A distortion calibration method for AR-HUD based on light emitting area

Abstract

The present invention discloses an AR-HUD distortion calibration method based on a light-emitting area. The method comprises the following steps: projecting one or more images that can display a dot matrix and an edge of a light-emitting area, using a viewpoint camera to collect images projected by the AR-HUD, detecting dot matrix and a light-emitting area or an edge of a light-emitting area required for calibration in the collected images, finding dot matrixes with a clear corresponding relationship with a projection original image on the light-emitting area, calculating a homography relationship using the determined correspondence, calculating the corresponding dot matrix of the sample dot matrix on the projection original image using the relationship, calculating a pre-distortion variable at the dot matrix according to the difference between the dot matrices, and further obtaining pre-distortion parameters using an interpolation or fitting method. The light-emitting area of ​​the AR-HUD can be effectively utilized, and compared with the prior art, the size of the field of view angle can be significantly improved, a larger size or richer information display can be provided, and the visual experience of the driver can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of image processing, and in particular relates to an AR-HUD distortion calibration method based on a light emitting area. Background Art

[0002] In the prior art, similar Figure 2 The dot matrix image with a black background is used to calibrate the AR-HUD distortion, but due to Figure 2 The background is black. In the AR-HUD calibration scenario where there is no ambient light or the ambient light is dim, the image captured by the viewpoint camera cannot effectively distinguish the actual light-emitting area of ​​the AR-HUD from the ambient light area. Therefore, the distortion-free virtual image can only be found within the envelope determined by the outermost points of the sample dot matrix, which limits the size of the FOV that can be obtained. Obviously, the actual light-emitting area of ​​the AR-HUD includes the sample dot matrix and the area determined by it. If distortion calibration can be performed in the actual light-emitting area, a larger FOV can be obtained.

[0003] For example, patent documents CN107527324B, CN115205138A, etc. place the physical calibration device at the target position in front of the vehicle, then control the viewpoint camera to capture the image and regard the dot matrix in the image as the reference dot matrix for subsequent calibration parameter calculations. However, the AR-HUD device has problems such as material uniformity, device installation tolerance, and windshield free-form surface. This will lead to different AR-HUDs or AR-HUDs on different vehicles having different degrees of differences in the sample dot matrix obtained during calibration and the area determined by its outermost points. If the edge of the area determined by the outermost points of the sample dot matrix is ​​inside the area determined by the outermost points of the reference dot matrix, it will cause the display content to be missing after de-distortion. In order to prevent such missing content, it is necessary to design a smaller reference dot matrix area, that is, to make certain sacrifices in the FOV after de-distortion. Figure 7 For example, the dotted rectangle in the figure is the area determined by the outermost points of the reference dot matrix, and the solid curve is the area determined by the outermost points of the sample dot matrix. In order to effectively calibrate each AR-HUD, it is necessary to ensure that Figure 7 The solid curve frame is always outside the dotted rectangular frame. At this time, it is necessary to appropriately reduce the overall size of the reference dot matrix (i.e., reduce the dotted rectangular frame). After dedistortion using a solution similar to CN107527324B and CN115205138A, the virtual image is compressed from the area determined by the solid curve frame before calibration to the dotted rectangular frame, which objectively reduces the FOV.

[0004] For example, the strategy for obtaining the reference dot matrix in CN115546057A is to find the largest inscribed rectangle in the area determined by the outermost dot matrix of the sample dot matrix, and determine the reference dot matrix within the largest inscribed rectangle. Figure 8 As shown, the solid curve frame is the area determined by the outermost points of the sample dot matrix, and the dotted rectangular frame is the largest inscribed rectangle of the solid dotted frame, and is also the boundary of the area determined by the outermost points of the reference dot matrix. After calibration, the display area of ​​the virtual image is reduced from the solid curve frame to the dotted rectangular frame, which can ensure that the dotted rectangular frame is always within the solid curve frame, thereby ensuring the integrity of the displayed content. In CN115546057A, the reference dot matrix is ​​determined in real time based on the sample dot matrix of the current AR-HUD. Compared with CN107527324B and CN115205138A, there is no need to reserve a tolerance area between the edges of the virtual image area before and after de-distortion. Therefore, CN115546057A can usually obtain a larger FOV.

[0005] Although CN115546057A can obtain a relatively larger FOV, it uses a similar Figure 2 The original projection image with a black background, therefore, its FOV is determined within the area determined by the outermost points of the sample lattice. The actual undistorted virtual image that can be displayed obviously includes the sample lattice and the area determined by the sample lattice. Therefore, theoretically, a larger FOV can be obtained by obtaining the undistorted virtual image in the entire undistorted virtual image area (i.e., the actual light emitting area of ​​the AR-HUD).

[0006] like Figure 6 As shown, the image is generated by the PGU, and then its light is controlled by multiple hardwares, and finally an image is formed in front of the car. In this process, the position of the PGU, the uniformity of the light control hardware, the installation position, etc. may have different avoidable errors. These errors will eventually affect the overall light output of the AR-HUD, that is, the size of the actual display area of ​​the virtual image. In order to ensure that each AR-HUD displays complete (undedistorted) content in front of the car, it is necessary to take the above errors into account when the PGU generates the image. Specifically, Fig. 9 As shown, the content to be displayed is compressed into the solid rectangular frame, and the part outside the solid rectangular frame is used as a tolerance area and no specific content is displayed.

[0007] However, the area where AR-HUD can emit light is larger than Fig. 9 The solid line rectangular area shown in FIG. 1 and the boundary of the actual light exit area are on the tolerance area. If the dedistorted virtual image can be determined on the actual light exit area, a larger FOV than that of CN115546057A can be obtained. Summary of the invention

[0008] The purpose of the present invention is to provide an AR-HUD distortion calibration method based on the light emitting area, so as to solve the problem that the FOV size after AR-HUD distortion calibration is limited due to the failure to utilize the actual light emitting area of ​​the AR-HUD in the prior art proposed in the above background technology.

[0009] To achieve the above object, the present invention adopts the following technical solution: an AR-HUD distortion calibration method based on a light emitting area, the method comprising the following steps:

[0010] (a) projecting one or more images of the dot matrix and the edge of the light-emitting area; (b) using a viewpoint camera to capture the image projected by the AR-HUD; (c) detecting the dot matrix and the light-emitting area or the edge of the light-emitting area required for calibration in the captured image; (d) finding the dot matrix on the light-emitting area that has a clear correspondence with the original projection image; (e) using the correspondence determined in step (d) to calculate the homography relationship, and using the relationship to calculate the corresponding dot matrix of the sample dot matrix on the original projection image; (f) calculating the pre-distortion variable at the dot matrix based on the difference between the dot matrices in step (e), and further using interpolation or fitting methods to obtain the pre-distortion parameters.

[0011] Preferably, the image projected in step (a) includes a pure color image and an image including a dot matrix pattern, or only includes a dot matrix image that can clearly display the edge in the tolerance area. The pure color image or the dot matrix image that can display the edge will be used to extract the edge of the actual light emitting area, and the dot matrix image will be used to detect the dot matrix.

[0012] Preferably, the process of detecting the light emitting area or the edge of the light emitting area in step (c) includes:

[0013] The envelope determined by the outermost points of the sample lattice is obtained, and the edge of the light area is detected with the help of the Canny operator of OpenCV. At the same time, the edge is filtered in combination with the envelope information.

[0014] Preferably, the process of determining the dot matrix on the light-emitting area in step (d) includes: (d1) determining the virtual image area after de-distortion; (d2) determining the radius of the circular spot in the display area on the original projection image and its ratio information to the length and width of the display area; (d3) leaving a margin in equal proportion between the dot matrix and the boundary of the virtual image area to form Region1; (d4) finding the required dot matrix on the virtual image area after removing Region1.

[0015] Preferably, the margin reserved in step (d3) is determined based on the ratio information of the area formed by the envelope formed by the outermost points of the projection dot matrix and the edge of the display content area on the display content area.

[0016] Preferably, the process of calculating the homography relationship in step (e) includes converting the sample dot matrix to the projection original image by means of the homography relationship between the reference dot matrix and the projection dot matrix.

[0017] Preferably, in step (f), a bicubic spline interpolation method is used to calculate the pre-distortion variable of any point on the projection original image.

[0018] Preferably, the method further comprises presetting a target position, which is the position of the reference dot matrix, to ensure that there is sufficient overlap between the area determined by the reference dot matrix and the virtual image area.

[0019] Preferably, in step (c), the findCirclesGrid function of OpenCV is used to detect the sample dot matrix, and the boundary of the light emitting area is determined by the envelope determined by the outermost points of the dot matrix.

[0020] Preferably, the pre-distortion parameters calculated in step (f) are applied to the projected original image to generate a pre-distorted image, thereby reducing or eliminating the distortion of the AR-HUD during the final display.

[0021] Technical effects and advantages of the present invention: Compared with the prior art, the AR-HUD distortion calibration method based on the light-emitting area proposed in the present invention has the following advantages:

[0022] The present invention projects one or more images of a display dot matrix and an edge of a light-emitting area, uses a viewpoint camera to collect images projected by the AR-HUD, detects the dot matrix and the light-emitting area or the edge of the light-emitting area required for calibration in the collected image, finds the dot matrix with a clear corresponding relationship with the original projection image on the light-emitting area, calculates the homography relationship using the determined correspondence, and uses the relationship to calculate the corresponding dot matrix of the sample dot matrix on the original projection image, calculates the pre-distortion variable at the dot matrix according to the difference between the dot matrices, and further uses an interpolation or fitting method to obtain the pre-distortion parameter; the light-emitting area of ​​the AR-HUD can be effectively utilized, and compared with the prior art, the size of the field of view can be significantly improved, a larger size or richer information display can be provided, and the driver's visual experience is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Schematic diagram of AR-HUD system;

[0024] Figure 2 This is an example of the original projection image;

[0025] Figure 3 This is an example of a dot matrix under the viewpoint camera;

[0026] Figure 4 This is an example diagram of the pre-distortion variable;

[0027] Figure 5 It is a schematic diagram of the field of view;

[0028] Figure 6 This is an example diagram of the AR-HUD optical path;

[0029] Figure 7 A schematic diagram of one of the areas determined by the sample dot matrix and the reference dot matrix;

[0030] Figure 8 A second schematic diagram of the area determined by the sample dot matrix and the reference dot matrix;

[0031] Fig. 9 One of the images generated by PGU;

[0032] Fig.10 The second image generated for PGU;

[0033] Fig.11 The image captured by the camera;

[0034] Fig.12 Schematic diagram of edge detection of the light-emitting area;

[0035] Fig.13 A schematic diagram for finding the dot matrix on the light-emitting area;

[0036] Fig.14 The figure is a flow chart of the AR-HUD distortion calibration method based on the light emitting area of ​​the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0038] The present invention provides an AR-HUD distortion calibration method based on the light emitting area, such as Fig.14 As shown, the method comprises the following steps:

[0039] (a) projecting one or more images showing the dot matrix and the edge of the light-emitting area;

[0040] Furthermore, the projected image includes a pure color image and an image containing a dot matrix pattern, or only contains a dot matrix image that can clearly display the edge in the tolerance area. Among them, the pure color image or the dot matrix image that can display the edge will be used to obtain the actual light emitting area or its edge of the AR-HUD, and the dot matrix image will be used to detect the dot matrix.

[0041] (b) Using the viewpoint camera to capture the image projected by the AR-HUD;

[0042] (c) Detecting the dot matrix and the light-emitting area or the edge of the light-emitting area required for calibration in the captured image; using the findCirclesGrid function of OpenCV to detect the sample dot matrix, and determining the boundary of the light-emitting area through the envelope determined by the outermost points of the dot matrix.

[0043] Furthermore, the process of detecting the light emitting area or the edge of the light emitting area includes: obtaining the envelope determined by the outermost points of the sample lattice, detecting the edge of the light emitting area with the help of the Canny operator of OpenCV, and filtering the edge in combination with the envelope information.

[0044] (d) Find a dot matrix on the light-emitting area that has a clear correspondence with the original projection image;

[0045] Furthermore, the process of determining the dot matrix on the light-emitting area includes: (d1) determining the virtual image area after de-distortion; (d2) determining the radius of the circular spot in the display area on the original projection image and its ratio information to the length and width of the display area; (d3) leaving a margin in equal proportion between the dot matrix and the boundary of the virtual image area to form Region 1; (d4) finding the required dot matrix on the virtual image area after removing Region 1.

[0046] Preferably, the margin reserved in step (d3) is determined based on the ratio information of the area formed by the envelope formed by the outermost points of the projection dot matrix and the edge of the display content area on the display content area.

[0047] (e) using the correspondence determined in step (d) to calculate the homography relationship, and using the relationship to calculate the corresponding point matrix of the sample point matrix on the projected original image;

[0048] Furthermore, the process of calculating the homography relationship includes converting the sample point matrix to the projection original image by means of the homography relationship between the reference point matrix and the projection point matrix.

[0049] (f) The pre-distortion amount at the dot matrix is ​​calculated according to the difference between the dot matrix in step (e), and the pre-distortion parameters are obtained by interpolation or fitting. Furthermore, the pre-distortion amount at any point on the projection original image is calculated by bicubic spline interpolation. In addition, the calculated pre-distortion parameters are applied to the projection original image to generate a pre-distorted image, thereby reducing or eliminating the distortion of the AR-HUD when it is finally displayed.

[0050] In another embodiment, the method further comprises presetting a target position, where the target position is the position of the reference dot matrix, to ensure that there is sufficient overlap between the area determined by the reference dot matrix and the virtual image area.

[0051] The following will be further described with reference to the accompanying drawings:

[0052] The specific steps are as follows:

[0053] 1) Projected image. In addition to obtaining the dot matrix, the present invention also needs to obtain the light-emitting area (or the boundary of the light-emitting area). Therefore, it is necessary to project an image that can display the complete light-emitting area (or the boundary of the light-emitting area). If there is no dot matrix in the image, it is also necessary to project the dot matrix image. For example: projecting a pure white image or a pure color image and a similar Figure 2 (or Fig.10 ) or just project a dot image like Fig.10 A dot matrix image that can display the edge in the tolerance area, etc. Among them, the pure color image or the dot matrix image that can display the edge will be used to obtain the actual light emitting area or its edge of the AR-HUD, and the dot matrix image will be used to detect the dot matrix.

[0054] In the embodiment, in order to reduce the time consumption of this step, a similar Fig.10 The dot matrix image. Fig.10 The background of the original projection image is white. If it is projected through AR-HUD, the light-emitting area corresponding to the white area will be significantly distinguished from the calibration occasion with no ambient light or dim ambient light, and the actual light-emitting area of ​​​​the AR-HUD can be obtained.

[0055] 2) Capture images, that is, the viewpoint camera captures the images projected by the AR-HUD.

[0056] In the embodiment, the image captured by the camera is as follows: Fig.11 As shown, the black circular spot on the white area corresponds to the original projection image Fig.10 The white area itself corresponds to Fig.10 The area where the white background can be projected is the actual light-emitting area of ​​the AR-HUD, and the black area outside is the imaging of the calibration workshop with no ambient light or dim ambient light outside the AR-HUD light-emitting area on the sample image. Fig.11It can be seen intuitively that the area that can be determined by the sample dot matrix and its outer points is within the actual light-emitting area of ​​the AR-HUD. Therefore, calibrating the AR-HUD based on the actual light-emitting area will obtain a larger FOV than the existing solution based on the area determined by the sample dot matrix.

[0057] 3) Detecting the image, that is, detecting the dot matrix and the light-emitting area or the edge of the light-emitting area required for calibration in the acquired image.

[0058] In the embodiment, first, the sample dot matrix is ​​detected by using the findCirclesGrid function of OpenCV; then, the envelope determined by the outermost points of the sample dot matrix is ​​obtained, and the edge of the light-emitting area should appear in the area outside the envelope, so the edge of the subsequent detection can be filtered out with the help of this information; finally, the edge of the light-emitting area is detected, and the edge detection is completed with the help of the Canny operator of OpenCV, and the following is obtained. Fig.12 The result shown above shows that the larger white outline on the outside is the edge of the light-emitting area, and the inner ring is the edge of the sample dot matrix. Further, the inner ring is filtered out by combining the envelope of the sample dot matrix obtained in the previous step to obtain the following Fig.12 The edge of the actual light-emitting area of ​​the AR-HUD shown below.

[0059] 4) Find a dot matrix on the light-emitting area that has a clear correspondence with the original projection image. The purpose is to use the correspondence between the dot matrix and certain points on the original projection image to determine the conversion relationship between the sample image and the original projection image, and then realize the conversion between the dot matrices on the two.

[0060] Since the invention searches for dots on the light-emitting area, its specific solution is different from the existing solution. Fig. 9 As shown, the area included between the edge of the display area (i.e., the solid rectangular frame) and the envelope line (dotted rectangular frame) determined by the outermost points of the projection dot matrix is ​​also an effective display content area (hereinafter referred to as Region0), and its main function is to ensure that the outermost points of the projection dot matrix can be displayed as complete circular spots in the sample image, and thus can be effectively detected. Therefore, the solution of searching for dot matrix in the area determined by the outermost points of the sample dot matrix in the prior art has taken Region0 into consideration. However, the present embodiment determines the dot matrix on the light emitting area, and there is no effective light emitting area similar to Region0 outside the light emitting area, so it is necessary to take into account the correspondence of Region0 on the virtual image when searching for the dot matrix.

[0061] In the embodiment, the corresponding area of ​​Region0 on the virtual image is taken into account by adopting the following scheme: First, the virtual image area after dedistortion (hereinafter referred to as Region) is determined, that is, the maximum inscribed rectangle is found inside the edge of the detected light-emitting area, and the result is as follows: Fig.13 The result is shown by the solid rectangle in the figure. After distortion calibration, the distortion-free virtual image displayed in front of the vehicle is in the rectangular area. Then, the radius of the circular spot in the display area on the original projection image and its ratio information to the length and width of the display area are determined. Next, an area corresponding to Region0 (hereinafter referred to as Reigin1) is reserved in equal proportion between the edge of Region and the envelope determined by the outermost points of the dot matrix. The specific details of Reigin1 are as follows: Fig.13 The area formed by the dotted rectangle and the realization rectangle is shown as follows; finally, the required dot matrix is ​​found on the Region without Region1, specifically using Fig.10 The number of rows and columns of the midpoint matrix are respectively Fig.13 The width and height of the dotted rectangle are separated, and the resulting dot matrix is ​​as follows Fig.13 As shown in the white spots in the figure. Fig.13 and sample images Fig. 9 , the corresponding region Region1 of Region0 on the virtual image in front of the vehicle is effectively taken into account. The existence of Region1 can prevent the displayed content after dedistortion from being lost due to being adjusted outside the image.

[0062] In summary, the present invention projects one or more images of the display dot matrix and the edge of the light-emitting area, uses a viewpoint camera to collect the image projected by the AR-HUD, detects the dot matrix and the light-emitting area or the edge of the light-emitting area required for calibration in the collected image, finds the dot matrix with a clear corresponding relationship with the original projection image on the light-emitting area, calculates the homography relationship using the determined correspondence, and uses the relationship to calculate the corresponding dot matrix of the sample dot matrix on the original projection image, calculates the pre-distortion variable at the dot matrix according to the difference between the dot matrices, and further uses the interpolation or fitting method to obtain the pre-distortion parameter; the light-emitting area of ​​the AR-HUD can be effectively utilized, and compared with the prior art, the size of the field of view angle can be significantly improved, a larger size or richer information display can be provided, and the driver's visual experience is improved.

[0063] The above terms have the following meanings:

[0064] AR-HUD (AR-Head-up-Display): The fusion of AR technology and HUD display reflects the image through the windshield, and the image is integrated with the environment outside the car, allowing the driver to see the picture that is a combination of the displayed content and the actual environment.

[0065] Viewpoint camera: Figure 1 As shown, a camera is placed at the location of the driver's eyes (viewpoint) to obtain the image seen by the human eye.

[0066] Projected original image: Pattern images containing dots such as checkerboard and circular spot images projected by AR-HUD. Figure 2 This is an example image where the original projection image is a circular spot image.

[0067] Projection dot matrix: the dot matrix in the original projection image. If the original projection image is a chessboard, the projection dot matrix is ​​composed of the corner point coordinates. If it is a circular spot image, the projection dot matrix is ​​composed of the center coordinates.

[0068] Sample image: The image of the virtual image in front of the windshield captured by the viewpoint camera. The so-called virtual image is similar to Figure 1 The AR-HUD in the image is imaged in front of the windshield. After passing through the AR-HUD's complex optical path, the virtual image in the sample image is as follows Figure 3 As shown by the hollow circle in , there is a certain deformation (i.e. distortion) in the spatial arrangement.

[0069] Sample dot matrix: The dot matrix in the extracted sample image. Figure 3 The dot matrix formed by the centers of the hollow circles in the figure is an example of a sample dot matrix.

[0070] Reference dot matrix: A dot matrix generated based on parameters such as arrangement, number of rows and columns, and position. Its function is to provide a calibration benchmark for the sample dot matrix. Figure 3 The point matrix formed by the centers of the solid circles in the figure is an example of the reference point matrix.

[0071] Target position: The position of the reference point matrix. Its value can be set, but it needs to ensure that: in the field of view of the viewpoint camera, the area determined by the reference point matrix at this position overlaps with the virtual image area. Figure 1 The reference point array shown is the target position, such as Figure 3 As shown, the reference point array (solid circle) under the camera's field of view falls within the area (virtual image area) determined by the sample point array (hollow circle).

[0072] Pre-distortion: According to the distortion characteristics of AR-HUD, the original projected image is reversely distorted in advance to offset the distortion of AR-HUD itself so that the human eye sees a normal picture.

[0073] Pre-distortion variables: Figure 4 As shown in the figure, assuming that the image width direction corresponds to the X direction and the height direction corresponds to the Y direction, the black solid circle is a point in the projection lattice, and the black hollow circle is a point in the sample lattice corresponding to the black solid circle and converted to the projection original image. If the point in the sample lattice corresponding to the black hollow circle is to be coincident with the corresponding point in the viewpoint reference lattice (i.e., dedistortion), the black hollow circle needs to be moved to the black solid circle on the projection original image, and the amount of movement is the pre-distortion amount.

[0074] Pre-distortion parameters: Based on the relationship between the dot matrix, the pre-distortion variables at these dot matrixes can be determined, and then the pre-distortion parameters can be obtained by interpolation, fitting and other operations based on the information of the pre-distortion variables corresponding to the positions of the points in the dot matrix. These distortion parameters can be used to calculate the pre-distortion variables at each pixel on the original projection image.

[0075] FOV (Field of View): Also known as the field of view in optical engineering, the size of the field of view angle determines the field of view of the optical instrument. Figure 5 As shown, a larger field of view angle generally means a larger field of view.

[0076] PGU: Image generation unit. Currently, PGU technologies mainly include TFT-LCD projection (Thin Film Transistor Liquid Crystal Display), DLP projection (Digital Light Processing), LBS laser scanning projection (Laser Beam Scanning), LCOS projection (Liquid Crystal on Silicon), etc.

[0077] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An AR-HUD distortion calibration method based on light emitting area, characterized in that: The method comprises the following steps: (a) projecting one or more images showing the dot matrix and the edge of the light-emitting area; (b) Using the viewpoint camera to capture the image projected by the AR-HUD; (c) detecting the dot matrix and the light-emitting area or the edge of the light-emitting area required for calibration in the acquired image; (d) Find a dot matrix on the light-emitting area that has a clear correspondence with the original projection image; The process of determining the dot matrix on the light-emitting area includes: (d1) determining the virtual image area after dedistortion; (d2) determining the radius of the circular spot in the display area on the original projection image and its ratio to the length and width of the display area; (d3) leaving a margin in equal proportion between the dot matrix and the boundary of the virtual image area to form a Region1 area; (d4) Find the required dot matrix on the virtual image area after removing Region1; The margin reserved in step (d3) is determined based on the ratio information of the area formed by the envelope formed by the outermost points of the projection dot matrix and the edge of the display content area on the display content area; (e) using the correspondence determined in step (d) to calculate the homography relationship, and using the relationship to calculate the corresponding point matrix of the sample point matrix on the projected original image; (f) calculating the pre-distortion variables at the lattice according to the differences between the lattices in step (e), and obtaining the pre-distortion parameters by interpolation or fitting method.

2. The AR-HUD distortion calibration method based on the light emitting area according to claim 1, characterized in that: The image projected in step (a) includes a pure color image and an image including a dot matrix pattern, or only includes a dot matrix image that can clearly display the edge in the tolerance area.

3. The AR-HUD distortion calibration method based on the light emitting area according to claim 1, characterized in that: The process of detecting the light emitting area or the edge of the light emitting area in step (c) includes: The envelope determined by the outermost points of the sample lattice is obtained, and the edge of the light area is detected with the help of the Canny operator of OpenCV. At the same time, the edge is filtered in combination with the envelope information.

4. The AR-HUD distortion calibration method based on the light emitting area according to claim 1, characterized in that: The process of calculating the homography relationship in step (e) includes converting the sample dot matrix to the projection original image by means of the homography relationship between the reference dot matrix and the projection dot matrix.

5. The AR-HUD distortion calibration method based on light emitting area according to claim 1, characterized in that: In the step (f), the bicubic spline interpolation method is used to calculate the pre-distortion variable of any point on the projection original image.

6. The AR-HUD distortion calibration method based on light emitting area according to claim 1, characterized in that: The method further comprises presetting a target position, which is the position of the reference dot matrix, to ensure that there is sufficient overlap between the area determined by the reference dot matrix and the virtual image area.

7. The AR-HUD distortion calibration method based on light emitting area according to claim 1, characterized in that: In the step (c), the findCirclesGrid function of OpenCV is used to detect the sample dot matrix, and the boundary of the light emitting area is determined by the envelope determined by the outermost points of the dot matrix.

8. The AR-HUD distortion calibration method based on light emitting area according to claim 1, characterized in that: The pre-distortion parameters calculated in step (f) are applied to the projected original image to generate a pre-distorted image, thereby reducing or eliminating the distortion of the AR-HUD during the final display.

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