A correction method for pattern transfer position deviation based on camera internal and external parameters

Abstract

The present invention provides a method for correcting the position deviation of pattern transfer based on camera internal and external parameters, and relates to the field of image processing technology. The method includes the following steps: calibrating the lens, obtaining the internal and external parameters of the camera, and establishing a world coordinate system corresponding to a pixel coordinate system at each steel plate position; confirming the reference, adjusting the X-axis and Y-axis directions of the steel plate to obtain the correct pattern coordinates; delineating the pattern area, performing image enhancement on the area, finding the Mark point area, screening the Mark points by morphological features, calculating the center coordinates of the pattern, and comparing with the reference coordinates to obtain the X-axis and Y-axis deviations; moving the equipment rubber head, adjusting the direction of the camera in the pattern and carrier coordinate system, and realizing the transfer printing action of the correct position of the pattern. By integrating the calibration of camera internal and external parameters, calibration of three-dimensional point cloud data, establishment of pattern coordinate system and position correction, the goal of high consistency and precision of multiple calibration matrix data can be achieved, and the complex process of calibration of three-dimensional cameras and manipulators can be simplified.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to a method for correcting pattern transfer position deviation based on camera internal and external parameters. Background Art

[0002] In modern industrial manufacturing, steel plate pattern transfer technology is a widely used surface treatment process to improve the aesthetics and functionality of products. This technology has important applications in the fields of automobiles, home appliances, and building materials. However, ensuring that the pattern is accurately transferred to the specified position of the steel plate is a critical and challenging task. This process is affected by many factors, including mechanical errors, camera installation errors, ambient light changes, and uneven surface of the steel plate.

[0003] During the pattern transfer process, the positioning accuracy of the mechanical equipment directly affects the transfer position of the pattern. The repeatability of the robot arm, the accuracy of the transmission system, and the positioning accuracy of the steel plate will all lead to deviations in the pattern transfer position. Mechanical errors include but are not limited to the positioning error of the robot arm, the error of the transmission system, and the positioning error of the steel plate. The positioning accuracy of the robot arm at different positions may vary, especially during long-term work or complex operations; the gears, belts, or chains of the transmission system may be inaccurately positioned due to wear, looseness, or manufacturing errors; the position of the steel plate on the conveyor belt or workbench may be offset due to vibration, sliding, or positioning device errors.

[0004] In the process of pattern transfer, the camera is used as an image acquisition device, and its installation position and angle have a direct impact on the image quality and accuracy. Camera installation errors include camera position error and camera angle error. The fixed position error of the camera relative to the robot arm or steel plate will cause the target position in the image to shift. The rotation angle error of the camera (such as pitch angle, yaw angle, roll angle) will affect the perspective effect and geometric distortion of the image.

[0005] During the pattern transfer process, changes in lighting conditions will affect the quality and stability of the image captured by the camera. Ambient lighting changes include changes in light intensity and light direction. Among them, changes in light intensity in different time periods or environments will lead to inconsistent image brightness, affecting the accuracy of image processing; changes in the direction of the light source will lead to changes in shadows and reflections, affecting image feature extraction and matching.

[0006] During the pattern transfer process, the surface unevenness of the steel plate (such as surface roughness, reflectivity, color difference, etc.) will also affect the accuracy of the pattern transfer position. Surface unevenness leads to reflection interference and color difference. Among them, the reflection on the surface of the steel plate may cause bright or dark spots in the camera imaging, affecting the image quality. The color of steel plates from different batches or different parts may be different, affecting the stability and accuracy of pattern recognition.

[0007] Traditional methods of pattern transfer position correction usually rely on manual adjustment and simple mechanical positioning control, which have the limitations of low manual adjustment efficiency, low precision and low automation. Manual adjustment requires operators to have high experience and skills, and the adjustment process is time-consuming and easily affected by human factors; traditional mechanical positioning control is difficult to achieve high-precision requirements, especially in repeated operations, where the error accumulation is large; traditional methods are difficult to achieve a high level of automation and intelligence, affecting production efficiency and consistency.

[0008] In order to overcome the above technical difficulties, it is necessary to provide a correction method based on the internal and external parameters of the camera, so as to achieve high-precision pattern transfer position correction by accurately calibrating the internal and external parameters of the camera. Summary of the invention

[0009] In view of this, the purpose of the present invention is to propose a correction method for pattern transfer position deviation based on camera internal and external parameters, aiming to improve the accuracy and stability of camera calibration, and then improve the accuracy and reliability of pattern transfer. By integrating camera internal and external parameter calibration, three-dimensional point cloud data calibration, pattern coordinate system establishment and position correction, the goal of high consistency and accuracy of multiple calibration matrix data can be achieved, simplifying the complex process of three-dimensional camera and manipulator calibration.

[0010] Based on the above purpose, in a first aspect, the present invention provides a method for correcting pattern transfer position deviation based on camera internal and external parameters, comprising the following steps:

[0011] Step 1: Calibrate the lens, obtain the internal and external parameters of the camera, and establish a world coordinate system corresponding to the pixel coordinate system at each steel plate position;

[0012] Step 2: Confirm the benchmark and adjust the X-axis and Y-axis directions of the steel plate to obtain the correct pattern coordinates;

[0013] Step 3: Define the pattern area, perform image enhancement on the area, find the Mark point area, select the Mark point by morphological features, calculate the center coordinates of the pattern, and compare them with the reference coordinates to obtain the X-axis and Y-axis deviations;

[0014] Step 4: Move the device's rubber head and adjust the direction of the camera within the pattern and carrier coordinate system to achieve pad printing at the correct position of the pattern.

[0015] Through the above method, high-precision and high-consistency pattern transfer position correction can be achieved, significantly improving production efficiency and product quality.

[0016] As a further solution of the present invention, correction of the pattern transfer position deviation is obtained, comprising the following steps:

[0017] The benchmark determination process includes alignment in the pattern coordinate system and alignment in the carrier coordinate system;

[0018] Production alignment printing process, including compensation alignment of pattern coordinate system and carrier coordinate system;

[0019] Move the pad of the device to achieve pad printing at the correct position of the pattern.

[0020] As a further solution of the present invention, the benchmark determination process also includes camera calibration and benchmark determination, wherein:

[0021] Alignment within the pattern coordinate system, with the equipment rubber head aligned with the pattern center;

[0022] The alignment circle in the carrier coordinate system, the equipment rubber head is aligned with the center of the carrier;

[0023] Move the rubber head of the device to achieve the transfer action of the pattern to the correct position.

[0024] As a further solution of the present invention, the production alignment printing process also includes:

[0025] Alignment within the pattern coordinate system, calculation and compensation of deviations in the horizontal and vertical directions of the steel plate;

[0026] The alignment circle in the carrier coordinate system calculates and compensates for the deviations in the horizontal and vertical axis directions;

[0027] Move the rubber head of the device to achieve the transfer action of the pattern to the correct position.

[0028] Through the above steps, the present invention can achieve high-precision correction of the pattern transfer position, greatly improve production efficiency and product quality, and has significant application value and promotion prospects.

[0029] As a further solution of the present invention, the correction method of the pattern transfer position deviation based on the camera internal and external parameters also includes a three-dimensional machine vision camera calibration, and the three-dimensional machine vision camera calibration includes the following steps:

[0030] Prepare a robot, a camera mounted on a manipulator, a depth sensor, a calibration block and a calibration ball with a fixed spatial position;

[0031] Keep the calibration plate still, and take pictures of the calibration plate from three different positions to obtain images, which are named initial position, position 1, and position 2 respectively;

[0032] Using the end position posture provided by the robot controller, the three posture matrices H0, H1, and H2 of the robot are obtained through transformation, and the transformation matrices A1 and A2 corresponding to the two movements of the tool are calculated;

[0033] Use camera calibration to obtain the external parameter matrices M0, M1, and M2 corresponding to the initial position, position 1, and position 2, and calculate the transformation matrices B1 and B2 corresponding to the two camera movements;

[0034] Calibrate 3D point cloud data; use Zhang's correction method to estimate the camera's intrinsic parameter matrix; calculate the camera's extrinsic parameters for each set of matched feature points; use nonlinear optimization methods to fine-tune the intrinsic and extrinsic parameters;

[0035] The accuracy of the calibration results is evaluated by calculating indicators such as reprojection error and image quality after distortion correction; the intrinsic and extrinsic parameters are applied to subsequent image processing and computer vision tasks.

[0036] As a further solution of the present invention, the transformation matrix A1 is from the initial position to position 1; the transformation matrix A2 is from the initial position to position 2; the calculation formulas of the transformation matrices A1 and A2 are:

[0037]

[0038]

[0039] The transformation matrix B1 is from the initial position to position 1; the transformation matrix B2 is from the initial position to position 2; the calculation formulas of the transformation matrices B1 and B2 are:

[0040]

[0041] .

[0042] As a further solution of the present invention, when calibrating three-dimensional point cloud data, it includes converting the rotation matrix into a rotation vector; normalizing the rotation vector, calculating the modified Rodriguez vector, calculating the initial rotation vector, calculating the rotation vector, and calculating the rotation matrix and the translation matrix.

[0043] As a further solution of the present invention, when the rotation matrix is ​​converted into a rotation vector, the calculation formula is:

[0044]

[0045] The rotation vector is normalized and the calculation formula is:

[0046]

[0047] Calculate the modified Rodriguez vector using the formula:

[0048]

[0049] Calculate the initial rotation vector using the following formula:

[0050]

[0051] Calculate the rotation vector using the following formula:

[0052]

[0053] Calculate the rotation matrix, the calculation formula is:

[0054]

[0055] Calculate the translation matrix, the calculation formula is:

[0056]

[0057] In the formula, The rotation matrix is ​​a 3x3 matrix in three-dimensional space, which is used to describe the rotation of an object around a certain point. It can be expressed as a rotation around the x-axis, y-axis, or z-axis, or obtained from the rotation vector through the Rodriguez formula.

[0058] is the rotation vector, which is a three-dimensional vector representing the direction of the rotation axis and the magnitude of the rotation. The magnitude of the rotation vector represents the angle of rotation, and the direction represents the rotation axis.

[0059] is the initial rotation vector ;

[0060] is the initial rotation vector ;

[0061] and is the rotation matrix, which is used to calculate the rotation matrix of the rotation vector, representing different rotation operations or rotations in different coordinate systems; Represents the rotation matrix a, describing the rotation state of object a, Represents the rotation matrix b, describing the rotation state of object b;

[0062] is the translation vector, that is, the translation component in the translation matrix, which represents the displacement of the object in the x-axis direction;

[0063] Represents the identity matrix, used for multiplication operations;

[0064] The skew function is a function that converts a vector into a skew-symmetric matrix and is used to calculate the rotation matrix; the sin and cos functions are trigonometric functions that are used to calculate the components in rotation and translation.

[0065] In another aspect of the present invention, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, any one of the above-mentioned methods for correcting the pattern transfer position deviation based on the internal and external parameters of the camera according to the present invention is executed.

[0066] In another aspect of the present invention, a computer-readable storage medium is provided, storing computer program instructions, which, when executed, implement any of the above-mentioned methods for correcting pattern transfer position deviation based on camera internal and external parameters according to the present invention.

[0067] Compared with the prior art, the method for correcting the pattern transfer position deviation based on the camera internal and external parameters proposed in the present invention has the following beneficial effects:

[0068] 1. Improved transfer accuracy. By calibrating the internal and external parameters of the camera, the actual deviation of the pattern can be accurately calculated. This ensures that the transfer equipment can be adjusted according to the precise deviation information, thereby achieving high-precision pattern transfer. By establishing the correspondence between the pixel coordinate system and the world coordinate system, it is ensured that each transfer can accurately align with the center position of the pattern, reducing position errors.

[0069] 2. Reduced defective rate. By dynamically adjusting the X-axis and Y-axis directions of the steel plate, the position of each transfer is aligned with the preset reference position, which helps to reduce the defective rate caused by position deviation during the transfer process. Accurate calibration and deviation correction ensure the consistency of each transfer, thereby reducing quality problems caused by position deviation.

[0070] 3. Improved production efficiency. Through the automated deviation calculation and correction process, the need for manual intervention is reduced, and the automation level and production efficiency of the production line are improved. The precise calibration of the camera's internal and external parameters reduces the debugging time after each equipment startup or maintenance, allowing the production line to resume normal production faster.

[0071] 4. Enhanced system stability. 3D machine vision is used to perform high-precision camera internal and external parameter calibration to ensure the stability and accuracy of the system after long-term operation. Through real-time deviation detection and correction, various position changes and errors that may occur during the production process can be responded to in a timely manner, thus enhancing the stability of the system.

[0072] 5. Improved product quality. Through technologies such as image enhancement and morphological feature screening, the Mark points can be identified and located more accurately to ensure the position accuracy of pattern transfer. This directly improves the appearance quality and market competitiveness of the product. Accurate deviation calculation and correction methods ensure the consistency and repeatability of each batch of products, improving product quality and customer satisfaction.

[0073] In summary, the pattern transfer position deviation correction method based on camera internal and external parameters of the present invention reduces the defective rate, reduces the waste cost caused by position deviation, improves the overall production efficiency, and reduces the waste of materials through efficient and accurate transfer, improves the utilization efficiency of resources, and reduces production costs. It not only improves the accuracy and consistency of transfer in technology, but also brings significant improvements in production management and operating costs.

[0074] These and other aspects of the present application will be more concise and understandable in the following description of the embodiments. It should be understood that the above general description and the following detailed description are only exemplary and explanatory and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other embodiments can be obtained based on these drawings without paying creative work.

[0076] In the figure:

[0077] Figure 1 The present invention is a flowchart of a method for correcting pattern transfer position deviation based on camera internal and external parameters according to an embodiment of the present invention.

[0078] Figure 2 It is a schematic diagram of the center coordinates of the pattern for correcting the position of the steel plate pattern in the method for correcting the pattern transfer position deviation based on the internal and external parameters of the camera according to an embodiment of the present invention.

[0079] Figure 3 The present invention is a flowchart of a camera calibration and a reference determination process in a method for correcting a pattern transfer position deviation based on camera internal and external parameters according to an embodiment of the present invention.

[0080] Figure 4 It is a flow chart of the production alignment printing process in the method for correcting the pattern transfer position deviation based on the camera internal and external parameters according to an embodiment of the present invention.

[0081] Figure 5 The present invention is a flowchart of three-dimensional machine vision camera calibration in a method for correcting pattern transfer position deviation based on camera internal and external parameters in an embodiment of the present invention. DETAILED DESCRIPTION

[0082] Below, the present application is further described in conjunction with the accompanying drawings and specific implementation methods. It should be noted that, under the premise of no conflict, the various embodiments or technical features described below can be arbitrarily combined to form a new embodiment.

[0083] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the embodiments of the present invention are further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0084] It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are intended to distinguish two non-identical entities or non-identical parameters with the same name. It can be seen that "first" and "second" are only for the convenience of expression and should not be understood as limitations on the embodiments of the present invention. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, other steps or units inherent to a process, method, system, product or device that includes a series of steps or units.

[0085] 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 embodiments of the present application. Obviously, the described embodiments are 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.

[0086] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0087] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0088] The present invention relates to a method for correcting position deviation of camera calibration and pattern transfer based on three-dimensional machine vision, aiming to improve the accuracy and stability of camera calibration, and further improve the accuracy and reliability of pattern transfer. By integrating camera internal and external parameter calibration, three-dimensional point cloud data calibration, pattern coordinate system establishment and position correction, the goal of high consistency and precision of multiple calibration matrix data can be achieved, simplifying the complex process of three-dimensional camera and manipulator calibration.

[0089] See also Figures 1 to 4 As shown, a method for correcting pattern transfer position deviation based on camera internal and external parameters provided by an embodiment of the present invention includes the following steps:

[0090] Step S10, calibrate the lens, obtain the internal and external parameters of the camera, and establish a world coordinate system corresponding to the pixel coordinate system at each steel plate position;

[0091] Step S20, confirm the reference, and adjust the X-axis and Y-axis directions of the steel plate to obtain the correct pattern coordinates;

[0092] Step S30, delineate the pattern area, perform image enhancement on the area, find the Mark point area, select the Mark point by morphological features, calculate the center coordinates of the pattern, and compare with the reference coordinates to obtain the X-axis and Y-axis deviations;

[0093] Step S40, moving the device rubber head, adjusting the direction of the camera in the pattern and carrier coordinate system, and achieving pad printing at the correct position of the pattern.

[0094] Through the above steps, high-precision and high-consistency pattern transfer position correction can be achieved, significantly improving production efficiency and product quality.

[0095] Among them, see Figure 3 and Figure 4 As shown, the correction of the pattern transfer position deviation is obtained, including the following steps:

[0096] The benchmark determination process includes alignment in the pattern coordinate system and alignment in the carrier coordinate system;

[0097] Production alignment printing process, including compensation alignment of pattern coordinate system and carrier coordinate system;

[0098] Move the pad of the device to achieve pad printing at the correct position of the pattern.

[0099] See also Figure 3 As shown, the benchmark determination process also includes camera calibration and benchmark determination, among which: alignment within the pattern coordinate system, the equipment rubber head is aligned with the pattern center; alignment circle within the carrier coordinate system, the equipment rubber head is aligned with the carrier center; the equipment rubber head is moved to realize the transfer action of the correct position of the pattern.

[0100] See also Figure 4 As shown, the production alignment printing process also includes: alignment within the pattern coordinate system, calculating and compensating for the deviations in the horizontal axis steel plate and the vertical axis; alignment circle within the carrier coordinate system, calculating and compensating for the deviations in the horizontal axis trolley and the vertical axis; moving the equipment rubber head to achieve the transfer action of the pattern in the correct position.

[0101] Through the above steps, the present invention can achieve high-precision correction of the pattern transfer position, greatly improve production efficiency and product quality, and has significant application value and promotion prospects.

[0102] In some embodiments, see Figure 5 As shown, the correction method of the pattern transfer position deviation based on the camera internal and external parameters also includes a three-dimensional machine vision camera calibration, and the three-dimensional machine vision camera calibration includes the following steps:

[0103] Step S101, prepare a robot, a camera mounted on a manipulator, a depth sensor, a calibration block and a calibration ball at a fixed spatial position;

[0104] Step S102, keeping the calibration plate still, photographing the calibration plate from three different positions to obtain images, which are named as initial position, position 1, and position 2 respectively;

[0105] Step S103, using the end position posture provided by the robot controller, three posture matrices H0, H1, H2 of the robot are obtained through transformation, and the transformation matrices A1 and A2 corresponding to the two movements of the tool are calculated;

[0106] Step S104, using camera calibration to obtain the external parameter matrices M0, M1, and M2 corresponding to the initial position, position 1, and position 2, and calculating the transformation matrices B1 and B2 corresponding to the two camera movements;

[0107] Step S105, calibrate the three-dimensional point cloud data; use Zhang's correction method to estimate the camera's intrinsic parameter matrix; calculate the camera's extrinsic parameters for each set of matched feature points; use a nonlinear optimization method to fine-tune the intrinsic and extrinsic parameters;

[0108] Step S106, evaluating the accuracy of the calibration result by calculating indicators such as reprojection error and image quality after distortion correction; applying the intrinsic and extrinsic parameters to subsequent image processing and computer vision tasks.

[0109] Among them, in step S103, the transformation matrix A1 is from the initial position to position 1; the transformation matrix A2 is from the initial position to position 2; the calculation formulas of the transformation matrices A1 and A2 are:

[0110]

[0111]

[0112] In step S104, the transformation matrix B1 is from the initial position to position 1; the transformation matrix B2 is from the initial position to position 2; the calculation formulas of the transformation matrices B1 and B2 are:

[0113]

[0114] .

[0115] Among them, in step S105, when calibrating the three-dimensional point cloud data, it includes converting the rotation matrix into a rotation vector; normalizing the rotation vector, calculating the modified Rodriguez vector, calculating the initial rotation vector, calculating the rotation vector, and calculating the rotation matrix and translation matrix. Among them:

[0116] When the rotation matrix is ​​converted into a rotation vector, the calculation formula is:

[0117]

[0118] The rotation vector is normalized and the calculation formula is:

[0119]

[0120] Calculate the modified Rodriguez vector using the formula:

[0121]

[0122] Calculate the initial rotation vector using the following formula:

[0123]

[0124] Calculate the rotation vector using the following formula:

[0125]

[0126] Calculate the rotation matrix, the calculation formula is:

[0127]

[0128] Calculate the translation matrix, the calculation formula is:

[0129]

[0130] In the formula, The rotation matrix is ​​a 3x3 matrix in three-dimensional space, which is used to describe the rotation of an object around a certain point. It can be expressed as a rotation around the x-axis, y-axis, or z-axis, or obtained from the rotation vector through the Rodriguez formula.

[0131] is the rotation vector, which is a three-dimensional vector representing the direction of the rotation axis and the magnitude of the rotation. The magnitude of the rotation vector represents the angle of rotation, and the direction represents the rotation axis.

[0132] is the initial rotation vector ;

[0133] is the initial rotation vector ;

[0134] and is the rotation matrix, which is used to calculate the rotation matrix of the rotation vector, representing different rotation operations or rotations in different coordinate systems; Represents the rotation matrix a, describing the rotation state of object a, Represents the rotation matrix b, describing the rotation state of object b;

[0135] is the translation vector, that is, the translation component in the translation matrix, which represents the displacement of the object in the x-axis direction;

[0136] Represents the identity matrix, used for multiplication operations;

[0137] The skew function is a function that converts a vector into a skew-symmetric matrix and is used to calculate the rotation matrix; the sin and cos functions are trigonometric functions that are used to calculate the components in rotation and translation.

[0138] In this embodiment, vector dot product (V4): This is the dot product result of vector v, which is usually used to calculate scalars; vector cross product (PxPI): This is the cross product result of vector p and vector q, coefficients in the Rodriguez transform formula (1, 2, 4): These coefficients are the parameters in the Rodriguez formula, which are used to convert a rotation vector into a rotation matrix.

[0139] Through the above-mentioned three-dimensional machine vision camera calibration, accurate calibration of the camera's intrinsic and extrinsic parameters was achieved. A camera calibration system was designed and implemented, including key technologies such as data acquisition, calibration algorithm implementation, and result visualization. The accuracy and stability of the proposed method were proved through experimental verification, which improved the accuracy and reliability of camera calibration.

[0140] The method for correcting the position deviation of pattern transfer based on camera internal and external parameters of the present invention can accurately calculate the actual deviation of the pattern by calibrating the internal and external parameters of the camera. This ensures that the transfer equipment can be adjusted according to the precise deviation information, thereby achieving high-precision pattern transfer. By establishing a correspondence between the pixel coordinate system and the world coordinate system, it is ensured that each transfer can be accurately aligned with the center position of the pattern to reduce position errors. By dynamically adjusting the X-axis and Y-axis directions of the steel plate, it is ensured that the position of each transfer can be aligned with the preset reference position, which helps to reduce the defective rate caused by position deviation during the transfer process. Accurate calibration and deviation correction ensure the consistency of each transfer, thereby reducing quality problems caused by position deviation.

[0141] The correction method of the pattern transfer position deviation based on the camera internal and external parameters of the present invention also reduces the need for manual intervention through automated deviation calculation and correction process, thereby improving the automation level and production efficiency of the production line. The precise calibration of the camera internal and external parameters reduces the debugging time after each equipment startup or maintenance, so that the production line can resume normal production more quickly. The three-dimensional machine vision is used to perform high-precision calibration of the camera internal and external parameters to ensure the stability and accuracy of the system after long-term operation. Through real-time deviation detection and correction, various position changes and errors that may occur in the production process can be responded to in a timely manner, thereby enhancing the stability of the system. Through technologies such as image enhancement and morphological feature screening, the Mark point can be more accurately identified and located to ensure the position accuracy of the pattern transfer. This directly improves the appearance quality and market competitiveness of the product. Accurate deviation calculation and correction methods ensure the consistency and repeatability of each batch of products, thereby improving product quality and customer satisfaction.

[0142] In summary, the pattern transfer position deviation correction method based on camera internal and external parameters of the present invention reduces the defective rate, reduces the waste cost caused by position deviation, improves the overall production efficiency, and reduces the waste of materials through efficient and accurate transfer, improves the utilization efficiency of resources, and reduces production costs. It not only improves the accuracy and consistency of transfer in technology, but also brings significant improvements in production management and operating costs.

[0143] According to a second aspect of an embodiment of the present invention, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method of any one of the above embodiments is implemented.

[0144] The computer device includes a processor and a memory, and may also include an input system and an output system. The processor, memory, input system and output system may be connected via a bus or other means, and the input system may receive input digital or character information, and generate signal input related to the migration of the correction method of the pattern transfer position deviation based on the internal and external parameters of the camera. The output system may include display devices such as a display screen.

[0145] As a non-volatile computer-readable storage medium, the memory can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as the program instructions / modules corresponding to the correction method of the pattern transfer position deviation based on the internal and external parameters of the camera in the embodiment of the present application. The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created by the use of the correction method of the pattern transfer position deviation based on the internal and external parameters of the camera, etc. In addition, the memory 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 embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the local module 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.

[0146] In some embodiments, the processor may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor is generally used to control the overall operation of the computer device. In this embodiment, the processor is used to run the program code stored in the memory or process data. The processors of the multiple computer devices of the computer device of this embodiment execute various functional applications and data processing of the server by running non-volatile software programs, instructions and modules stored in the memory, that is, to implement the steps of the correction method of the pattern transfer position deviation based on the internal and external parameters of the camera in the above method embodiment.

[0147] It should be understood that, without conflicting with each other, all the embodiments, features and advantages described above for the method for correcting the pattern transfer position deviation based on camera internal and external parameters according to the present invention are also applicable to the method for correcting the pattern transfer position deviation based on camera internal and external parameters and storage medium according to the present invention.

[0148] It will also be appreciated by those skilled in the art that various exemplary logic blocks, modules, circuits and algorithm steps described in conjunction with the disclosure herein can be implemented as electronic hardware, computer software or a combination of the two. In order to clearly illustrate this interchangeability of hardware and software, a general description has been given to the functions of various schematic components, blocks, modules, circuits and steps. Whether this function is implemented as software or hardware depends on specific applications and the design constraints imposed on the entire system. Those skilled in the art can implement the function in various ways for each specific application, but this implementation decision should not be interpreted as causing a departure from the disclosed scope of the embodiments of the present invention.

[0149] The above are exemplary embodiments disclosed in the present invention, but it should be noted that various changes and modifications may be made without departing from the scope disclosed in the embodiments of the present invention as defined in the claims. The functions, steps and / or actions of the method claims according to the disclosed embodiments described herein do not need to be performed in any particular order. In addition, although the elements disclosed in the embodiments of the present invention may be described or required in individual form, they may also be understood as multiple unless explicitly limited to the singular.

[0150] It should be understood that, as used herein, the singular form "a" or "an" is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, "and / or" refers to any and all possible combinations of one or more of the items listed in association. The serial numbers of the embodiments disclosed in the above embodiments of the present invention are for description only and do not represent the advantages and disadvantages of the embodiments.

[0151] A person skilled in the art should understand that the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the disclosure of the embodiments of the present invention (including the claims) is limited to these examples; under the concept of the embodiments of the present invention, the technical features in the above embodiments or different embodiments can also be combined, and there are many other changes in different aspects of the above embodiments of the present invention, which are not provided in detail for the sake of simplicity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present invention should be included in the protection scope of the embodiments of the present invention.

Claims

1. A method for correcting pattern transfer position deviation based on camera internal and external parameters, characterized in that: The following steps are involved: Calibrate the lens, obtain the internal and external parameters of the camera, and establish a world coordinate system corresponding to the pixel coordinate system at each steel plate position; Confirm the benchmark and adjust the X-axis and Y-axis directions of the steel plate to obtain the correct pattern coordinates; Define the pattern area, perform image enhancement on the area, find the Mark point area, select the Mark points by morphological features, calculate the center coordinates of the pattern, and compare them with the reference coordinates to obtain the X-axis and Y-axis deviations; Move the device rubber head and adjust the direction of the camera in the pattern and carrier coordinate system to achieve pad printing at the correct position of the pattern; The method for correcting the pattern transfer position deviation based on the camera internal and external parameters also includes three-dimensional machine vision camera calibration, which includes the following steps: Prepare a robot, a camera mounted on a manipulator, a depth sensor, a calibration block and a calibration ball with a fixed spatial position; Keep the calibration plate still, and take pictures of the calibration plate from three different positions to obtain images, which are named initial position, position 1, and position 2 respectively; Using the end position posture provided by the robot controller, the three posture matrices H0, H1, and H2 of the robot are obtained through transformation, and the transformation matrices A1 and A2 corresponding to the two movements of the tool are calculated; Use camera calibration to obtain the external parameter matrices M0, M1, and M2 corresponding to the initial position, position 1, and position 2, and calculate the transformation matrices B1 and B2 corresponding to the two camera movements; Calibrate 3D point cloud data; Estimate the camera's intrinsic parameter matrix using Zhang's correction method; Calculate the camera's extrinsic parameters for each set of matched feature points; Use nonlinear optimization methods to fine-tune internal and external parameters; The accuracy of the calibration results is evaluated by calculating the reprojection error and the image quality index after distortion correction; Apply intrinsic and extrinsic parameters to subsequent image processing and computer vision tasks.

2. The method for correcting pattern transfer position deviation based on camera internal and external parameters according to claim 1, characterized in that: Obtaining correction of pattern transfer position deviation includes the following steps: The benchmark determination process includes alignment in the pattern coordinate system and alignment in the carrier coordinate system; Production alignment printing process, including compensation alignment of pattern coordinate system and carrier coordinate system; Move the pad of the device to achieve pad printing at the correct position of the pattern.

3. The method for correcting pattern transfer position deviation based on camera internal and external parameters according to claim 2, characterized in that: The benchmark determination process also includes camera calibration and benchmark determination, including: Alignment within the pattern coordinate system, with the equipment rubber head aligned with the pattern center; The alignment circle in the carrier coordinate system, the equipment rubber head is aligned with the center of the carrier; Move the rubber head of the device to achieve the transfer action of the pattern to the correct position.

4. The method for correcting pattern transfer position deviation based on camera internal and external parameters according to claim 3, characterized in that: The production process of offset printing also includes: Alignment within the pattern coordinate system, calculation and compensation of deviations in the horizontal and vertical directions of the steel plate; The alignment circle in the carrier coordinate system calculates and compensates for the deviations in the horizontal and vertical axis directions; Move the rubber head of the device to achieve the transfer action of the pattern to the correct position.

5. The method for correcting pattern transfer position deviation based on camera internal and external parameters according to claim 4, characterized in that: The transformation matrix A1 is from the initial position to position 1; the transformation matrix A2 is from the initial position to position 2; the calculation formulas of the transformation matrices A1 and A2 are: The transformation matrix B1 is from the initial position to position 1; the transformation matrix B2 is from the initial position to position 2; the calculation formulas of the transformation matrices B1 and B2 are: 。 6. The method for correcting pattern transfer position deviation based on camera internal and external parameters according to claim 5, characterized in that: The calibration of three-dimensional point cloud data includes converting the rotation matrix into a rotation vector; normalizing the rotation vector, calculating the modified Rodriguez vector, calculating the initial rotation vector, calculating the rotation vector, and calculating the rotation matrix and the translation matrix.

7. The method for correcting pattern transfer position deviation based on camera internal and external parameters according to claim 6, characterized in that: When the rotation matrix is ​​converted into a rotation vector, the calculation formula is: The rotation vector is normalized and the calculation formula is: Calculate the modified Rodriguez vector using the formula: Calculate the initial rotation vector using the following formula: Calculate the rotation vector using the following formula: Calculate the rotation matrix, the calculation formula is: Calculate the translation matrix, the calculation formula is: In the formula, is the rotation matrix, is the rotation vector, and is the rotation matrix, Represents the identity matrix.

8. A computer device comprising a memory and a processor, characterized in that: The memory stores a computer program, which, when executed by the processor, executes the method for correcting the pattern transfer position deviation based on camera internal and external parameters as described in any one of claims 1 to 7.

9. A computer-readable storage medium storing computer program instructions, which, when executed, implement the method for correcting pattern transfer position deviation based on camera internal and external parameters as described in any one of claims 1 to 7.

Images