Vehicle projection image correction method and system, vehicle and storage medium

Abstract

The invention provides a vehicle projection image correction method and system, a vehicle and a storage medium. The correction method for the vehicle projection image comprises the steps that a black and white chess calibration disc is projected in a projection area of the vehicle projection image, and the black and white chess calibration disc comprises a plurality of black grids and white grids which are distributed in the warp direction and the weft direction at intervals; collecting calibration data of the black lattices and the white lattices, and determining a distortion type of the black and white chess calibration disc according to the calibration data; determining a corresponding distortion correction parameter according to the distortion type; and correcting the vehicle projection image according to the distortion correction parameter. Through the arrangement, the geometric structure of the curved vehicle projection image can be corrected, so that the display effect of the vehicle projection image is better.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a correction method, system, vehicle and storage medium for a vehicle projection image. Background Art

[0002] When driving, users are unlikely to consider the interference of the ground undulations, road shoulders, and potholes around the vehicle on the vehicle projection image. When the vehicle projection related functions are enabled after parking, the uneven ground may interfere with the vehicle projection image, causing the geometric structure of the vehicle projection image to bend and become distorted. Summary of the invention

[0003] The present application provides a vehicle projection image correction method, system, vehicle and storage medium that can correct the geometric structure of a distorted vehicle projection image and improve the display effect of the vehicle projection image.

[0004] The present application provides a method for correcting a vehicle projection image, comprising:

[0005] In the projection area of ​​the vehicle projection image, a black-and-white chess calibration plate is projected, the black-and-white chess calibration plate comprising a plurality of black grids and white grids spaced apart in the longitudinal direction and the latitudinal direction respectively;

[0006] Collecting calibration data of the plurality of black squares and white squares, and determining the distortion type of the black and white chess calibration board according to the calibration data;

[0007] Determining corresponding distortion correction parameters according to the distortion type; and

[0008] The vehicle projection image is corrected according to the distortion correction parameters.

[0009] Optionally, collecting calibration data of the plurality of black squares and white squares, and determining the distortion type of the black and white chess calibration board according to the calibration data, includes:

[0010] Determining whether the edges of the white grid and the black grid are curved;

[0011] If it is detected that some of the edges of the white squares and the black squares are bent, it is determined that the distortion type of the black and white chess calibration plate is image distortion.

[0012] Optionally, after determining that the distortion type of the black and white chess calibration board is image distortion, the correction method further includes:

[0013] Detecting the bending directions of the edges of the white grid and the black grid;

[0014] If it is detected that the edges of the white squares and the black squares are concave from the edge of the black and white chess calibration plate to the center, it is determined that the distortion type of the black and white chess calibration plate is pincushion distortion;

[0015] If it is detected that the edges of the white squares and the black squares are convex from the center to the edge of the black and white chess calibration plate, it is determined that the distortion type of the black and white chess calibration plate is barrel distortion.

[0016] Optionally, after determining that the distortion type of the black and white chess calibration board is image distortion, determining corresponding distortion correction parameters according to the distortion type includes:

[0017] Obtaining four coordinate information of the four corners of the distorted white grid and the black grid;

[0018] Selecting three coordinate information from the four coordinate information, and determining the original center position information of the white grid and the black grid according to the selected three coordinate information;

[0019] According to the center position information, the distortion adjustment parameters corresponding to the distorted white grid and the black grid are determined by using a spatial point positioning method.

[0020] Optionally, if it is detected that the edges of all the white grids and the black grids are not bent, the correction method further includes:

[0021] Detecting the interval between two adjacent black grids and the white grids in the longitudinal direction and / or the latitudinal direction;

[0022] Determine whether the interval distance is equal to the interval distance threshold;

[0023] If the interval distance is not equal to the interval distance threshold, determining that the distortion type of the black and white chess calibration plate is trapezoidal distortion;

[0024] If the interval distance is equal to the interval distance threshold, it is determined that the black and white chess calibration board is not distorted.

[0025] Optionally, after determining that the distortion type of the black and white chess calibration board is trapezoidal distortion, determining corresponding distortion correction parameters according to the distortion type includes:

[0026] Mark the boundaries where the separation distance is not equal to the separation distance threshold;

[0027] Determine the area where the distance from the boundary to the interval is not equal to the interval distance threshold as the interval abnormal area, and cut the interval abnormal area;

[0028] Determine the centroid position information of the cut black and white chess calibration plate, and determine the projection area of ​​the vehicle projection image according to the centroid position information.

[0029] Optionally, after the vehicle projection image is corrected, the correction method further includes: adjusting the vehicle projection image to be displayed in a two-dimensional mode.

[0030] The present application also provides a computer-readable storage medium having a program stored thereon. When the program is executed by a processor, the method for correcting a vehicle projection image as described in any one of the above embodiments is implemented.

[0031] The present application also provides a vehicle projection image correction system, comprising: one or more processors, configured to implement the vehicle projection image correction method as described in any one of the above embodiments.

[0032] The present application also provides a vehicle, comprising: a vehicle projection image correction system as described in the above embodiments.

[0033] The vehicle projection image correction method, system, vehicle and storage medium of the embodiments of the present application. The vehicle projection image correction method projects a black and white chess calibration plate on the projection area, collects calibration data of multiple black and white squares of the black and white chess calibration plate, determines the distortion type of the black and white chess calibration plate according to the calibration data, and then determines the corresponding distortion correction parameters according to the distortion type, and finally corrects the vehicle projection image according to the distortion correction parameters. With such an arrangement, the geometric structure of the distorted vehicle projection image can be corrected, so that the display effect of the vehicle projection image is better. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 Shown is a flow chart of an embodiment of a method for correcting a vehicle projection image of the present application.

[0035] Figure 2 Shown Figure 1 A flow chart of another embodiment of a method for correcting a vehicle projection image is shown.

[0036] Figure 3 Shown Figure 1 A flow chart of yet another embodiment of a method for correcting a vehicle projection image is shown.

[0037] Figure 4 Shown is a functional block diagram of an embodiment of a vehicle projection image correction system of the present application. DETAILED DESCRIPTION

[0038] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0039] The terms used in this application are only for the purpose of describing specific embodiments and are not intended to limit this application. Unless otherwise defined, the technical terms or scientific terms used in this application should be understood by people with ordinary skills in the field to which this application belongs. The words "first", "second" and similar words used in the specification and claims of this application do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "one" or "one" do not indicate a quantitative limit, but indicate that there is at least one. "Multiple" or "several" means at least two. Unless otherwise specified, words such as "front", "rear", "lower" and / or "upper" are only for the convenience of explanation and are not limited to a position or a spatial orientation. Words such as "include" or "comprise" mean that the elements or objects appearing in front of "include" or "comprise" include the elements or objects listed after "include" or "comprise" and their equivalents, and do not exclude other elements or objects. Words such as "connect" or "connected" are not limited to physical or mechanical connections, and can include electrical connections, whether direct or indirect.

[0040] The singular forms "a", "said" and "the" used in this specification and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0041] The present application provides a correction method, system, vehicle and storage medium for a vehicle projection image. The correction method for a vehicle projection image includes: projecting a black and white chess calibration plate in the projection area of ​​the vehicle projection image, the black and white chess calibration plate including a plurality of black and white squares spaced apart in the longitudinal and latitudinal directions respectively; collecting calibration data of the plurality of black and white squares, and determining the distortion type of the black and white chess calibration plate according to the calibration data; determining corresponding distortion correction parameters according to the distortion type; and correcting the vehicle projection image according to the distortion correction parameters. With such a configuration, the geometric structure of the curved vehicle projection image can be corrected, so that the display effect of the vehicle projection image is better.

[0042] Figure 1 FIG. 1 is a flowchart showing a method for correcting a vehicle projection image according to an embodiment of the present invention. Figure 1 As shown, the vehicle projection image correction method is used to correct the geometric structure of the distorted vehicle projection image. A holographic grating module is provided in the vehicle, and the holographic grating module is used to project a vehicle projection image, which is displayed in a two-dimensional mode.

[0043] Figure 1 In the illustrated embodiment, the method for correcting a vehicle projection image includes steps S1 to S4.

[0044] in,

[0045] Step S1, projecting a black-and-white chess calibration plate in the projection area of ​​the vehicle projection image, the black-and-white chess calibration plate comprising a plurality of black and white grids spaced in the longitudinal and latitudinal directions, respectively. This embodiment utilizes a light source and a reference FOV (Field of View) parameter to project a black-and-white chess calibration grid in the projection area of ​​the vehicle projection image for illumination.

[0046] Step S2, collecting calibration data of multiple black and white squares, and determining the distortion type of the black and white chess calibration disk according to the calibration data. In this embodiment, a camera is used to obtain an image of the black and white chess calibration disk formed by projection in the projection area. The image of the black and white chess calibration disk includes calibration data of multiple black and white squares, and the calibration data can be the curvature of the edge of the black or white square or the spacing between two adjacent black and white squares. Different degrees of curvature or different spacing between two adjacent black and white squares will result in different distortion types of the black and white chess calibration disk. In order to ensure the randomness of image acquisition, a video stream should be acquired within a specific time period and then randomly framed as a calibration image for analysis.

[0047] Step S3: Determine the corresponding distortion correction parameter according to the distortion type. In this embodiment, different distortion types are determined, and different distortion correction parameters are determined. The distortion correction parameter can be a distortion adjustment parameter or a re-determined projection area.

[0048] Step S4, correcting the vehicle projection image according to the distortion correction parameters. In this embodiment, after the distortion correction parameters are determined, they are fed back to the holographic grating module, and the holographic grating module re-projects according to the determined distortion correction parameters to correct the distorted vehicle projection image, so as to adjust the vehicle projection image to be displayed in a two-dimensional mode.

[0049] The vehicle projection image correction method, system, vehicle and storage medium of the embodiments of the present application. The vehicle projection image correction method projects a black and white chess calibration plate on the projection area, collects calibration data of multiple black and white squares of the black and white chess calibration plate, determines the distortion type of the black and white chess calibration plate according to the calibration data, and then determines the corresponding distortion correction parameters according to the distortion type, and finally corrects the vehicle projection image according to the distortion correction parameters. With such an arrangement, the geometric structure of the distorted vehicle projection image can be corrected, so that the display effect of the vehicle projection image is better.

[0050] Figure 2 Shown Figure 1 A flow chart of another embodiment of a method for correcting a vehicle projection image is shown. Figure 1 to Figure 2 As shown, step S2 includes step S21. Wherein, step S21 includes step S211. Wherein,

[0051] Step S21, determine whether the edges of the white and black squares are curved. In this embodiment, the edges of the initial projected black and white chess calibration plate are straight in the longitudinal and latitude directions without bending or deformation. If the edges of the white and black squares are bent or deformed, it may be caused by uneven terrain. In this embodiment, a camera is used to obtain the edge contours of the white and black squares.

[0052] Step S211: If it is detected that the edges of some white and black squares are bent, it is determined that the distortion type of the black and white chess calibration plate is image distortion. In this embodiment, if it is detected that the edges of the black and white chess calibration plate are bent, it can be roughly determined that the distortion type of the black and white chess calibration plate is image distortion, and the image distortion may be caused by uneven terrain, resulting in deformation of the vehicle projection image.

[0053] With such a setting, the black and white chess calibration plate can be used as a reference calibration to accurately determine whether the vehicle projection image is distorted.

[0054] exist Figure 2 In the embodiment shown, after executing step S11, the calibration method further includes steps S212 to S14.

[0055] Step S212: Detect the bending directions of the edges of the white grid and the black grid. In this embodiment, the bending directions of the edges of the white grid and the black grid are acquired by using a camera.

[0056] Step S213: If it is detected that the edges of the white and black squares are concave from the edge of the black and white chess calibration plate to the center, the distortion type of the black and white chess calibration plate is determined to be pillow distortion. The pillow distortion of this embodiment is similar to a concave pillow.

[0057] Step S214: If it is detected that the edges of the white and black squares are convex from the center to the edge of the black and white chess calibration plate, the distortion type of the black and white chess calibration plate is determined to be barrel distortion. Barrel distortion is similar to a convex bucket, and is opposite to the concave and convex direction of pincushion distortion.

[0058] In this embodiment, if the distortion type of the black and white chess calibration plate is determined to be pincushion distortion or barrel distortion, the vehicle projection image may be distorted, and the image may lose accuracy and realism. The vehicle projection image with image distortion may cause dizziness or discomfort, which is visually uncomfortable. In this embodiment, by detecting the direction in which the edges of the white and black grids are bent, it can be preliminarily determined that the distortion type of the black and white chess calibration plate is pincushion distortion or barrel distortion. For different distortion types, the subsequent correction parameters are different.

[0059] exist Figure 2 In the embodiment shown, step S3 includes steps S31 to S33. Step S31 is performed after step S213 or step S214.

[0060] Step S31, obtaining four coordinate information of the four corners of the distorted white grid and the black grid. In this embodiment, the four coordinate information of the four corners of the distorted white grid and the black grid is obtained by using a camera.

[0061] Step S32: select three coordinate information from the four coordinate information, and determine the center position information of the original white grid and the black grid according to the selected three coordinate information.

[0062] Step S33: Determine the distortion adjustment parameters corresponding to the distorted white grid and the black grid using a spatial point positioning method according to the center position information.

[0063] In this embodiment, the distortion type of the black and white chess calibration board is pincushion distortion or barrel distortion. Regardless of pincushion distortion or barrel distortion, part of the coordinate information of the four coordinate information of the four corners of the corresponding white and black squares has deviated from the original coordinate information. By obtaining the four coordinate information of the four corners of the distorted white and black squares, the center position information corresponding to the distorted white and black squares is re-determined.

[0064] For example, three coordinate information including A, B, and C are selected from four coordinate information. Two coordinate information A and B located at opposite corners are selected from the three coordinate information A, B, and C, and the third coordinate information C is connected with two of the coordinate information A and B to form a triangle. The center point D of the two coordinate information A and B is determined, and the third coordinate information C is connected with the center point D, and intersects with the line connecting A and B at E in the vertical direction at the center point D, and E is determined as the center position information of the original white grid and the black grid. In this way, the central position information of the distorted white grid and the black grid is determined by using the triangulation positioning method, and then the B' and C' corresponding to the black grid or the white grid can be determined by using the determined B, C, and E, so as to restore the four coordinate information B, C, C', and B' of the four corners of the original white grid and the black grid. According to the spatial point positioning method, the four coordinate information of the four corners of the distorted white grid or the black grid is matched one by one with the four coordinate information of the four corners of the restored original white grid and the black grid, and the distortion adjustment parameters corresponding to the distorted white grid and the black grid are determined. The distortion adjustment parameter can be a coordinate deviation value. The coordinate deviation value is fed back to the holographic grating module, and the holographic grating module is fine-tuned according to the coordinate deviation value information to make the vehicle projection image undistorted. This embodiment uses the above correction method to correct the vehicle projection image with pincushion distortion or barrel distortion, so that the vehicle projection image is not distorted, more accurate and realistic, and avoids the feeling of dizziness or discomfort, and the viewing experience is comfortable.

[0065] exist Figure 2 In the embodiment shown, if it is detected that the edges of all white and black grids are not bent, it means that the image is not distorted. The correction method also includes steps S215 to S218. Step S215 is executed after step S21.

[0066] Step S215, detecting the distance between two adjacent black and white grids in the longitudinal direction and / or the latitudinal direction. In this embodiment, the distance between two adjacent black and white grids in the longitudinal direction and / or the latitudinal direction is obtained by using a camera. It is detected whether the distance between two adjacent black and white grids in the longitudinal direction and / or the latitudinal direction is equal to the distance between two adjacent black and white grids in the longitudinal direction and / or the latitudinal direction, so as to determine the distortion type.

[0067] Step S216, determine whether the interval distance is equal to the interval distance threshold. In this embodiment, if no distortion occurs, the interval distance is equal to the interval distance threshold. If other geometric distortions other than image distortion occur, the interval distance may be greater than or less than the detection distance threshold.

[0068] Step S217: If the interval distance is not equal to the interval distance threshold, determine that the distortion type of the black and white chess calibration board is trapezoidal distortion. In this embodiment, if it is determined that the interval distance is not equal to the interval distance threshold, it means that the interval distance is greater than or less than the interval distance threshold, indicating that the distortion type that occurs is trapezoidal distortion. When trapezoidal distortion occurs, some image content is compressed and some image content is stretched, making the display ratio of the image inconsistent.

[0069] Step S218: If the interval distance is equal to the interval distance threshold, it is determined that the black and white chess calibration board is not distorted. In this embodiment, if it is determined that the interval distance is equal to the interval distance threshold, it means that no distortion occurs at this time, and the display ratio of the projected vehicle projection image is appropriate at this time, and no correction is performed.

[0070] exist Figure 2 In the embodiment shown, step S3 includes steps S34 to S36. Step S34 is performed after step S217.

[0071] Step S34, marking the borders where the interval distance is not equal to the interval distance threshold. In this embodiment, when trapezoidal distortion occurs, the interval distance is not equal to the interval distance threshold. The adjacent borders where the interval distance is not equal to the interval distance threshold are marked to distinguish different display ratios.

[0072] Step S35, determine the area from which the distance from the boundary to the interval is not equal to the interval distance threshold as the interval abnormal area, and cut the interval abnormal area. In this embodiment, the proportion of the vehicle projection image displayed in the interval abnormal area is inconsistent. Cut the interval abnormal area to ensure that the retained area can display a normal proportion.

[0073] Step S36, determining the centroid position information of the cut black and white chess calibration plate, and determining the projection area of ​​the vehicle projection image according to the centroid position information. In this embodiment, the centroid position information of the black and white chess calibration plate is re-determined in the cut area to readjust the projection area, so as to avoid the abnormal interval area, and perform projection display in the adjusted projection area. At this time, the projection area is compressed or the projection display deviates from the abnormal interval area, so that the display ratio of the vehicle projection image is appropriate and the display effect is good.

[0074] In actual applications, in order to enhance interactivity, users usually use colored lights to increase the interactivity of lighting effects. At the same time, in order to enhance the color perception, more and more vehicles are equipped with colored laser light sources. The vehicle projector will pre-set the image quality mode when it is shipped. However, the difference in background color and projection distance in the actual use environment will cause the distortion of the viewing color, resulting in a poor viewing experience. If the color of the vehicle projection image is distorted or missing, even if the distortion of the vehicle projection image is corrected to make the display ratio of the vehicle projection image appropriate, the distortion of the viewing color caused by the difference in background color and projection distance in the actual use environment may also affect the display effect of the vehicle projection image, which may make the vehicle projection image incomplete and cause a poor viewing experience.

[0075] Therefore, the correction method of the present application can not only correct the structure of the distorted vehicle projection image, but also correct the color of the vehicle projection image. By correcting the structure and color of the vehicle projection image, it can ensure that the display ratio of the vehicle projection image is appropriate, and it can also ensure that the color of the vehicle projection image is saturated and not distorted under different background colors, so that the display effect of the vehicle projection image is better, and the viewing experience and user experience are improved.

[0076] Figure 3 Shown Figure 1 A flowchart of another embodiment of a method for correcting a vehicle projection image is shown. Figure 3 In the embodiment shown, the vehicle projection image correction method is used to correct the color of the vehicle projection image. Specifically, it includes steps S4 to S8.

[0077] Step S4, irradiate the projection area of ​​the vehicle projection image with pure white light. In the present embodiment, a light source is provided in the vehicle, and the light source is used to emit pure white light to irradiate the projection area, so as to facilitate the acquisition of the background color of the projection area. In the present embodiment, the projection area is irradiated with Lab color gamut pure white light. Step S5, obtain the background color of the projection area and the vehicle projection image. In the present embodiment, the vehicle projection image is a two-dimensional pattern image, and the vehicle projection image is projected onto the ground. A camera is provided in the vehicle, and the camera is used to capture the background color of the projection area and the vehicle projection image. In the present embodiment, the vehicle projection image is projected onto the ground, and the background color of the projection area captured by the camera is the color of the ground.

[0078] Step S6, grayscale the vehicle projection image to determine the bright area and dark area of ​​the image in the vehicle projection image. Since the vehicle projection image is in color, grayscale processing is helpful to distinguish the bright area and dark area of ​​the image. In this embodiment, the color image of the vehicle projection image is converted into a matrix of RGB three components. Then, for each pixel point, according to its value in the three RGB components, its grayscale value is calculated according to the specified weight, so that the calculated grayscale is closer to the visual perception of the human eye. The grayscale image finally obtained is an image containing only one grayscale channel, in which the value of each pixel point represents the grayscale value of the point. Then, according to the grayscale of the vehicle projection image, the bright area and dark area of ​​the image in the vehicle projection image are screened out.

[0079] Step S7, extracting the brightest point with the largest grayscale value from the bright area of ​​the image, and extracting the darkest point with the smallest grayscale value from the dark area of ​​the image, and determining the colors complementary to the background color at the brightest point and the darkest point as compensation colors. Since overexposure points and overdark points are prone to appear at the brightest point in the bright area of ​​the image and the darkest point in the dark area of ​​the image, when overexposure points and overdark points appear, noise points are prone to appear, resulting in image distortion. In this embodiment, in order to avoid the appearance of noise points, compensation colors are determined at the brightest point and the darkest point for compensation. In this embodiment, the RGB color gamut space of the brightest point and the darkest point is converted into the Lab color gamut space, and at least two Lab coordinates of the brightest point and the darkest point in the coordinate system of the Lab color gamut space are obtained respectively. After extracting the maximum grayscale value and the minimum grayscale value for the bright area and the dark area of ​​the image respectively, the color gamut data of the feature point is substituted into the Lab color gamut space for dotting to obtain the coordinates in the Lab coordinate system. Then, according to at least two Lab coordinates of the brightest point and the darkest point in the coordinate system of the Lab color gamut space, the key coordinates of the brightest point and the darkest point are respectively screened out. Finally, the color of the key coordinates of the brightest point and the darkest point is determined as the compensation color, and the compensation color is a complementary color to the background color. In this embodiment, the colors of at least two selected key coordinates are used as the color values ​​of the image filter. In this way, the vehicle projection image is integrated with the background color when projected to the projection area to display the original color of the vehicle projection image. In this way, the color correction of the vehicle projection image can be achieved, ensuring that the color of the vehicle projection image is saturated and not distorted under different background colors, with strong adaptability, and improving the viewing experience and user experience.

[0080] Step S8, adjusting the colors of the bright and dark areas of the vehicle projection image according to the compensation color, so that the vehicle projection image is integrated with the background color when projected to the projection area, so as to display the original color of the vehicle projection image. In this way, the color of the bright and dark areas of the vehicle projection image is compensated by the compensation color, noise points are avoided, and the vehicle projection image is integrated with the background color when projected to the projection area, so as to display the original color of the vehicle projection image. In this way, the color correction of the vehicle projection image can be achieved, ensuring that the color of the vehicle projection image is saturated and not distorted under different background colors, thereby improving the viewing experience and user experience.

[0081] In the above scheme, the correction method of this embodiment can not only correct the distorted geometric structure of the vehicle projection image, but also correct the color of the vehicle projection image. By correcting the color and geometric structure of the vehicle projection image, it can ensure that the display ratio of the vehicle projection image is appropriate, and it can also ensure that the color of the vehicle projection image is saturated and not distorted under different background colors, so that the display effect of the vehicle projection image is better, and the viewing experience and user experience are improved.

[0082] The present application also provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the above Figures 1 to 3 The correction method of the vehicle projection image shown in the embodiment. In some embodiments, the computer-readable storage medium may be an internal storage unit of the aforementioned vehicle, such as a hard disk or a memory. The computer-readable storage medium may also be an external storage device of the vehicle, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), an SD card, a flash card (Flash Card), etc. equipped on the device. Furthermore, the computer-readable storage medium may also include both the internal storage unit of the vehicle and an external storage device. The computer-readable storage medium is used to store computer programs and other programs and data required for the vehicle, and may also be used to temporarily store data that has been output or is to be output. From a hardware perspective, such as Figure 4 As shown, it is a hardware structure diagram of the vehicle in which the processor of the present application is located, except Figure 4 In addition to the processor, memory, network interface, and non-volatile memory shown, the vehicle in which the adjustment system is located in the embodiment may also include other hardware according to the actual functions of the vehicle, which will not be described in detail.

[0083] The present application also provides a vehicle projection image correction system, comprising: one or more processors, for implementing a vehicle projection image correction method such as any one of the above-mentioned embodiments. For the system embodiment, it basically corresponds to the method embodiment, so the relevant parts can refer to the partial description of the method embodiment. The system embodiment described above is merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without creative work.

[0084] The vehicle includes a vehicle projection image correction system. The vehicle uses the vehicle projection image correction system to achieve Figures 1 to 3 The correction method of the vehicle projection image described in any one of the above. The present application uses a holographic grating module to record the spatial position characteristics of the corresponding target in the holographic grating module during the exposure process. During the projection process, the holographic grating module is illuminated by a light source, and the virtual image of the original target can be effectively seen. The vehicle's own sensors, cameras, millimeter-wave radars, etc. are combined to collect the surrounding environment of the vehicle and the vehicle's own state, and a light control system is formed through an optical modulation module and a light source module of the vehicle body. After autonomous detection of the external environment of the vehicle, the appropriate mode (distance, brightness) is adaptively selected for projection. In this embodiment, a black and white chess calibration plate is projected in the projection area, and calibration data of multiple black and white squares of the black and white chess calibration plate are collected. The distortion type of the black and white chess calibration plate is determined according to the calibration data, and then the corresponding distortion correction parameters are determined according to the distortion type. Finally, the vehicle projection image is corrected according to the distortion correction parameters. With such a setting, the geometric structure of the distorted vehicle projection image can be corrected, so that the display effect of the vehicle projection image is better. The correction method of the present application can not only correct the geometric structure of the distorted vehicle projection image, but also correct the color of the vehicle projection image. By correcting the color and geometric structure of the vehicle projection image, it is ensured that the structure of the distorted vehicle projection image is corrected. When the display ratio of the vehicle projection image is appropriate, it can also ensure that the color of the vehicle projection image is saturated and not distorted under different background colors, so that the display effect of the vehicle projection image is better, and the viewing experience and user experience are improved.

[0085] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for correcting a vehicle projection image, characterized in that: include: In the projection area of ​​the vehicle projection image, a black-and-white chess calibration plate is projected, the black-and-white chess calibration plate comprising a plurality of black grids and white grids spaced apart in the longitudinal direction and the latitudinal direction respectively; Collecting calibration data of the plurality of black squares and white squares, and determining the distortion type of the black and white chess calibration board according to the calibration data; Determining corresponding distortion correction parameters according to the distortion type; and The vehicle projection image is corrected according to the distortion correction parameters.

2. The calibration method according to claim 1, characterized in that: The collecting the calibration data of the plurality of black squares and white squares, and determining the distortion type of the black and white chess calibration board according to the calibration data, comprises: Determining whether the edges of the white grid and the black grid are curved; If it is detected that some of the edges of the white squares and the black squares are bent, it is determined that the distortion type of the black and white chess calibration plate is image distortion.

3. The calibration method according to claim 2, characterized in that: After determining that the distortion type of the black and white chess calibration board is image distortion, the correction method further includes: Detecting the bending directions of the edges of the white grid and the black grid; If it is detected that the edges of the white squares and the black squares are concave from the edge of the black and white chess calibration plate to the center, it is determined that the distortion type of the black and white chess calibration plate is pincushion distortion; If it is detected that the edges of the white squares and the black squares are convex from the center to the edge of the black and white chess calibration plate, it is determined that the distortion type of the black and white chess calibration plate is barrel distortion.

4. The calibration method according to claim 3, characterized in that: The determining, according to the distortion type, corresponding distortion correction parameters includes: Obtaining four coordinate information of the four corners of the distorted white grid and the black grid; Selecting three coordinate information from the four coordinate information, and determining the original center position information of the white grid and the black grid according to the selected three coordinate information; According to the center position information, the distortion adjustment parameters corresponding to the distorted white grid and the black grid are determined by using a spatial point positioning method.

5. The calibration method according to claim 2, characterized in that: If it is detected that the edges of all the white grids and the black grids are not bent, the correction method further includes: Detecting the interval between two adjacent black grids and the white grids in the longitudinal direction and / or the latitudinal direction; Determine whether the interval distance is equal to the interval distance threshold; If the interval distance is not equal to the interval distance threshold, determining that the distortion type of the black and white chess calibration plate is trapezoidal distortion; If the interval distance is equal to the interval distance threshold, it is determined that the black and white chess calibration board is not distorted.

6. The calibration method according to claim 5, characterized in that: The determining, according to the distortion type, corresponding distortion correction parameters includes: Mark the boundaries where the separation distance is not equal to the separation distance threshold; Determine the area where the distance from the boundary to the interval is not equal to the interval distance threshold as the interval abnormal area, and cut the interval abnormal area; Determine the centroid position information of the cut black and white chess calibration plate, and determine the projection area of ​​the vehicle projection image according to the centroid position information.

7. The calibration method according to claim 1, characterized in that: After the vehicle projection image is corrected, the correction method further includes: adjusting the vehicle projection image to be displayed in a two-dimensional mode.

8. A computer-readable storage medium, characterized in that: A program is stored thereon, and when the program is executed by a processor, the method for correcting a vehicle projection image as claimed in any one of claims 1 to 7 is implemented.

9. A vehicle projection image correction system, characterized in that: include: One or more processors, used to implement the vehicle projection image correction method as described in any one of claims 1 to 7.

10. A vehicle, characterized in that: include: The vehicle projection image correction system as claimed in claim 9.

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