A method for detecting eccentricity of a camera

Abstract

The application discloses a camera eccentricity detection method, comprising the following steps: fixing the camera at a preset position and keeping a reference object at an initial position, wherein the camera is located at the center point of the reference object and faces a fixed mirror; lighting the camera by using a capture card and taking a screenshot of the display picture of the camera by using a computer to obtain a first screenshot; rotating the reference object at least once, taking a screenshot of the display picture of the camera by using the computer after each rotation to obtain a second screenshot, the first screenshot and the second screenshot corresponding to the same area on the mirror, and the area containing the imaging of the reference object in the mirror; aligning the first screenshot and all the second screenshots, and calculating the coincidence degree of the center point of the reference object in all the screenshots; and if the coincidence degree is less than a first threshold value, the camera has eccentricity. The application has the advantages of simple operation and high test efficiency.

Description

Technical Field

[0001] This application relates to the field of equipment testing technology, and more specifically, to a method for detecting the eccentricity of a camera. Background Technology

[0002] Currently, in-vehicle cameras are widely used, providing real-time video and audio data and offering more scientific data for traffic information. 360° panoramic technology from in-vehicle cameras helps customers view the area around their vehicle. Camera resolution, dynamic range, color saturation, and eccentricity are among the key indicators for evaluating cameras, with eccentricity, as an inherent property of cameras, having a more direct impact on image quality.

[0003] Existing vehicle-mounted cameras use a wide-angle testing system. The system's acquisition card illuminates the camera, and the transmissive image card is adjusted to maintain a 45° angle aligned with the camera, ensuring the camera is centered. Power and computer equipment are connected, and the software is launched to perform an off-center test.

[0004] Because the illumination of the wide-angle device needs to be changed multiple times during the test, each change requires 10 minutes of stabilization time before the image is captured again. Connecting to the computer and adjusting the camera position multiple times takes a relatively long time, and keeping the light source on for extended periods will also reduce the lifespan of the device.

[0005] In summary, existing wide-angle testing systems are complex to operate and have low testing efficiency. Summary of the Invention

[0006] This application provides a method for detecting camera eccentricity. By maintaining the relative distance between the camera and the mirror, keeping the camera at the center point of the reference object, and maintaining the camera's shooting angle, the method obtains image screenshots of the reference object in various poses through the mirror. By aligning the screenshots, it is determined whether the center point of the reference object in different screenshots coincides, thereby determining whether the camera is eccentric. The method is simple to operate and has high testing efficiency.

[0007] This application provides a method for detecting camera eccentricity, including:

[0008] Fix the camera in a preset position and keep the reference object in its initial position, wherein the camera is located at the center point of the reference object and faces the fixed mirror, and the reference object and the camera's shooting light do not interfere with each other;

[0009] The camera is turned on using a capture card, and the first screenshot is obtained by taking a screenshot of the camera's display using a computer.

[0010] Keeping the camera's shooting angle unchanged, rotate the reference object at least once while keeping the camera at the center point of the reference object. After each rotation, take a screenshot of the camera's display screen using a computer to obtain a second screenshot. The first and second screenshots correspond to the same area on the mirror surface, and the area contains the image of the reference object in the mirror surface.

[0011] After aligning the first screenshot with all the second screenshots, calculate the overlap of the center points of the reference objects in all screenshots;

[0012] If the overlap is less than the first threshold, then the camera is off-center.

[0013] Preferably, the camera is fixed on the gimbal at the top of the tripod.

[0014] Preferably, the reference object is a cuboid with open sides.

[0015] Preferably, the bottom surface of the reference object is provided with multiple casters, which are located on the horizontal platform.

[0016] Preferably, the eccentricity detection method further includes:

[0017] Obtain multiple screenshot combinations, each screenshot combination including a first screenshot and at least one second screenshot;

[0018] Calculate the overlap of each screenshot combination;

[0019] The overlap of all screenshots is used to determine if the camera is off-center.

[0020] Preferably, the overlap of all screenshot combinations is used to determine whether the camera is off-center, specifically including:

[0021] Calculate the mean, variance, or standard deviation of the overlap of all screenshot combinations. If the mean, variance, or standard deviation is less than the second threshold, then the camera is skewed.

[0022] Preferably, the mirror is a square mirror.

[0023] Preferably, the edges of the first and second screenshots coincide with the edge of the mirror.

[0024] Preferably, the camera is positioned directly opposite the center point of the mirror.

[0025] Other features and advantages of this application will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0026] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of the present application and, together with their description, serve to explain the principles of the present application.

[0027] Figure 1 A flowchart of the camera eccentricity detection method provided in this application;

[0028] Figure 2 This is a schematic diagram of the eccentricity detection device provided in this application. Detailed Implementation

[0029] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0030] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0031] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the specification.

[0032] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0033] This application provides a method for detecting camera eccentricity. By maintaining the relative distance between the camera and the mirror, keeping the camera at the center point of the reference object, and maintaining the camera's shooting angle, the method obtains image screenshots of the reference object in various poses through the mirror. By aligning the screenshots, it is determined whether the center point of the reference object in different screenshots coincides, thereby determining whether the camera is eccentric. The method is simple to operate and has high testing efficiency.

[0034] like Figure 1 As shown, the camera eccentricity detection method provided in this application includes:

[0035] S110: Fix the camera in a preset position and keep the reference object in its initial position, wherein the camera is located at the center point of the reference object and faces the fixed mirror, and the reference object and the camera's shooting light do not interfere with each other.

[0036] As an example, such as Figure 2 As shown, the camera 100 is fixed on the gimbal 500 at the top of the tripod 400, and the tripod 400 and the gimbal 500 are used to support and fix the camera.

[0037] As an example, such as Figure 2 As shown, reference object 200 is a cuboid with four open sides.

[0038] As an example, such as Figure 2 As shown, reference object 200 is placed on horizontal platform 600, and horizontal platform 600 supports reference object.

[0039] Preferably, the bottom surface of the reference object 200 is provided with multiple casters, which are located on the horizontal platform 600. The casters reduce the difficulty of rotating the reference object 200.

[0040] S120: Use the capture card to turn on the camera 100, and use the computer to take a screenshot of the camera's display screen to obtain the first screenshot.

[0041] S130: Keeping the shooting angle of the camera 100 unchanged, the camera 100 is kept at the center point of the reference object 200 and rotated at least once. After each rotation, the computer is used to take a screenshot of the display screen of the camera 100 to obtain a second screenshot. The first screenshot and the second screenshot correspond to the same area on the mirror surface, and the area contains the image of the reference object in the mirror surface 300.

[0042] Preferably, the rotation is performed more than three times, thereby obtaining at least three second screenshots. Analyzing the overlap of the four screenshots (see S140) can improve the accuracy of the judgment.

[0043] S140: After aligning the first screenshot with all the second screenshots, calculate the overlap of the center points of the reference objects in all screenshots.

[0044] It should be noted that during the rotation of reference object 200, the distance between mirror 300 and camera 100 remains unchanged. Therefore, the displayed image size of camera 100 is the same, and thus the first and second screenshots are the same size. The alignment of the two screenshots refers to the alignment of their edges. Based on this, theoretically, the center points of the reference object in the screenshots should coincide. If the center points of the reference object in different screenshots do not coincide, it indicates that the camera is off-center.

[0045] Preferably, the mirror 300 is a square mirror, and the edges of the screenshots (first screenshot and second screenshot) coincide with the edges of the mirror, which helps to accurately determine the screenshot area in the image displayed by the camera and ensures that the corresponding areas of the first screenshot and the second screenshot are consistent.

[0046] Based on this, preferably, the camera 100 is directly facing the center point of the mirror 300. Therefore, theoretically, the center point of the reference object coincides with the center point of the screenshot, which is more conducive to calculating the degree of overlap.

[0047] As an example, one screenshot (e.g., the first screenshot) can be used as the base screenshot. The distance between the center point of the reference object in the other screenshots and the center point of the reference object in the base screenshot can be calculated. If the distance is less than a preset value, the center points of the two reference objects coincide; otherwise, the center points of the two reference objects do not coincide. Then, the percentage of overlapping screenshots out of the total number of screenshots is calculated as the degree of overlap.

[0048] As another embodiment, one screenshot (e.g., the first screenshot) can be used as the reference screenshot. A circle is drawn with the center point of a reference object in the reference screenshot as the center and a preset value as the radius. If the center points of reference objects in other screenshots are located inside the circle, then the center point of the reference object in the new screenshot coincides with the center point of the reference object in the reference screenshot; otherwise, the center points of the reference objects in the new screenshot do not coincide with the center point of the reference object in the reference screenshot. The percentage of overlapping screenshots out of the total number of screenshots is then calculated as the degree of overlap.

[0049] S150: Determine if the overlap is less than the first threshold. If yes, proceed to S160; otherwise, proceed to S170.

[0050] S160: The camera is determined to be off-center.

[0051] S170: The camera is determined to be unbiased.

[0052] Based on the above, to further improve the accuracy of detection, preferably, multiple screenshot combinations are obtained according to steps S110-S130, each screenshot combination including a first screenshot and at least one second screenshot. Then, the overlap ratio of each screenshot combination is calculated according to step S140. Subsequently, the overlap ratio of all screenshot combinations is used to determine whether the camera is off-center.

[0053] Specifically, the overlap of all screenshot combinations is used to determine whether the camera is skewed. This can be achieved by calculating the mean, variance, or standard deviation of the overlap of all screenshot combinations. If the mean, variance, or standard deviation is less than a second threshold, then the camera is skewed.

[0054] While specific embodiments of this application have been described in detail by way of examples, those skilled in the art should understand that the above examples are for illustrative purposes only and are not intended to limit the scope of this application. Those skilled in the art should understand that modifications can be made to the above embodiments without departing from the scope and spirit of this application. The scope of this application is defined by the appended claims.

Claims

1. A method for detecting the eccentricity of a camera, characterized in that, include: The camera is fixed in a preset position, and the reference object is kept in its initial position, wherein the camera is located at the center point of the reference object and faces the fixed mirror surface, and the reference object does not interfere with the shooting light of the camera; The camera is turned on using a capture card, and the first screenshot is obtained by taking a screenshot of the camera's display using a computer. Keeping the camera's shooting angle unchanged, the camera is kept at the center point of the reference object and rotated at least once. After each rotation, the computer is used to take a screenshot of the camera's display screen to obtain a second screenshot. The first screenshot and the second screenshot correspond to the same area on the mirror surface, and the area contains the image of the reference object on the mirror surface. After aligning the first screenshot with all the second screenshots, calculate the overlap of the center points of the reference objects in all screenshots; If the overlap is less than the first threshold, then the camera is off-center.

2. The camera eccentricity detection method according to claim 1, characterized in that, The camera is fixed to the gimbal at the top of the tripod.

3. The camera eccentricity detection method according to claim 1, characterized in that, The reference object is a cuboid with four open sides.

4. The camera eccentricity detection method according to claim 1, characterized in that, The bottom surface of the reference object is provided with multiple casters, which are located on the horizontal platform.

5. The camera eccentricity detection method according to claim 1, characterized in that, Also includes: Obtain multiple screenshot combinations, each combination including a first screenshot and at least one second screenshot; Calculate the overlap of each screenshot combination; The overlap of all screenshot combinations is used to determine whether the camera is eccentric.

6. The camera eccentricity detection method according to claim 5, characterized in that, Determining whether the camera is off-center by using the overlap of all screenshot combinations specifically includes: Calculate the mean, variance, or standard deviation of the overlap of all screenshot combinations. If the mean, variance, or standard deviation is less than a second threshold, then the camera is eccentric.

7. The camera eccentricity detection method according to claim 1, characterized in that, The mirror is a square mirror.

8. The camera eccentricity detection method according to claim 7, characterized in that, The edges of the first and second screenshots coincide with the edge of the mirror.

9. The method for detecting camera eccentricity according to claim 7 or 8, characterized in that, The camera is positioned directly opposite the center point of the mirror.

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