Camera module distortion center offset test system

Abstract

The invention relates to the technical field of camera module testing, and particularly discloses a camera module distortion center offset testing system, which comprises a control module used for controlling a controllable rotating platform to move to a plurality of preset angles; the image acquisition management module is used for controlling the camera module to shoot a preset number of images from the plurality of preset angles and receiving image data; the image calibration module is used for analyzing checkerboard images in the preset number of images, establishing a mapping relation between image pixel coordinates and three-dimensional world coordinates and calculating distortion related parameters; the error resolving module is used for carrying out statistical analysis on the X-direction error d1 and the Y-direction error e1 of the multiple groups of checkerboard images so as to obtain a root-mean-square value RMSX of the X-direction error and a root-mean-square value RMSY of the Y-direction error; and the offset resolving module is used for resolving the offset COD X and the offset COD Y of the distortion center. By adopting the technical scheme of the invention, automatic collection and judgment of the COD value of the camera module can be realized.

Description

Technical Field

[0001] This invention relates to the field of camera module testing technology, and in particular to a camera module distortion center offset testing system. Background Technology

[0002] As a core component of modern electronic devices, the imaging quality of camera modules directly impacts user experience. In the production and testing of camera modules, distortion is one of the key factors affecting image quality, and the offset of the center of distortion (COD) is an important indicator for measuring the distortion correction effect and the module assembly accuracy.

[0003] In existing technologies, there may be practices in the industry that rely on optical center (OC) alignment to indirectly evaluate or guarantee distortion center (COD) alignment. However, practice has shown that optical center alignment cannot accurately reflect or guarantee distortion center alignment. This deviation leads to inaccurate test results, potentially causing unqualified modules to be misjudged as qualified, thus affecting the quality of the final product.

[0004] Furthermore, as camera module pixel counts increase, the requirements for testing accuracy also rise. Existing testing methods may lack efficient and automated means to collect and determine the COD values ​​of high-pixel products in batches, resulting in low testing efficiency, excessive manual intervention, and poor consistency, making it difficult to meet the needs of large-scale production.

[0005] Therefore, there is an urgent need for a camera module distortion center offset testing system that can solve the problem that optical center alignment is not the same as distortion center alignment, and can realize the automated collection and judgment of camera module COD values. Summary of the Invention

[0006] This invention provides a camera module distortion center offset testing system, which can realize the automated collection and judgment of camera module COD values.

[0007] To solve the above-mentioned technical problems, this application provides the following technical solution: A camera module distortion center offset testing system includes a mechanical structure, which includes a controllable rotating platform for mounting a fixture on which the camera module is fixed. The controllable rotating platform is driven by a motor to achieve multi-angle shooting of the camera module. The system also includes a software system, which comprises: The control module is used to control the controllable rotating platform to move to multiple preset angles and trigger the camera module to perform a photo-taking action; The image acquisition and management module is used to control the camera module to capture a preset number of images from the multiple preset angles and to receive image data; The image calibration module is used to analyze the checkerboard image in the preset number of images, establish the mapping relationship between image pixel coordinates and three-dimensional world coordinates, and calculate distortion-related parameters, including X-direction error and Y-direction error. The error calculation module is used to perform statistical analysis on the X-direction error d1 and Y-direction error e1 of multiple sets of chessboard images to obtain the root mean square value RMS_X of the X-direction error and the root mean square value RMS_Y of the Y-direction error. The offset calculation module is used to calculate the distortion center offsets COD X and COD Y based on RMS_X and RMS_Y, as well as the preset known physical parameters.

[0008] Furthermore, the image calibration module is used to automatically identify corner points in a checkerboard image using a 9-point calibration method; based on the known physical dimensions of the calibration board and the extracted corner point pixel coordinates, it establishes a mapping relationship between image pixel coordinates and three-dimensional world coordinates, and calculates distortion-related parameters, including the corner point coordinates, distortion coefficients, and x-direction and y-direction errors.

[0009] Furthermore, the offset calculation module calculates the root mean square value (RMS_X) of the X-direction error d1 and the root mean square value (RMS_Y) of the Y-direction error e1 using the following formulas: ; ; Where N is the number of data sets.

[0010] Furthermore, the offset calculation module is used to retrieve the known physical parameters of the current test module and convert the statistical errors RMS_X and RMS_Y into physical offsets COD_X and COD_Y. Among them, known physical parameters include pixel size, effective focal length or specific length, and projection or scaling factors in the X / Y directions.

[0011] Furthermore, the formula for calculating the physical offset CODX is as follows: ; The physical lens focal length break improves the production efficiency of the testing process itself. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the mechanical structure in an embodiment of a camera module distortion center offset testing system.

[0013] Figure 2A logic block diagram of an embodiment of a camera module distortion center offset testing system; Figure 3 This is a schematic diagram of an image captured by a camera module in a camera module distortion center offset testing system. Figure 4 This is a schematic diagram of another image captured by a camera module in a camera module distortion center offset testing system. Figure 5 This is a schematic diagram of another image captured by a camera module in a camera module distortion center offset testing system. Figure 6 This is a schematic diagram of an image captured by a camera module in a camera module distortion center offset testing system. Detailed Implementation

[0014] The following detailed description illustrates the specific implementation method: The markings in the accompanying drawings include: controllable rotating platform 1, fixture 2, PCBA 3.

[0015] Example This embodiment of a camera module distortion center offset testing system includes a mechanical structure and a software system.

[0016] Mechanical structure parts such as Figure 1 As shown, this is used to build a test environment. Its core function is to provide a controllable rotating platform 1 driven by a motor, which is used to mount a fixture 2 with a fixed camera module, and the motor enables multi-angle shooting by the camera module. Data communicates with the computer via PCBA 3.

[0017] The core of this embodiment lies in the software system. Deployed on a computer, this software system, through collaborative work with the mechanical structure, achieves accurate calculation and automated determination of COD, such as... Figure 2 As shown, it includes: The control module is used to realize communication and control between the upper-layer software logic and the lower-layer test hardware. Specifically, the control module sends commands to the PCBA through a high-speed data line to control the PCBA to perform operations such as power supply and identification, motion control, and data acquisition control.

[0018] The power supply and identification functions are as follows: Power supply and identification control refers to the PCBA providing power to each camera module and identifying each camera module. Motion control refers to sending commands to the hardware circuitry that controls the motors, driving the motors to move the rotating platform and camera modules according to a preset program (e.g., rotating a specific angle) to meet the needs of multi-angle shooting. Acquisition control refers to triggering the camera modules to perform the photo-taking action.

[0019] The image acquisition management module manages the entire image acquisition process, ensuring sufficient and high-quality data is acquired for subsequent analysis. This module collaborates with the control module to execute a preset acquisition sequence. Specifically, it controls the camera module to capture a preset number of images from multiple different preset angles, such as... Figures 3-6 As shown, it is also used to receive image data captured by the camera module and processed by the PCBA, store it on the computer, and simultaneously create an index to prepare for subsequent calculations. In this embodiment, the preset number of images is 30 real-scene images and 30 checkerboard images.

[0020] The image calibration module is used to analyze the acquired checkerboard image and establish the imaging model of the camera module. In this embodiment, a 9-point calibration method is used to automatically identify the corner points in the checkerboard image. Based on the known physical dimensions of the calibration board and the extracted corner point pixel coordinates, a mapping relationship between image pixel coordinates and three-dimensional world coordinates is established, and distortion-related parameters are calculated, including the corner point coordinates (ax, ay, bx, by), x-direction error (d1), and y-direction error (e1). Specifically, when the camera module captures the checkerboard image, it captures multiple images from different angles. The internal ISP of the camera module combines these multiple images into a single image. The four corners of the checkerboard image represent the field of view of the camera module. The actual position and outline of the checkerboard image are mapped onto the image sensor chip of the camera module. When the checkerboard moves, the corresponding image on the image sensor chip changes accordingly. The actual displacement direction and distance of the checkerboard image are calculated from the minute changes in the image on the pixel. For example, the distortion offset in the x-direction (d1) is... The calculation formula is:

[0021] Wherein, distortion offset X' = F*Dr1 / Z1*PixelSize_x - F*Dr2 / Z2*PixelSize_x F is the lens focal length, Dr is the area of ​​the nine-square grid, and Z is the axial distance from the intersection of the field of view angles to the nine-square grid. PixelSize It's the size of a pixel.

[0022] The error calculation module is used to perform batch analysis on multiple sets (30 sets in this embodiment) of acquired checkerboard images according to the mapping relationship to obtain statistically significant error values. Specifically, it performs statistical analysis on the imaging error values ​​in the X and Y directions of all 30 sets of checkerboard images. In this embodiment, the root mean square value (RMS_X) of the X-direction error (d1) and the root mean square value (RMS_Y) of the Y-direction error (e1) are calculated:

[0023]

[0024] Where N is the number of data sets, for example, 30.

[0025] Using RMS values ​​can effectively smooth out noise and fluctuations in a single measurement, resulting in a more reliable average distortion error.

[0026] The offset calculation module is used to map the abstract statistical error (RMS_X, RMS_Y) obtained by the error calculation module to the distortion center offset (COD X, COD Y) with clear physical meaning.

[0027] Specifically, the module retrieves the known physical parameters of the current test module from its built-in database or from an external database, and converts the statistical errors RMS_X and RMS_Y into physical offsets COD_X and COD_Y. The known physical parameters include pixel size (PixelSize, e.g., 0.8um), lens focal length (LengthE3, e.g., 3.5500mm), and projection or scaling factors in the X / Y directions (thx, thy, e.g., thx=3.5622, thy=3.1145).

[0028] The formula for calculating CODX is:

[0029] The formula for calculating CODX is:

[0030] An automatic judgment module is used to obtain the pre-entered control range of distortion center and offset, i.e., the pass / fail standard. It automatically compares the calculated distortion center offset with the preset control range and, based on the comparison result, automatically determines whether the camera module is a good or defective product. In this embodiment, the preset control range is ≤30 pixels.

[0031] This solution uses a motor in the hardware to drive a rotating platform, enabling a camera module fixed to a fixture to capture multiple checkerboard images from different angles. The software system uses these images to generate world coordinates using a 9-point calibration method, and further calculates the distortion center and offset (COD X and COD Y). This solves the problem of discrepancies between OC and COD in existing technologies, achieving accurate collection and determination of COD values ​​for high-pixel products.

[0032] This solution can also automatically compare the calculated COD value based on the entered distortion center and offset control range, and determine whether the product is good or defective, replacing manual judgment and improving the production efficiency of the testing process itself.

[0033] The above are merely embodiments of the present invention. The invention is not limited to the fields covered by these embodiments. Commonly known structures and characteristics in the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are able to access all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A system for testing distortion center offset of a camera module, comprising a mechanical structure part, wherein the mechanical structure part comprises a controllable rotating platform for carrying a jig having the camera module fixed thereon, and the controllable rotating platform is driven by a motor to realize multi-angle shooting of the camera module, characterized in that, Also included is a software system portion, comprising: a control module for controlling the controllable rotating platform to move to a plurality of preset angles and triggering the camera module to perform a photographing action; an image acquisition management module for controlling the camera module to capture a preset number of images from the plurality of preset angles and receiving image data; an image calibration module for analyzing checkerboard images in the preset number of images, establishing a mapping relationship between image pixel coordinates and three-dimensional world coordinates, and calculating distortion-related parameters including X-direction error and Y-direction error; an error solving module for statistically analyzing X-direction error d1 and Y-direction error e1 of multiple groups of checkerboard images to obtain root mean square value RMS_X of X-direction error and root mean square value RMS_Y of Y-direction error; an offset amount solving module for solving distortion center offset amount COD X, COD Y according to RMS_X and RMS_Y and preset known physical parameters. 2.The camera module distortion center offset test system of claim 1, wherein: The image calibration module is configured to automatically identify corner points in the checkerboard images using a 9-point calibration method, establish a mapping relationship between image pixel coordinates and three-dimensional world coordinates based on known calibration board physical dimensions and extracted corner point pixel coordinates, and calculate distortion-related parameters including corner point coordinates, distortion coefficients, and x-direction error and y-direction error. 3.The camera module distortion center offset test system of claim 2, wherein: The offset amount solving module calculates the root mean square value RMS_X of X-direction error d1 and the root mean square value RMS_Y of Y-direction error e1 according to the following formulas: ； ； where N is the number of data groups.

4. The camera module distortion center shift test system of claim 3, wherein: The offset amount solving module is configured to retrieve known physical parameters of the current test module, convert statistical errors RMS_X and RMS_Y into physical offset amounts COD X and COD Y, where the known physical parameters include pixel size, effective focal length or specific length, and X / Y direction projection or scaling coefficient.

5. The camera module distortion center shift test system of claim 4, wherein: The physical offset amount COD X is calculated according to the following formula: ； The physical offset amount COD X is calculated according to the following formula: ； wherein, is the pixel size; is the effective focal length or a certain length; thx, thyare the projection or scaling factors in X, Y directions, respectively.

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