Method for calibrating vehicle headlights

Abstract

The present invention relates to a method (1) for calibrating vehicle headlights, in which a misalignment of a predetermined light distribution is determined by evaluating images from at least one vehicle camera, characterized in that in a first step (2) at least three images are taken, namely a first image (3) including a calibration pattern (4), a second image (5) without the calibration pattern (4), and a third image (6) including an inverted calibration pattern (4'), and in a second step (7) the second image (5) is subtracted from the first and third images (3, 6) to clean up the images (3, 6) from the existing scene.

Description

Technical Field

[0001] The present invention relates to a method for calibrating a vehicle headlight as more particularly defined by the generic concept of claim 1.

Background Art

[0002] Basically, methods for calibrating vehicle headlights are known from the prior art. Such methods are necessary because the positions of the vehicle's headlights are often misaligned. Even if the vehicle is equipped with an automatic lighting range control unit, mechanical stress, thermal expansion or contraction, and step loss of the assembled stepping motor occur over time. Due to all these factors, the headlights are gradually misaligned.

[0003] In particular, misalignment in the vertical direction is a safety-related problem because it can dazzle oncoming traffic or narrow one's own field of vision. Therefore, it is desirable to regularly inspect the headlight position.

[0004] That is, from Patent Document 1, a method for generating a three-dimensional depth information map of the surrounding environment is known. In this method, an optical pattern is projected onto the surrounding environment using a projector and photographed by a camera. Subsequently, the camera image can be evaluated. At this time, the respective positions of the feature points on the corresponding epipolar line are identified, and depth information regarding the three-dimensional map is obtained by determining the displacement of the feature points on this line.

[0005] Another prior art is described in Patent Document 2. This prior art describes a vehicle camera device capable of performing 3D surrounding environment detection. For this, at least two camera modules having at least partially overlapping detection areas are required. 3D surrounding environment detection can be performed using a "pseudo-noise pattern" via a control unit, an evaluation unit, and a spotlight projector.

[0006] Patent Document 3 describes a method for adjusting the headlights of a vehicle. For this purpose, the individual lighting units of the headlights are controlled in a time-staggered manner to illuminate a scene. The scene is captured over a predetermined period of time using a camera included in the vehicle. The luminance distribution pattern obtained as a result of the time-staggered control of multiple lighting units can be used to calculate the deviation from a reference pattern. Subsequently, the headlights can be adjusted based on this deviation. For further prior art, please refer to Patent Documents 4, 5, 6, 7, 8, 9, and 10.

[0007] Stepping motors are used to actively adjust headlights, for example, for illumination range control or cornering light functions. These stepping motors can adjust the illumination module in the headlight by a target angle. There are also approaches to automatically and in-situately adjust the headlight position. For example, the light distribution of the headlights in the area in front of the vehicle can be detected and evaluated via a driver assistance camera. For this type of evaluation, a prominent point with a clear boundary (cutoff line), such as the H0V0 point, is often used. Attempts are made to identify these points in the image. In another variation, a light distribution specially designed for calibration can also be emitted under appropriate conditions, for example, during startup or during sleep mode.

[0008] Next, based on the distance from each pixel in the camera image to a calibrated reference point, the vertical and horizontal angular differences are estimated and compared with the current target adjustment. This allows for compensation of vertical and horizontal positional deviations. However, difficulties arise under uncontrolled or uncontrollable environmental conditions. These environmental conditions include optical characteristics, as well as the structure, shape, and position of the illuminated surface. Furthermore, different vehicles may have different lighting systems. In such cases, differences in color and luminance distribution can lead to errors in individual pixels or inaccuracies in the optical path, which can cause blurring and color shifts. The evaluation algorithm may be based particularly on edge detection and maximum detection; however, this could lead to imprecise calibration with inaccurate and variable feature extraction. In particular, it may not be possible to robustly maintain the 0.1% safety-related accuracy required by ECE. For example, the introduction of high-resolution lighting systems based on LCD, DMD, or μLED technology into vehicles also necessitates projecting increasingly complex light distributions. [Prior art documents] [Patent Documents]

[0009] [Patent Document 1] DE102020007613A1 [Patent Document 2] DE102017222708A1 [Patent Document 3] DE102016118801A1 [Patent Document 4] DE102012007908A1 [Patent Document 5] DE102016006391A1 [Patent Document 6] DE102011109440A1 [Patent Document 7] DE102015203889A1 [Patent Document 8] DE102014117845A1 [Patent Document 9] DE102017117594A1 [Patent Document 10] DE102020000292A1 [Overview of the project] [Problems that the invention aims to solve]

[0010] The object of the present invention is to provide a method for calibrating vehicle headlights that overcomes the above-mentioned drawbacks. [Means for solving the problem]

[0011] According to the present invention, this problem is solved by the features of claim 1, and more particularly by the method comprising the configuration described in the feature portion of claim 1. Advantageous configurations and variations become apparent from the dependent claims of claim 1.

[0012] Essentially, the method according to the present invention involves, in the first step, taking at least three images, namely, a first image containing the calibration pattern, a second image without the calibration pattern, and a third image containing the inverted calibration pattern; and in the second step, the second image is subtracted from the first and third images, thereby cleaning up the image from the existing scene, wherein the calibration pattern includes circles, the positions of the circles in the image are known, the center points of the circles are located on the horizontal line, the center points of each circle are calculated using linear approximation, and it is determined whether the projection of the calibration pattern is on an appropriate surface suitable for performing the calibration. As a result of subtracting the images, at any point, only the calibration pattern can be seen in the image. This significantly simplifies the subsequent evaluation algorithm and allows the evaluation algorithm to be implemented more robustly. Thus, a system is provided for automatically and accurately calibrating high-resolution headlight systems in vehicles.

[0013] A method for calibrating vehicle headlights identifies a predetermined misalignment of the light distribution by evaluating images from at least one vehicle camera. This misalignment can then be compensated for, for example, by a stepping motor and by redefining the zero position.

[0014] During calibration, this method can detect structures in the area in front of the vehicle, and in particular, it can output whether or not there is a wall in front of the vehicle. Similarly, it can also determine the orientation of the wall. All of this information can be used to adapt the projection from the headlights to the existing area in front.

[0015] Preferably, in the third step, the first image and the third image can be compared pixel by pixel in order to identify the brightness difference between pixels at the same location.

[0016] Here, with a favorable configuration, areas with very small luminance differences can be represented as gray areas. As gray areas, for example, areas outside the calibration pattern are marked, and since these areas also exist within the camera image, i.e., within the image, there is no need to evaluate them further. This has the advantage that the background scene is represented by gray values ​​that are clearly separated from the headlight projection area. Furthermore, the fusion of the two inverse images eliminates the effects of optical crosstalk of active pixels caused by imperfect light channels. This, for example, can improve the positioning of subsequent circles.

[0017] The calibration pattern includes a circle, in which case the position of the circle in the image is known. High-resolution systems allow for the use of entirely different projections for calibration. Therefore, for example, circles can be used, and these circles offer several advantages. For instance, a circle has a constant center point, independent of the focal point of the illumination system on the projection plane. Furthermore, circles are robust to distortion.

[0018] The central point of the circle is arranged on a horizontal line. Advantageously, the position of the circle in the illumination area of the headlight is known. This can be done, for example, using the known spacing of lines parallel to each other, as well as the maximum allowable distance or known distance between the central points.

[0019] Using linear approximation, the central point of each circle is calculated, and it is determined whether the projection of the calibration pattern is performed on a suitable plane suitable for carrying out the calibration. For example, the projection can be ensured to be performed on a plane by the necessary maximum rotation and the spacing of the parallel lines. Only in such cases, advantageously, it is desirable for the calibration to be continued.

[0020] According to a very advantageous development of the idea, the vehicle camera can be calibrated in advance. This is advantageous for the implementation of the linear approximation described above. A pre-calibrated vehicle camera is also advantageous for determining the position and rotation of the projection plane, i.e., for determining the pose.

[0021] Here, according to an advantageous configuration, the pose of the projection plane can be determined by rotating the calibration pattern in the horizontal and vertical directions and shifting the central point of the circle in the camera image. This is particularly done by assuming a flat projection plane. Thus, in the last step, the orientation of the headlight can be determined via the pose of the plane, the position of the central point in the camera image, and the known angular position of the associated headlight pixel, and the related misalignment can be derived. The known angular position may be the vertical angle with respect to the central point and / or the horizontal angle with respect to the central point of the circle.

[0022] Similarly or alternatively, the headlight can be calibrated in advance for using the circle as a feature point for triangulation of 3D coordinates. Here, advantageously, for two shifted calibration patterns, an additional 2 × 3 image is taken once. In this type of case, in particular, a corresponding camera - headlight pair is used as a structured light system.

[0023] Similarly, when scaling the projected circle in space, it is conceivable to model the circle as the side surface of a cone. Here again, the position of the ring in three-dimensional space can be precisely determined, and since the mounting position of the headlights is known, the light beam can be reconstructed, allowing for direct calculation of the headlight adjustments.

[0024] In another advantageous configuration, the orientation can be determined by a known angular position of a calibrated vehicle camera, and by detecting flat surfaces and discontinuous scenes, the projection and / or animation for effect can be adapted to the projection surface. Advantageously, this allows for accurate measurement of the projection surface in front of the vehicle, in which not only flat surfaces such as walls or roads but also more complex and unstable scenes can be detected.

[0025] Another advantage of the method according to the present invention will become apparent from the remaining dependent claims and from the embodiments described below in more detail with reference to the drawings. [Brief explanation of the drawing]

[0026] [Figure 1] One possible embodiment of the calibration pattern is shown. [Figure 2] Another possible embodiment of the calibration pattern is shown. [Figure 3] This document outlines the possible steps taken by this method. [Modes for carrying out the invention]

[0027] Figure 1 shows possible embodiments of calibration pattern 4. Calibration pattern 4 has individual circles 9, each having a center point 10. The surface shows, for example, the surface of the headlight 13.

[0028] Another modified embodiment of Method 1 can be seen in Figure 2. The difference from Figure 1 is the arrangement of the circles 9. Furthermore, a horizontal line 11 extending along the center point 10 can be seen. In this type of calibration pattern 4, vertical lines 11' can also be drawn for evaluation, and these vertical lines similarly connect two center points 10 to each other.

[0029] Figure 3 shows the possible steps of Method 1. In the first step 2, three separate images are generated. Image 3, containing calibration pattern 4, is captured. Image 5, not containing calibration pattern 4, is captured. Image 6, containing the inverted calibration pattern 4', is captured. In the second step 7, Image 5 is subtracted from Image 3 and Image 6. This allows Images 3 and 6 to be cleaned up from the existing separate scenes. For clarity, the second step 7 is shown redundantly. In the third step 8, Images 3 and 6 are compared pixel by pixel to find brightness differences between pixels at the same location. Small brightness differences are represented as gray areas. This corresponds to the area outside the headlight 13 and is represented by thin dashed lines.

[0030] Therefore, this method enables simple and automatic calibration of headlights without requiring additional hardware components. Advantageously, high accuracy can be achieved. Furthermore, this method is robust to the surrounding environment and can be performed autonomously, and therefore without the contribution of a driver or other operator. This inevitably brings advantages in terms of safety and comfort. Similarly, using the projection space profile calculated during operation, vehicle projections, such as animations for startup effects, can be adapted to the existing projection surface.

Claims

1. A method (1) for calibrating vehicle headlights, wherein a predetermined positional deviation of the light distribution is identified by evaluating images from at least one vehicle camera, In the first step (2), at least three images are taken, namely, a first image (3) containing the calibration pattern (4) is taken, a second image (5) not containing the calibration pattern (4) is taken, and a third image (6) containing the inverted calibration pattern (4') is taken, and in the second step (7), the second image (5) is subtracted from the first and third images (3, 6) so that the first and third images (3, 6) are cleaned up from the existing scene. The calibration pattern (4) includes a circle (9), the position of the circle (9) in the image is known, the center point (10) of the circle (9) is located on a horizontal line (11), the center point (10) of each circle is calculated using linear approximation, and the calibration pattern obtained from the subtracted and cleaned-up first and third images (3, 6) is used to determine whether the projection of the calibration pattern (4) is on an appropriate surface suitable for performing the calibration. This is the method (1).

2. The method (1) according to claim 1, characterized in that in the third step (8), the subtracted and cleaned first image (3) and the subtracted and cleaned third image (6) are compared pixel by pixel in order to identify the difference in brightness between pixels at the same position.

3. The method (1) according to claim 2, characterized in that the region with a very small difference in brightness is represented as a gray region.

4. The method (1) according to any one of claims 1 to 3, characterized in that the vehicle camera is calibrated in advance.

5. The method (1) according to claim 4, characterized in that the orientation of the projection plane is determined by rotating the calibration pattern (4) in the horizontal and vertical directions and shifting the center point (10) of the circle in the camera image (12) to calculate the orientation of the projection plane.

6. The method (1) according to claim 5, characterized in that the orientation is determined by a known angular position of the calibrated vehicle camera, and by detecting flat surfaces and discontinuous scenes, the projection and / or animation for performance can be adapted to the projection surface.

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