view of the above technical problems, the embodiment of the present application proposes a calibration method for automatic optical inspection equipment. When the 3D AOI equipment is equipped with multiple side cameras, multiple calibration plates are carried and fixed by the calibration bracket during the calibration process, and enter the inspection area in turn to complete the projection and image acquisition of each calibration plate. The calibration plate is placed in different posture states, and in each posture state, the central camera and multiple side cameras are controlled to complete image acquisition respectively, and calibration is performed based on the corresponding image acquisition results. In this way, various conversion matrices required for generating surface morphological parameters of the object to be measured based on optical detection in the subsequent inspection process can be obtained, thereby avoiding the inefficiency of manually adjusting the orientation of the calibration plate during the calibration process and improving the calibration efficiency.

[0061] Figure 1 A method flow chart of a calibration method for an automatic optical inspection device provided in an embodiment of the present application. The automatic optical inspection device in the real-time example of the present application includes a central camera and a central projection that share a lens, and a plurality of side cameras arranged around the central camera, wherein the central projection is a device for projecting onto the center of the area to be measured, and the central projection can be realized by a projector, while the central camera is a device for capturing an image of the center of the area to be measured. The central projection and the central camera use the same lens, which can be realized during the hardware assembly process. For example, a 45° semi-transparent and semi-reflective lens can be used as a lens, and the central projection and the central camera share a telecentric lens. In addition, the side camera is a camera used to capture images from the side of the central camera. The number of side cameras can be set according to actual needs. In this embodiment, the number of side cameras is 4 as an example for explanation, and the side cameras can use wide-angle lenses.

[0062] like Figure 1 As shown, the calibration method of the automatic optical detection equipment includes:

[0063] Step S110: Encode multiple sinusoidal stripes based on a preset frequency and a preset number of steps, and project the multiple sinusoidal stripes in turn to the calibration plate in each posture state through central projection. A plurality of calibration points are drawn on the surface of the calibration plate. The calibration plate in each posture state is fixed to a calibration bracket and faces the central camera or different side cameras respectively. The calibration bracket is used to carry the calibration plate into the detection area in turn during the calibration process.

[0064] In order to achieve the given calibration in the embodiment of the present application, it is necessary to encode the sinusoidal fringes. It can be understood that sinusoidal fringes are sinusoidal-shaped fringes. When encoding the sinusoidal fringes, it is necessary to encode sinusoidal fringes with multiple steps at multiple frequencies, wherein the number of steps of the sinusoidal fringes refers to the distance between two adjacent in-phase points in the sinusoidal fringe diagram. The number of steps of the sinusoidal fringes determines the accuracy and resolution of the measurement. Exemplarily, in this embodiment, the sinusoidal fringes with five-frequency four-step sinusoidal fringes are used as an example for explanation. The five-frequency four-step sinusoidal fringes are sinusoidal fringes with five frequencies and four steps at each frequency. In this embodiment, the sinusoidal fringes can be encoded by the following formula:

[0065] In(x,y)=A(x,y)+B(x,y)cos[Φ(x,y)+2kπfx / 4]

[0066] Wherein, A is the background intensity, B is the amplitude, Φ is the phase, f is the frequency, k is the number of steps (in this embodiment, 1<=k<=4, k∈Z), and (x, y) are the coordinates in the pixel coordinate system of the central projection.

[0067] In this embodiment, the sinusoidal stripes include transverse stripes that are expanded horizontally and longitudinal stripes that are expanded vertically, so stripes in two directions need to be encoded during encoding. In one embodiment, assuming that the resolution of the line beam projected by the central projection is 1920*1080, the frequencies of the five transverse stripes that are expanded horizontally are 240hz, 235hz, 192hz, 45hz and 44hz, respectively. Among them, the highest frequency used for the transverse stripes is 240hz, because 1920 / 240=8, that is, one cycle of the transverse stripes includes 8 pixels (if the frequency is higher, the contrast of the stripes will decrease); 192hz means that one cycle includes 10 pixels; 235 is an empirical value; in addition, the frequency difference between 45hz and 44hz is 1, which is also an empirical value. The frequency difference of 1 can solve a complete expansion phase, and the expansion phase solved by the low frequency can guide the high frequency expansion. The frequencies of the five longitudinal stripes are 135 Hz, 130 Hz, 108 Hz, 25 Hz and 24 Hz respectively. The value selection principle is similar to that of the transverse stripes. The combination of these frequencies can provide better measurement accuracy and stability for the subsequent measurement. It can be understood that the frequency of the five-frequency four-step sinusoidal stripes can also be set according to actual needs, and is not specifically limited in this embodiment. It is possible to encode and project sinusoidal stripes at all stages of automatic optical detection.

[0068] After encoding the five-frequency four-step sinusoidal stripes, it is necessary to project the five-frequency four-step sinusoidal stripes sequentially onto the surface of a calibration plate or an object to be measured through central projection, wherein the calibration plate is a flat plate structure with calibration points drawn strictly according to the layout requirements, and the object to be measured refers to an object to be three-dimensionally reconstructed, for example, the object to be measured may be a circuit board or a component, etc. That is, in this embodiment, it is necessary to sequentially project the sinusoidal stripes with four steps at one frequency onto the surface of the object to be measured, until the sinusoidal stripes of all steps at all frequencies are projected. By projecting the five-frequency four-step sinusoidal stripes onto the object to be measured, the true shape of the object to be measured can be reflected according to the deflection of the sinusoidal stripes on the object to be measured. The calibration plate is the object to be photographed in the calibration stage, and the object to be measured is the object to be photographed in the actual test stage after calibration. The embodiments of this application mainly describe the process of projection, image acquisition and image processing with the calibration plate as the object to be photographed in the calibration stage.

[0069] In the embodiment of the present application, considering that the posture of the calibration plate needs to be changed multiple times for calibration, the number of calibration plates is directly set to multiple, and the distribution of calibration points on each calibration plate is the same; multiple calibration plates are fixed to the calibration bracket, and each calibration plate corresponds to a different posture state; during the calibration process, the calibration bracket can be placed on the conveyor belt, and the 3D AOI equipment can be controlled to start calibration, so that the conveyor belt can be driven to drive the calibration bracket to move to the detection area, and multiple calibration plates follow the position change of the calibration bracket to enter the detection area in turn. The staff only needs to manually confirm the start of calibration to automatically complete the calibration process without manually adjusting the calibration plate, which effectively improves the calibration speed and better controls the calibration process.

[0070] Step S120: In each posture state, the central camera and the side camera are used to collect a first image of the calibration plate under the illumination of the light source, and the side camera is used to collect a second image of the calibration plate under the projection of the sinusoidal stripes each time.

[0071] The first image and the second image are both images obtained by photographing the calibration plate. The difference in content between the two lies mainly in the different projections of the central projection on the calibration plate. The first image has a light source but no sinusoidal stripes. The light source can be a white light source or a light source of other colors; the second image has sinusoidal stripes. Considering that each side camera and the overall processing ideas for different sinusoidal stripes are the same, the images captured by all side cameras on the calibration plate when projecting different sinusoidal stripes are collectively referred to as the second image. In the specific calibration process, there is no limitation on the shooting order based on the changes in the projection content of each posture state and the central projection, for example, the first image or the second image can be captured first. For the first image, each side camera needs to collect 5 images corresponding to 5 posture states; for the second image, taking five-frequency four-step as an example, five-frequency four-step has a total of 20 sinusoidal stripes, corresponding to the horizontal and vertical directions. Each side camera needs to collect 40 second images in one posture state, and a total of 200 second images need to be collected corresponding to five posture states. If there are a total of 4 side cameras, a total of 800 second images are collected, but the 800 second images are divided into 4 groups for processing based on the side cameras, and the calibration results of the 4 side cameras are obtained.

[0072] Step S130: According to the associated images corresponding to the side camera, the center camera and the center projection in the image set, respectively confirm the transformation matrix from the pixel coordinate system corresponding to the side camera, the center camera and the center projection to the corresponding target coordinate system, and use the transformation matrix as the calibration result of the automatic optical detection equipment; the image set includes the projection content of the first image, the second image and the center projection.

[0073] In 3D AOI equipment, each camera and the central projection itself can only perform planar imaging. To realize the confirmation from planar imaging to three-dimensional shape and complete the conversion from planar position to three-dimensional position, the conversion is realized by the conversion matrix obtained through calibration. Each camera and the central projection have a directly associated coordinate system, that is, the corresponding target coordinate system. The target coordinate system is mainly the world coordinate system or the pixel coordinate system of other hardware. For different cameras and central projections, the calibration is realized with their corresponding associated images. For different cameras or central projections, the associated image can refer to the pattern of the calibration plate, the sinusoidal fringe image projected by the central projection and / or the corresponding collected image in step S110 and step S120. Through the regular changes of the content of these images themselves and the imaging information of these contents in the collected images (such as the position of the origin in the calibration plate), the conversion matrix from the pixel coordinate system corresponding to the side camera, the central camera and the central projection to the corresponding target coordinate system can be confirmed through various calibration methods such as Zhang Zhengyou calibration.

[0074] Corresponding to the specific hardware type in the automatic optical inspection equipment, the calibration result in step S130 includes three conversion matrices, namely, the first conversion matrix from the corresponding pixel coordinate system of each side camera to the world coordinate system, the second conversion matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera, and the third conversion matrix from the corresponding pixel coordinate system of the central projection to the world coordinate system. The specific confirmation process of the first conversion matrix, the second conversion matrix and the third conversion matrix can be implemented by referring to the description of steps S131 to S134. Considering that the images collected by the side camera and the central camera are based on the corresponding pixel coordinate system, the pixel coordinate system used to describe the information content in the images collected by the side camera and the central camera is also called the image coordinate system.

[0075] Step S131: confirming the homography matrix between the pixel coordinate system of each side camera and the world coordinate system according to the first image, and confirming the first transformation matrix from the corresponding pixel coordinate system of each side camera to the world coordinate system according to the homography matrix.

[0076] In the specific implementation process, the purpose of calibration is to obtain multiple transformation matrices, each of which is specifically used to describe the transformation relationship between coordinates in two different coordinate systems, where the first transformation matrix is ​​used to describe the transformation relationship between the corresponding pixel coordinate system and the world coordinate system of each side camera. Under the first image of the side camera, the coordinates of the center point of the calibration point are extracted to obtain the coordinates of the center point in the pixel coordinate system of the side camera. At the same time, the plane where the calibration plate is located is used as the xy plane of the world coordinate system, and the center of the first calibration point is used as the origin (0,0,0). The world coordinates of each calibration point can be recorded separately according to the layout relationship of each calibration point when drawing the calibration point. In the specific conversion process, the first transformation matrix from the corresponding pixel coordinate system to the world coordinate system of each side camera can be obtained through the operation of the first transformation matrix and the world coordinate system. Specifically, the intrinsic parameters and extrinsic parameters of each side camera can be obtained by Zhang Dingyou calibration for the first image corresponding to each side camera; according to the product of the intrinsic parameters and extrinsic parameters corresponding to each side camera, the first transformation matrix from the corresponding pixel coordinate system to the world coordinate system of each side camera is obtained. This method of confirming the intrinsic parameters and extrinsic parameters can specifically be the Zhang Zhengyou calibration, or other camera calibration methods based on calibration objects.

[0077] Step S132: Calculate the phase of the center point coordinates of each calibration point in the first image through the second image corresponding to each side camera, and convert each center point coordinate in each posture state into the pixel coordinate system corresponding to the central projection according to the phase to obtain the corresponding projection point coordinates.

[0078] In the specific implementation process, the phase of the coordinates of the center point of each calibration point in the first image is solved through the second image corresponding to each side camera, including: confirming the wrapping phase corresponding to each frequency of each side camera through the second image corresponding to the sinusoidal stripes of each frequency collected by each side camera; unfolding the wrapping phase corresponding to the target frequency to obtain the unfolded phase of the sinusoidal stripes in one cycle, and the target frequency is the frequency with the largest value. That is, after the side camera has captured all the target images corresponding to the five-frequency four-step sinusoidal stripes, the unfolded phase of the five-frequency four-step sinusoidal stripes in one cycle can be determined according to the target image captured by the side camera, wherein the unfolded phase refers to restoring the original phase value from the wrapped phase. In one embodiment, the wrapped phase of each frequency can be determined according to the target image corresponding to each step of each frequency captured by each side camera, and then the wrapped phase of the frequency with the largest value is unfolded to obtain the unfolded phase of the five-frequency four-step sinusoidal stripes in one cycle.

[0079] The wrapped phase refers to the phase information obtained by the phase shifting technology. The phase is constrained to be between -π, π. This constraint is the origin of the word "wrapped". Specifically, for the target images corresponding to the four steps of each frequency captured by each side camera, the wrapped phase of each frequency can be determined by the following formula:

[0080]

[0081] Where (x s ,y s ) represents the coordinates of the pixel points in the target image, I i (x s ,y s ) represents the coordinates (x) in the target image s ,y s ) is the gray value corresponding to the i-th step size, Then the coordinate (x s ,y s ), after solving for the wrapped phase, since the wrapped phase is between [-π,π], it is necessary to further normalize the wrapped phase to between [0, 1]. In an optional unfolding method, the multi-frequency heterodyne principle is used to unfold the low-frequency wrapped phase to assist the high-frequency wrapped phase.

[0082] Afterwards, by combining the target image captured by each side camera with the wrapped phase corresponding to each frequency of the sinusoidal fringes, the wrapped phase corresponding to each frequency in the sinusoidal fringes can be determined.

[0083] After determining the wrapped phase of each frequency of the sinusoidal stripes, it is necessary to further expand the wrapped phase of the target frequency, where the target frequency is the frequency with the largest value among all frequencies. The reason for selecting the frequency with the largest value is that the frequency with the largest value has the highest accuracy. The five frequencies in the five-frequency four-step sinusoidal stripes are decreasing, so the first frequency can be taken as the target frequency. When expanding the wrapped phase of the first frequency, multi-frequency heterodyne can be used to expand the wrapped phase. After expansion, an unambiguous one-cycle phase diagram is obtained. The specific formula is as follows:

[0084]

[0085] Among them, θ1 is the unwrapped phase of the first frequency, floor is the rounding function, is the difference between the wrapping phase of the first frequency and the wrapping phase of the second frequency. If the difference is greater than 0, it is retained, and if it is less than 0, it is increased by 1. λ1 is the value of the first frequency, λ 12 is the difference between the first frequency and the second frequency. When the difference is less than 0, the absolute value is taken. is the wrapping phase of the first frequency.

[0086] The embodiment of the present invention calculates the wrapped phase of each frequency of the sinusoidal stripes, thereby limiting the phase value within a specific range, eliminating the phase discontinuity, and making the phase value easier to process and analyze, so that the unfolded phase of the sinusoidal stripes within one period can be accurately and effectively determined subsequently.

[0087] Step S133: according to the pixel point coordinates and projection point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system, determine the second transformation matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera.

[0088] Among them, the second transformation matrix is ​​one of the transformation matrices that need to be confirmed. In the embodiment of the present application, the second transformation matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera is specifically confirmed by the least squares method.

[0089] Step S134: confirming a third transformation matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system according to the projection point coordinates and the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system.

[0090] In addition, the embodiment of the present application confirms the third conversion matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system through the telecentric lens imaging model, that is, confirms the last conversion matrix required. It should be noted that what is described in the embodiment of the present application is to confirm the first conversion matrix, the second conversion matrix and the third conversion matrix in sequence. This is only a textual order, and does not limit the order of the specific processing process. It can be determined in any order, or it can be processed in parallel if the processing power of the electronic device is sufficient. For the first conversion matrix, the second conversion matrix and the third conversion matrix that are finally confirmed, they can be recorded separately, and the image coordinates can be converted in sequence when the actual detection is carried out; or the first conversion matrix, the second conversion matrix and the third conversion matrix can be multiplied in the correct conversion order, and a final conversion matrix can be obtained by fusion. When the actual detection is carried out, the image coordinates can be directly converted according to the final conversion matrix obtained by fusion.

[0091] When implementing step S133 and step S134, based on the necessary previous processing steps, the center point coordinates Pc in the side camera pixel coordinate system, the center point coordinates Pcc in the center camera pixel coordinate system, the center point coordinates Pp in the projection pixel coordinate system, and the center point coordinates Pw in the world coordinate system are obtained in each posture state. The homography matrix H conversion relationship between the above point sets is calculated, including the conversion relationship Hcp between the center camera and the center projection, and the conversion relationship Hpw between the center projection and the world coordinate system. At the same time, the pixelsize of the telecentric lens is calculated through the imaging model of the telecentric lens, and the above coordinates are substituted into the telecentric lens imaging model as follows:

[0092]

[0093] In the telecentric lens imaging model, m represents the telecentric lens magnification, s is the lens distortion factor, (u0, v0) is the image coordinate origin, r and t are the rotation matrix and translation matrix in the external parameters respectively. In the experiment, the initial value of m, i.e. the telecentric lens magnification, can be estimated as 1 (telecentric lens parameter information), the initial value of s is set to 0, and the initial value of the camera origin is set to the pixel center point. The external parameters are obtained by combining the known initialization internal parameters and the normalized matrix. Here, we assume that h ij It represents the number in the i-th row and j-th column of the normalized matrix H. According to the above formula, the normalized matrix formula can be obtained. Compared with the normalized matrix of the pinhole model, this matrix does not have a normalized matrix on the Z axis:

[0094]

[0095] The DLT (Direct Linear Transformation) method can be used to directly solve this normalized function and obtain H. Then, based on R being a unit orthogonal matrix, we can obtain:

[0096]

[0097] Combining the above formulas, we can get (assuming m / du=m / dv=a):

[0098]

[0099] Then based on the rotation matrix constraint r ij ^2=h ij^2 / a^2<=1, we can get the solution of a, where a represents the pixel size of the central projection, which can be obtained from the projection DMD pixel size and the magnification of the telecentric lens (this data can be provided by the manufacturer when leaving the factory). Therefore, we can compare the factory pixel size with the pixel size obtained by calibration to determine whether the calibration result conforms to the actual physical imaging model, and thus obtain the intrinsic parameter matrix of the central projection. So far, we have obtained the first conversion matrix from the pixel coordinate system of the side camera to the world coordinate system, the second conversion matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera, and the third conversion matrix from the pixel coordinate system corresponding to the central projection to the world coordinate system (the third conversion matrix contains the intrinsic parameter matrix of the central projection), and so far, all calibration processes are completed.

[0100] Based on the calibration results mentioned above, the object to be tested, such as a circuit board or component, can be placed in the test area, and the sinusoidal stripes obtained by the central projection coding and the image acquisition by the front camera and the side camera can be used to complete the automatic optical inspection. Based on the existing calibration, image acquisition and processing and judgment are the basic processing flow in 3D AOI, which will not be described in detail here.

[0101] Figure 2 A schematic diagram of a calibration device for an automatic optical inspection device provided in an embodiment of the present application. The automatic optical inspection device includes a central camera and a central projection that share a lens, and a plurality of side cameras arranged around the central camera, such as Figure 2 As shown, the calibration device of the automatic optical detection equipment includes a stripe encoding unit 210, an image acquisition unit 220 and a matrix confirmation unit 230.

[0102] Wherein, the fringe encoding unit 210 is used to encode a plurality of sinusoidal fringes based on a preset frequency and a preset number of steps, and to project the plurality of sinusoidal fringes sequentially to a calibration plate in each posture state through central projection, wherein a plurality of calibration points are drawn on the surface of the calibration plate, and the calibration plate in each posture state faces the central camera or different side cameras respectively;

[0103] An image acquisition unit 220 is used to acquire, in each posture state, a first image of the calibration plate under the illumination of the light source through a central camera and a side camera, and to acquire a second image of the calibration plate under the projection of sinusoidal fringes through a side camera each time;

[0104] The matrix confirmation unit 230 is used to confirm the transformation matrix from the pixel coordinate system corresponding to the side camera, the center camera and the center projection to the corresponding target coordinate system according to the associated images corresponding to the side camera, the center camera and the center projection in the image set, and use the transformation matrix as the calibration result of the automatic optical detection equipment; the image set includes the projection content of the first image, the second image and the center projection.

[0105] Based on the above embodiment, the matrix confirmation unit 230 includes:

[0106] A first conversion confirmation module is used to confirm the homography matrix between the pixel coordinate system of each side camera and the world coordinate system according to the first image, and confirm the first conversion matrix from the corresponding pixel coordinate system of each side camera to the world coordinate system according to the homography matrix;

[0107] A coordinate confirmation module is used to solve the phase of the center point coordinates of each calibration point in the first image through the second image corresponding to each side camera, and convert each center point coordinate in each posture state into the pixel coordinate system corresponding to the central projection according to the phase to obtain the corresponding projection point coordinates;

[0108] A second conversion confirmation module is used to confirm a second conversion matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera according to the pixel point coordinates and the projection point coordinates of each calibration point in the first image acquired by the central camera in the corresponding pixel coordinate system;

[0109] The third conversion confirmation module is used to confirm the third conversion matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system according to the projection point coordinates and the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system.

[0110] Based on the above embodiment, the first conversion confirmation module includes:

[0111] A parameter confirmation submodule, used to obtain the intrinsic parameters and extrinsic parameters of each side camera by calibrating the first image corresponding to each side camera through Zhang Dingyou;

[0112] The product confirmation submodule is used to obtain the first transformation matrix from the corresponding pixel coordinate system to the world coordinate system of each side camera according to the product of the intrinsic parameter and the extrinsic parameter corresponding to each side camera.

[0113] Based on the above embodiment, the second conversion confirmation module includes:

[0114] The least squares processing submodule is used to confirm the second transformation matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera by the least squares method based on the pixel point coordinates and projection point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system.

[0115] Based on the above embodiment, the coordinate confirmation module includes:

[0116] A first phase confirmation submodule is used to confirm the wrapping phase corresponding to each frequency of each side camera through a second image corresponding to the sinusoidal stripes of each frequency collected by each side camera;

[0117] The second phase confirmation submodule is used to unfold the wrapped phase corresponding to the target frequency to obtain the unfolded phase of the sinusoidal fringe within one cycle, and the target frequency is the frequency with the largest value.

[0118] Based on the above embodiment, the third conversion confirmation module includes:

[0119] The imaging model application submodule is used to confirm the third transformation matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system through the telecentric lens imaging model.

[0120] The calibration device of the automatic optical inspection equipment provided in the embodiment of the present application is included in an electronic device and can be used to execute the calibration method of the corresponding automatic optical inspection equipment provided in the above embodiment, and has corresponding functions and beneficial effects.

[0121] It is worth noting that in the embodiment of the calibration device of the above-mentioned automatic optical detection equipment, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0122] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown, the electronic device includes a processor 310 and a memory 320, and may also include an input device 330, an output device 340 and a communication device 350; the number of the processor 310 in the electronic device may be one or more, Figure 3 A processor 310 is taken as an example; the processor 310, the memory 320, the input device 330, the output device 340 and the communication device 350 in the electronic device can be connected via a bus or other means. Figure 3 The example of connecting through bus is taken in the following.

[0123] The memory 320, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the calibration method of the automatic optical detection device in the embodiment of the present application. The processor 310 executes various functional applications and data processing of the electronic device by running the software programs, instructions and modules stored in the memory 320, that is, implements the calibration method of the automatic optical detection device described above.

[0124] The memory 320 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 320 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 320 may further include a memory remotely arranged relative to the processor 310, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0125] The input device 330 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the electronic device. The output device 340 may include a display device such as a display screen.

[0126] The electronic device mentioned above includes a calibration device for an automatic optical detection device, which can be used to execute a calibration method for any automatic optical detection device and has corresponding functions and beneficial effects.

[0127] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it is used to perform relevant operations in the calibration method of the automatic optical detection equipment provided in any embodiment of the present application, and has corresponding functions and beneficial effects.

[0128] Those skilled in the art should understand that the embodiments of the present application may be provided as methods, systems, or computer program products.

[0129] Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0130] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory. The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0131] Computer readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0132] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0133] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A calibration method for an automatic optical inspection device, characterized in that: The automatic optical detection device includes a central camera and a central projection that share a lens, and a plurality of side cameras arranged around the central camera. The calibration method of the automatic optical detection device includes: Encoding a plurality of sinusoidal fringes based on a preset frequency and a preset number of steps, projecting the plurality of sinusoidal fringes sequentially onto a calibration plate in each posture state through the central projection, wherein a plurality of calibration points are drawn on the surface of the calibration plate, and the calibration plate in each posture state is fixed to a calibration bracket and faces the central camera or different side cameras respectively, and the calibration bracket is used to carry the calibration plate to sequentially enter the detection area during the calibration process; In each posture state, the central camera and the side camera are used to collect a first image of the calibration plate under the illumination of a light source, and the side camera is used to collect a second image of the calibration plate under the projection of sinusoidal fringes each time; According to the associated images corresponding to the side camera, center camera and center projection in the image set, the transformation matrices from the pixel coordinate systems corresponding to the side camera, center camera and center projection to the corresponding target coordinate systems are respectively confirmed, and the transformation matrices are used as the calibration results of the automatic optical detection equipment; the image set includes the projection contents of the first image, the second image and the center projection.

2. The calibration method of automatic optical inspection equipment according to claim 1, characterized in that: The step of respectively determining the transformation matrices from the pixel coordinate systems corresponding to the side cameras, the center camera, and the center projection to the corresponding target coordinate systems according to the associated images corresponding to the side cameras, the center camera, and the center projection in the image set includes: Determine a homography matrix between a pixel coordinate system of each of the side cameras and a world coordinate system according to the first image, and determine a first transformation matrix from a corresponding pixel coordinate system of each of the side cameras to a world coordinate system according to the homography matrix; By using the second image corresponding to each side camera, the phase of the center point coordinates of each calibration point in the first image is solved, and according to the phase, each center point coordinate in each posture state is converted into the pixel coordinate system corresponding to the central projection to obtain the corresponding projection point coordinates; Determine a second transformation matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera according to the pixel point coordinates of each calibration point in the first image acquired by the central camera in the corresponding pixel coordinate system and the projection point coordinates; According to the projection point coordinates and the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system, a third transformation matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system is determined.

3. The calibration method of automatic optical inspection equipment according to claim 2, characterized in that: Determining a homography matrix between a pixel coordinate system of each of the side cameras and a world coordinate system according to the first image, and determining a first transformation matrix from a corresponding pixel coordinate system of each of the side cameras to a world coordinate system according to the homography matrix, comprising: Obtaining the intrinsic parameters and extrinsic parameters of each side camera by calibrating the first image corresponding to each side camera through Zhang Dingyou; According to the product of the intrinsic parameter and the extrinsic parameter corresponding to each of the side cameras, a first transformation matrix from the corresponding pixel coordinate system to the world coordinate system of each of the side cameras is obtained.

4. The calibration method of automatic optical inspection equipment according to claim 2, characterized in that: The determining, according to the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system and the projection point coordinates, a second transformation matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera comprises: According to the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system and the projection point coordinates, a second transformation matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera is confirmed by the least squares method.

5. The calibration method of automatic optical inspection equipment according to claim 2, characterized in that: The step of calculating the phase of the center point coordinates of each calibration point in the first image corresponding to the second image captured by each side camera includes: Confirming the wrapping phase of each side camera at each frequency through a second image corresponding to the sinusoidal fringes of each frequency collected by each side camera; The wrapped phase corresponding to the target frequency is unfolded to obtain the unfolded phase of the sinusoidal fringes within one period, and the target frequency is the frequency with the largest value.

6. The calibration method of automatic optical inspection equipment according to claim 2, characterized in that: The step of determining a third transformation matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system according to the projection point coordinates and the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system comprises: The third transformation matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system is confirmed by the telecentric lens imaging model.

7. A calibration device for an automatic optical inspection device, characterized in that: The automatic optical detection equipment includes a central camera and a central projection that share a lens, and a plurality of side cameras arranged around the central camera. The calibration device of the automatic optical detection equipment includes: A stripe encoding unit, used for encoding a plurality of sinusoidal stripes based on a preset frequency and a preset number of steps, and projecting the plurality of sinusoidal stripes sequentially onto a calibration plate in each posture state through the central projection, wherein a plurality of calibration points are drawn on the surface of the calibration plate, and the calibration plate in each posture state is fixed to a calibration bracket and faces the central camera or different side cameras respectively, and the calibration bracket is used for carrying the calibration plate to sequentially enter the detection area during the calibration process; An image acquisition unit, used for acquiring, in each posture state, a first image of the calibration plate under the illumination of a light source through the central camera and the side camera, and acquiring a second image of the calibration plate under the projection of sinusoidal fringes each time through the side camera; A matrix confirmation unit is used to confirm the transformation matrix from the pixel coordinate system corresponding to the side camera, the center camera and the center projection to the corresponding target coordinate system according to the associated images corresponding to the side camera, the center camera and the center projection in the image set, and use the transformation matrix as the calibration result of the automatic optical detection equipment; the image set includes the projection content of the first image, the second image and the center projection.

8. The calibration device for automatic optical inspection equipment according to claim 7, characterized in that: The matrix confirmation unit comprises: A first conversion confirmation module is used to confirm a homography matrix between a pixel coordinate system of each of the side cameras and a world coordinate system according to the first image, and to confirm a first conversion matrix from a corresponding pixel coordinate system of each of the side cameras to a world coordinate system according to the homography matrix; A coordinate confirmation module, used to solve the phase of the center point coordinates of each calibration point in the first image through the second image corresponding to each side camera, and convert each center point coordinate in each posture state into a pixel coordinate system corresponding to the central projection according to the phase to obtain the corresponding projection point coordinates; A second conversion confirmation module is used to confirm a second conversion matrix from the pixel coordinate system corresponding to the central projection to the pixel coordinate system corresponding to the central camera according to the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system and the projection point coordinates; The third conversion confirmation module is used to confirm the third conversion matrix of the central projection from the corresponding pixel coordinate system to the world coordinate system according to the projection point coordinates and the pixel point coordinates of each calibration point in the first image captured by the central camera in the corresponding pixel coordinate system.

9. An electronic device, characterized in that include: one or more processors; a memory for storing one or more computer programs; When the one or more computer programs are executed by the one or more processors, the electronic device implements the calibration method for the automatic optical detection device as described in any one of claims 1-6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the calibration method of the automatic optical detection device as described in any one of claims 1 to 6 is implemented.

Images