Camera distortion adjustment method and system, storage medium and device

Abstract

The invention provides a camera distortion adjustment method and system, a storage medium and a device, and the method comprises the steps: obtaining image data, and detecting the angular point coordinate position of the image data; obtaining a distortion center range of the camera based on the angular point coordinate position, and calculating and obtaining a final distortion center position according to the distortion center range; and acquiring the distance between the final distortion center position and the imaging center position of the camera, and adjusting the final distortion center position based on the distance until the final distortion center position is within a first preset distance range of the imaging center position of the camera. According to the method provided by the invention, the automatic adjustment of the distortion center position of the camera is realized, the accuracy and reliability of determining the center of the camera are improved, and the consistency and practicability of imaging of the camera are ensured.

Description

Technical Field

[0001] The present application relates to the field of computer vision, and specifically to a camera distortion adjustment method, system, storage medium and device. Background Art

[0002] With the continuous development of autonomous driving technology, image sensors have become an important part of the intelligence and safety of modern automobiles, and are widely used in lane detection, traffic sign recognition, obstacle monitoring, pedestrian recognition, intelligent driving, etc. Image sensors have higher and higher pixels, wider applications, and more and more diverse functions, which also brings more and more challenges to the entire process manufacturing, and the requirements for center alignment are also getting higher and higher.

[0003] At present, traditional vehicle camera assembly equipment mostly uses a planar light source and a chart. By building a target, the target is used as the center reference for imaging to determine the center for assembly and focusing. Since the target chart is movable, the determined center will change as the chart moves, resulting in large differences between devices and before and after the model change, causing distortion of the image data obtained by the camera equipment and low accuracy. Traditional vehicle camera assembly equipment has high environmental requirements, which is difficult to achieve through traditional artificial assumptions. The difference between the camera imaging end and the distortion center is large, which cannot meet the actual production requirements in different environments. Summary of the invention

[0004] In order to solve the above technical problems, the present application proposes a camera distortion adjustment method, system, storage medium and device. The purpose is to solve the problem of equipment differences caused by the movement of the target target card during the process of assembling and focusing the center of the vehicle-mounted camera using the target target as the center reference detection of the imaging to determine the center, thereby improving the accuracy and reliability of determining the center of the camera.

[0005] Specifically, the present application proposes a camera distortion adjustment method, comprising:

[0006] Image data is acquired, and the coordinate positions of corner points of the image data are detected.

[0007] The distortion center range of the camera is obtained based on the coordinate position of the corner point, and the final distortion center position is calculated according to the distortion center range.

[0008] And, obtaining the distance between the final distortion center position and the camera imaging center position, so as to adjust the final distortion center position based on the distance until the final distortion center position is within a first preset distance range of the camera imaging center position.

[0009] In the above technical solution, the final distortion center position is adjusted by calculating the distance between the final distortion center position and the camera imaging center position, thereby reducing the distortion of the image data acquired by the camera and improving the accuracy and consistency of the image data collected by the camera. By adjusting the final distortion center position, the camera distortion is automatically adjusted, so that the camera can adapt to different operating environments and improve the reliability and practicality of the camera.

[0010] Further, the detecting the coordinate position of the corner point of the image data includes:

[0011] The image data is converted into first image data in a preset format.

[0012] A corner point region in the first image data is detected based on a corner point detection algorithm.

[0013] The corner point area is filtered to obtain the coordinate position of the corner point.

[0014] Among them, by using the corner point detection algorithm, the corner point area in the first image data can be effectively detected, and filtering the corner point area effectively eliminates noise and irrelevant corner points, ensuring the reliability and robustness of the extracted corner point coordinate positions.

[0015] Furthermore, the obtaining of the distortion center range of the camera based on the corner point coordinate position includes:

[0016] The distances between all corner points are obtained according to the corner point coordinate positions, the area of ​​the corner point block is calculated based on the corner point distances, the area of ​​the corner point block is calculated through a relational data model, and the distortion center range is obtained.

[0017] By calculating the corner point block area through the relational data model, the distortion center range can be accurately obtained. By obtaining the distortion center range, a foundation is laid for the subsequent acquisition of the final distortion center position, thereby improving the accuracy and reliability of the final distortion center position.

[0018] Furthermore, before calculating and obtaining the final distortion center position according to the distortion center range, the method further includes:

[0019] Determine whether the distortion center range is within a second preset distance range of the camera imaging center position. If so, calculate the final distortion center position; otherwise, calculate the distortion center range again until the distortion center range is within the second preset distance range of the camera imaging center position.

[0020] By judging whether the distortion center range is within the second preset distance range of the camera imaging center position, the final distortion center position is calculated when the distortion center range is within the second preset distance range of the camera imaging center position, thereby improving the accuracy of the calculation of the final distortion center position. By means of a cyclic calculation method, it is ensured that the distortion center range meets the second preset distance range, thereby improving the stability and reliability of the algorithm.

[0021] Furthermore, the step of calculating and obtaining a final distortion center position according to the distortion center range further includes:

[0022] The calculated distortion center position is verified according to the corner point block area, and the verified distortion center position is used as the final distortion center position. The accuracy of the distortion center position is ensured by verifying the distortion center position.

[0023] Further, the adjusting the final distortion center position based on the distance until the final distortion center position is within a first preset distance range of the camera imaging center position includes:

[0024] Based on the distance, it is determined whether the final distortion center position is within a first preset distance range of the camera imaging center position; if so, the current distortion adjustment is ignored.

[0025] Otherwise, the pixel difference between the final distortion center position and the standard distortion center is calculated.

[0026] The pixel difference is converted into a distance difference, and the final distortion center position is offset adjusted according to the distance difference.

[0027] After the adjustment is completed, the image data is reacquired to calculate the final distortion center position until the final distortion center position is within a first preset distance range of the camera imaging center.

[0028] By adjusting the offset of the final distortion center position, it is ensured that the camera can automatically adjust the distortion center in different environments, thereby improving the practicality of the camera. By calculating the pixel difference between the final distortion center and the standard distortion center, the position can be adjusted in detail, thereby enhancing the accuracy of the distortion center position adjustment.

[0029] Further, after adjusting the final distortion center position to within the preset distance difference range, the method further includes:

[0030] The adjusted distortion center position is fixed by pre-curing.

[0031] Pre-curing at the adjusted distortion center position can ensure the consistency of the camera's image data acquisition, reduce the instability caused by frequent adjustment of the distortion center position, effectively avoid the cumulative error caused by repeated adjustment, and ensure stable image data output in different environments. The pre-curing method can quickly adapt to distortion in different scenes or conditions, improving the overall adaptability of the system.

[0032] Based on the same inventive concept, the present application also proposes a system for a camera distortion adjustment method, the system comprising: a data acquisition module, a corner point detection module, a calculation module and an adjustment module.

[0033] The data acquisition module is used to acquire image data.

[0034] The corner point detection module is used to detect the coordinate positions of the corner points of the image data.

[0035] The calculation module is used to obtain the distortion center range of the camera based on the corner point coordinate position, and calculate and obtain the final distortion center position according to the distortion center range.

[0036] And, the adjustment module is used to obtain the distance between the final distortion center position and the camera imaging center position, so as to adjust the final distortion center position based on the distance until the final distortion center position is within a first preset distance range of the camera imaging center position.

[0037] Based on the same inventive concept, the present application also proposes a computer-readable storage medium, which stores computer-executable instructions. The computer-executable instructions can be read by a domain controller and execute the camera distortion adjustment method.

[0038] Based on the same inventive concept, the present application also proposes a camera device, in which a distortion adjustment system is configured, and the distortion adjustment system executes the camera distortion adjustment method when running.

[0039] Compared with the prior art, this application has at least the following beneficial effects:

[0040] The camera distortion adjustment method proposed in this application provides an effective solution for determining the center reference for assembly and focusing of the vehicle-mounted camera during actual application. It solves the problem of changes in the center reference due to the movement of the target target card and the difference before and after the model change. By calculating the camera distortion center position and adjusting the final distortion center position, the distortion of the image data obtained by the camera is reduced, and the accuracy and consistency of the image data collected by the camera are improved. The automatic adjustment of the camera distortion is achieved by adjusting the final distortion center position, so that the camera can adapt to different operating environments and improve the reliability and practicality of the camera. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flow chart of the camera distortion adjustment method shown in an embodiment of the present application.

[0042] Figure 2 It is a schematic diagram of a camera distortion adjustment system shown in an embodiment of the present application. DETAILED DESCRIPTION

[0043] 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 only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0044] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0045] Embodiment 1:

[0046] Please refer to Figure 1 , the camera distortion adjustment method mainly includes:

[0047] Acquire image data and detect the coordinate positions of the corner points of the image data. The image data may be one or more image card data captured by an image sensor. A corner detection algorithm may be used to detect corners of the image data. The corner detection algorithm may be a corner detection method of OpenCV (Open Source Computer Vision Library). OpenCV is an open source computer vision library designed for real-time image processing. It provides a wealth of functions and tools that can process images and videos and perform multiple tasks such as feature detection, object recognition, and image enhancement.

[0048] The distortion center range of the camera is obtained based on the coordinate position of the corner point, and the final distortion center position is obtained by calculation according to the distortion center range. Among them, a mathematical model equation can be established mainly by polynomial fitting based on the obtained coordinate position of the corner point, the distortion center range of the camera is obtained according to the mathematical model equation, and then the final distortion center position is further calculated by integral calculation according to the obtained distortion center range.

[0049] And, obtain the distance between the final distortion center position and the camera imaging center position, so as to adjust the final distortion center position based on the distance until the final distortion center position is within the first preset distance range of the camera imaging center position. Among them, the final distortion center position can be mainly adjusted by a six-axis mechanism. The first preset distance range is the deviation range between the final distortion center position and the camera imaging center position, which can mainly be 1 pixel unit. The technicians in this field can adjust the first preset distance range according to the actual situation, and are not limited to this.

[0050] In some embodiments, detecting the coordinate position of the corner point of the image data includes:

[0051] The image data is converted into first image data in a preset format, a corner point region in the first image data is detected based on a corner point detection algorithm, and the corner point region is filtered to obtain the coordinate position of the corner point.

[0052] The first image data in the preset format can mainly be a grayscale image, and converting the image data into a grayscale image is more conducive to detecting corners in the image data. The corner detection algorithm can mainly adopt the corner detection method of OpenCV. Technicians in this field can select the corresponding corner detection algorithm according to actual working conditions, such as Harris (Harris Corner Detection) corner detection algorithm, Shi-Tomasi (Shi-Tomasi Corner Detection) corner detection algorithm, FAST (Features from Accelerated Segment Test), SIFT (Scale-Invariant Feature Transform), SURF (Speeded Up Robust Features) and ORB (Oriented FAST and Rotated BRIEF) corner detection algorithm.

[0053] Taking the corner point detection method of OpenCV as an example, the first image data is subjected to corner point detection by the corner point detection method of OpenCV to obtain a spot-shaped corner point region. The corner point region is filtered according to the distribution rule of the spot-shaped corner point region to reduce the influence of noise on the corner points, and the coordinate positions of all corner points are obtained.

[0054] Optionally, acquiring the distortion center range of the camera based on the corner point coordinate position includes:

[0055] The distances between all corner points are obtained according to the corner point coordinate positions, the area of ​​the corner point block is calculated based on the corner point distances, the area of ​​the corner point block is calculated through a relational data model, and the distortion center range is obtained.

[0056] Among them, the distance between all corner points can be obtained according to the corner point coordinate position mainly by recording the distance between the corner points in each row and each column in the corner point coordinate system, and the area of ​​each corner point block is calculated according to the distance between the corner points, and the distortion center range is obtained by calculating the relational data model.

[0057] For example, the coordinate position of each corner point can be recorded as P n =(X n , Y n ), where n is a natural number;

[0058] According to the coordinate position of the corner points, the distance between the corner points in each row is recorded as At the same time, the y coordinate Ly_n of each row is obtained, where n and i are natural numbers.

[0059] According to the coordinate position of the corner points, the interval distance of each column of corner points is recorded as At the same time, the x coordinate Lx_n of each column is obtained, where n and i are natural numbers.

[0060] The corner point block area S between each of the four corner points is obtained by calculating the spacing distance of each row of corner points and the spacing distance of each column of corner points. n , where n is a natural number.

[0061] According to the correlation between Ly_n and Lw_n, and the correlation between Lh_n and Lx_n, a mathematical model equation is established by polynomial fitting, and the coefficients of the model are confirmed based on the maximum correlation, and the distortion center range is calculated according to the mathematical model.

[0062] Optionally, before calculating and obtaining a final distortion center position according to the distortion center range, the method may further include:

[0063] Determine whether the distortion center range is within the second preset distance range of the camera imaging center position. If so, calculate the final distortion center position; otherwise, calculate the distortion center range again until the distortion center range is within the second preset distance range of the camera imaging center position. The second preset distance range may be a 2-pixel distance. When the distortion center range is outside the 2-pixel distance range of the camera imaging center position, it is necessary to reversely recalculate the distortion center until it is within the 2-pixel distance range. Those skilled in the art may adjust the second preset distance range according to actual conditions, and are not limited thereto.

[0064] Optionally, the calculating and obtaining a final distortion center position according to the distortion center range further includes:

[0065] The calculated distortion center position is verified according to the corner point block area, and the verified distortion center position is used as the final distortion center position.

[0066] For example, assuming that the distortion center range calculated in the above technical solution is Cx, Cy, the area of ​​the corner point blocks on the left and right sides of Cx can be calculated by using the ideal symmetry principle of the image sensor lens and the integral calculation method. Among them, Sx_L is the area of ​​the corner block on the left side of Cx, and Sx_R is the area of ​​the corner block on the right side of Cx. Take the Cx closest to Sx_L and Sx_R as the Cx of the distortion center. Then calculate the area of ​​the corner blocks on the left and right sides of Cy according to the integral calculation method. Where Sy_L is the area of ​​the corner block on the left side of Cy, and Sy_R is the area of ​​the corner block on the right side of Cy. According to the calculated Sy_L and Sy_R, the closest Cy is obtained as the Cy of the distortion center. n The distortion center position is verified to obtain the final distortion center position.

[0067] Optionally, the adjusting the final distortion center position based on the distance until the final distortion center position is within a first preset distance range of a camera imaging center position includes:

[0068] Based on the distance, it is determined whether the final distortion center position is within a first preset distance range of the camera imaging center position; if so, the current distortion adjustment is ignored.

[0069] Otherwise, the pixel difference between the final distortion center position and the standard distortion center is calculated.

[0070] The pixel difference is converted into a distance difference, and the final distortion center position is offset adjusted according to the distance difference.

[0071] After the adjustment is completed, the image data is reacquired to calculate the final distortion center position until the final distortion center position is within a first preset distance range of the camera imaging center.

[0072] Wherein, by calculating the distance between the final distortion center position and the camera imaging center position. According to the distance, it is judged whether the final distortion center position is within the first preset range of the camera imaging center position, for example, it is judged whether the distance is within 1 pixel range of the camera imaging center position. If so, the final distortion center position can be directly used for subsequent pre-curing processing. Otherwise, the pixel difference between the final distortion center position and the standard distortion center is calculated, and the pixel difference is converted into a distance difference by a calculation method that the distance difference is equal to the product of the pixel difference and the actual length of each pixel, and then the final distortion center position is offset adjusted according to the distance difference. The distortion adjustment of the final distortion center position can mainly be performed by using a six-axis mechanism to relatively cheaply adjust the camera and the sensor. In the actual adjustment process, the camera or the sensor can be adjusted left and right or up and down along the x or y direction mainly by the six-axis mechanism. After the adjustment is completed, the final distortion center position is recalculated in an iterative manner to ensure that the final distortion center position is within the first preset distance range.

[0073] Optionally, after adjusting the final distortion center position to within a preset distance difference range, the method further includes:

[0074] The adjusted center position of the distortion is fixed by pre-curing. Among them, the pre-curing method can mainly adopt UV pre-curing (Ultraviolet Pre-Curing), and the UV pre-curing method mainly uses ultraviolet irradiation to make the chemical components in the coating or glue containing photosensitive materials undergo polymerization reaction, thereby quickly curing. The adjusted center position of the distortion can be quickly cured by the UV pre-curing method, which reduces the curing time and improves the system efficiency. Those skilled in the art can select the corresponding pre-curing method according to actual needs, but are not limited to this. For example, thermal curing, natural curing, chemical curing, electromagnetic curing or cold curing can also be selected according to actual conditions.

[0075] Embodiment 2:

[0076] Please refer to Figure 2 The present application also proposes a system that adopts the camera distortion adjustment method described in Example 1, which mainly includes: a data acquisition module, a corner point detection module, a calculation module and an adjustment module.

[0077] The data acquisition module is used to acquire image data. The image data can mainly be one or more image card data collected by an image sensor, and the image sensor at least includes a vehicle-mounted camera device. The image data can be used to obtain more corner points and a wider coverage range, thereby improving the accuracy and adaptability of subsequent distortion center position calculation.

[0078] The corner point detection module is used to detect the coordinate positions of the corner points of the image data. Among them, it mainly includes converting the image data into first image data of a preset format, then detecting the corner point area in the first image data according to the corner point detection algorithm, and filtering the corner point area to obtain the coordinate positions of the corner points. The first image data of the preset format can mainly be a grayscale image, and converting the image data into a grayscale image is more conducive to detecting the corner points. The corner point detection algorithm can mainly be detected by the corner point detection algorithm of OpenCV, which mainly includes first detecting the corner point area of ​​the spot shape, and then filtering the corner point area of ​​the spot shape obtained by the detection to remove the noise caused by the false detection, and obtaining the coordinate positions of the corner points after filtering. Those skilled in the art can select different corner point detection algorithms according to actual needs, and are not limited to the corner point detection algorithm of OpenCV.

[0079] The calculation module is used to obtain the distortion center range of the camera based on the corner point coordinate position, and calculate the final distortion center position according to the distortion center range. Wherein, the method of obtaining the distortion center range of the camera based on the corner point coordinate position can mainly include recording the coordinate position of each corner point in the image data, recording the distance of the corner points in each row and column according to the corner point coordinate position, and calculating the area of ​​each corner point block according to the distance, and obtaining the distortion center range through a relational data model. The relational data model can mainly be a mathematical equation model of polynomial fitting. After obtaining the distortion center range, the final distortion center position is further calculated according to the distortion center range using an integral calculation method.

[0080] And, the adjustment module is used to obtain the distance between the final distortion center position and the camera imaging center position, so as to adjust the final distortion center position based on the distance until the final distortion center position is within a first preset distance range of the camera imaging center position.

[0081] When the distance between the final distortion center position and the camera imaging center position is no longer within the first preset range, the difference pixel between the final distortion center position and the standard distortion center is calculated, and then the pixel difference is converted into a distance difference, and the final distortion center position is offset and adjusted according to the distance difference, and then the image data is reacquired in an iterative manner to calculate the final distortion center position until the final distortion center position meets the first preset distance range. After confirming that the final distortion center position meets the first preset distance range, the final distortion center position is fixed by pre-curing.

[0082] Embodiment three:

[0083] The present application also proposes a computer-readable storage medium, the computer-readable storage medium comprising:

[0084] The computer-readable storage medium stores computer-executable instructions.

[0085] When the computer executable instructions are executed by the control processor, the camera distortion adjustment method described in Example 1 is implemented.

[0086] In the computer-readable storage medium, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk SolidState Disk (SSD)), etc.

[0087] Embodiment 4:

[0088] The present application further proposes a camera device, wherein the camera device is provided with a distortion adjustment system, and when the distortion adjustment system is running, the camera distortion adjustment method described in the first embodiment is executed.

[0089] The camera device may also include a six-axis mechanism, which processes the collected image data through the distortion adjustment system to calculate the distortion center position of the camera device, and then uses the six-axis mechanism to perform offset adjustment on the camera device according to the imaging center position of the camera device, until the offset error between the distortion center position of the camera device and the imaging center position meets a preset reasonable range, and then the distortion center position of the camera device is cured by pre-curing.

[0090] In summary, the camera distortion adjustment method proposed in this application provides an effective solution for determining the center reference for assembly and focusing of the vehicle-mounted camera during actual application. The problem of changes in the center reference due to the movement of the target target card and differences before and after the model change is solved. By calculating the camera distortion center position and adjusting the final distortion center position, the distortion of the image data acquired by the camera is reduced, and the accuracy and consistency of the image data collected by the camera are improved. The automatic adjustment of the camera distortion is achieved by adjusting the final distortion center position, so that the camera can adapt to different operating environments and improve the reliability and practicality of the camera.

[0091] In several embodiments provided in the present application, it is understood that each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved.

[0092] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling an electronic device to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0093] The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the scope of protection of the present application. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A camera distortion adjustment method, characterized in that: include: Acquire image data, and detect the coordinate positions of corner points of the image data; Obtaining a distortion center range of the camera based on the corner point coordinate position, and calculating and obtaining a final distortion center position according to the distortion center range; And, obtaining the distance between the final distortion center position and the camera imaging center position, so as to adjust the final distortion center position based on the distance until the final distortion center position is within a first preset distance range of the camera imaging center position.

2. The camera distortion adjustment method according to claim 1, characterized in that: The detecting the coordinate position of the corner point of the image data comprises: Converting the image data into first image data in a preset format; Detecting corner point regions in the first image data based on a corner point detection algorithm; The corner point area is filtered to obtain the coordinate position of the corner point.

3. The camera distortion adjustment method according to claim 1, characterized in that: The obtaining of the distortion center range of the camera based on the corner point coordinate position includes: Obtaining the interval distances of all corner points according to the coordinate positions of the corner points; Calculate the corner point block area based on the corner point interval distance; The area of ​​the corner point block is calculated through a relational data model to obtain the distortion center range.

4. The camera distortion adjustment method according to claim 3, characterized in that: Before calculating and obtaining the final distortion center position according to the distortion center range, the method further includes: Determine whether the distortion center range is within a second preset distance range of the camera imaging center position. If so, calculate the final distortion center position; otherwise, calculate the distortion center range again until the distortion center range is within the second preset distance range of the camera imaging center position.

5. The camera distortion adjustment method according to claim 3, characterized in that: The step of calculating and obtaining a final distortion center position according to the distortion center range further includes: The calculated distortion center position is verified according to the corner point block area, and the verified distortion center position is used as the final distortion center position.

6. The camera distortion adjustment method according to claim 1, characterized in that: The adjusting the final distortion center position based on the distance until the final distortion center position is within a first preset distance range of a camera imaging center position includes: Based on the distance, determining whether the final distortion center position is within a first preset distance range of the camera imaging center position, and if so, ignoring the current distortion adjustment; Otherwise, calculating the pixel difference between the final distortion center position and the standard distortion center; The pixel difference is converted into a distance difference, and the final distortion center position is offset adjusted according to the distance difference; after the adjustment, the image data is reacquired to calculate the final distortion center position until the final distortion center position is within a first preset distance range of the camera imaging center.

7. The camera distortion adjustment method according to claim 1, characterized in that: After adjusting the final distortion center position to within the preset distance difference range, the method further includes: The adjusted distortion center position is fixed by pre-curing.

8. A system based on the camera distortion adjustment method according to any one of claims 1 to 7, characterized in that: include: Data acquisition module, corner point detection module, calculation module and adjustment module; The data acquisition module is used to acquire image data; The corner point detection module is used to detect the coordinate positions of the corner points of the image data; The calculation module is used to obtain the distortion center range of the camera based on the coordinate position of the corner point, and calculate according to the distortion center range to obtain the final distortion center position; And, the adjustment module is used to obtain the distance between the final distortion center position and the camera imaging center position, so as to adjust the final distortion center position based on the distance until the final distortion center position is within a first preset distance range of the camera imaging center position.

9. A computer-readable storage medium storing computer-executable instructions, characterized in that: When the computer executable instructions are executed by the control processor, the camera distortion adjustment method as described in any one of claims 1-7 is implemented.

10. A camera device, wherein a distortion adjustment system is provided in the camera device, characterized in that: When the distortion adjustment system is running, it executes the camera distortion adjustment method as described in any one of claims 1-7.

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