A high-pixel headlamp detection device and method

Abstract

The present invention discloses a high-pixel headlamp detection device and method, the detection device comprises a high-pixel headlamp, an industrial lens, an industrial camera, a test screen and an industrial computer; the high-pixel headlamp projects a test image onto the test screen; the industrial camera and the industrial lens are used to collect images on the test screen and transmit the collected images to the industrial computer; the industrial computer is used to receive images transmitted by the industrial camera and perform image processing. The present invention provides a high-pixel headlamp detection device and method, which evaluates the projection pattern quality of the high-pixel headlamp through an imaging test method.

Description

Technical Field

[0001] The invention relates to a detection device and method for a high-pixel headlamp. Background Art

[0002] At present, the headlights of vehicles are a kind of lighting equipment installed on both sides of the head of the vehicle. When the vehicle is driving at night, the headlights can be turned on to illuminate the road ahead, thus ensuring safe driving. As the vehicle use environment becomes more and more complex, the demand for the lighting effect of the headlights is getting higher and higher. High-pixel headlights, due to their high resolution and independent control of each pixel, can directly project text, graphics, and even play images on the ground, realize human-vehicle interaction, vehicle-to-vehicle interaction, improve driving safety, and gradually replace traditional headlights to become the mainstream trend.

[0003] However, traditional headlights mainly use illuminometers, colorimeters, imaging brightness meters, and imaging colorimeters to measure light types. Among them, illuminometers and colorimeters are based on single-point measurement methods and cannot meet the testing requirements of high-pixel headlights. Although imaging brightness meters and imaging colorimeters can capture projected images based on imaging methods, the test resolution and field of view are limited by the test equipment and are expensive, so a more applicable, economical and convenient test method is needed. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a high-pixel headlamp detection device and method, which evaluates the projection pattern quality of the high-pixel headlamp through an imaging test method.

[0005] In order to solve the above technical problems, the technical solution of the present invention is:

[0006] On one hand, the present invention provides a high-pixel headlamp detection device, which includes a high-pixel headlamp, an industrial lens, an industrial camera, a test screen and an industrial computer;

[0007] The high-pixel headlamp projects a test picture onto a test screen;

[0008] The industrial camera and the industrial lens are used to collect images on the test screen and transmit the collected images to the industrial computer;

[0009] The industrial computer is used to receive images transmitted by the industrial camera and perform image processing.

[0010] Furthermore, the test screen is a D-type diffuse reflection screen.

[0011] Another aspect of the present invention provides a detection method of a high-pixel headlamp detection device, which comprises:

[0012] Step S1, a high-pixel headlamp projects a test picture onto a test screen, and an industrial camera and an industrial lens collect an image of the test picture on the test screen;

[0013] Step S2: the industrial camera transmits the collected test image to the industrial computer, which performs image processing;

[0014] Step S3, performing distortion test, FOV test, illumination uniformity test, black and white contrast test, dark spot test and MTF test in sequence.

[0015] Further, the distortion test includes:

[0016] The high-pixel headlamp projects a grid picture onto the test screen, and the industrial camera and industrial lens collect the image of the grid picture on the test screen, and then transmit the image to the industrial computer for image processing, and then identify the light profile of the image, obtain the number of pixels occupied by the bright line on the image, and calculate the horizontal and vertical distortion values ​​of the high-pixel headlamp. The calculation formula for the horizontal and vertical distortion values ​​of the high-pixel headlamp is:

[0017]

[0018]

[0019] Among them, Dist(H) is the distortion in the horizontal direction, Dist(V) is the distortion in the vertical direction, H1 is the number of pixels of the upper frame line of the Tianzi grid picture, H2 is the number of pixels of the lower frame line of the Tianzi grid picture, H3 is the number of pixels of the central horizontal frame line of the Tianzi grid picture, V1 is the number of pixels of the left frame line of the Tianzi grid picture, V2 is the number of pixels of the right frame line of the Tianzi grid picture, and V3 is the number of pixels of the central vertical frame line of the Tianzi grid picture.

[0020] Further, the FOV test includes:

[0021] The distance D between the high-pixel headlight and the test screen, the industrial lens magnification β, and the industrial camera pixel size l are input into the software of the industrial computer. The high-pixel headlight projects a grid picture onto the test screen. The industrial camera and the industrial lens collect the grid picture image on the test screen, and then transmit the image to the industrial computer for image processing. The image is corrected based on the distortion value measured in the distortion test, and the number of pixels occupied by the bright line on the test screen is measured to calculate the FOV of the high-pixel headlight. The calculation formula of the FOV of the high-pixel headlight is:

[0022]

[0023]

[0024] Among them, FOV(H) is the field of view in the horizontal direction, FOV(V) is the field of view in the vertical direction, D is the distance between the high-pixel headlight and the test screen, β is the magnification of the industrial lens, l is the pixel size of the industrial camera, H1 is the number of pixels of the upper frame line of the grid picture, H2 is the number of pixels of the lower frame line of the grid picture, V1 is the number of pixels of the left frame line of the grid picture, and V2 is the number of pixels of the right frame line of the grid picture.

[0025] Further, the illumination uniformity test includes:

[0026] The high-pixel headlamp projects a white image onto the test screen. The industrial camera and industrial lens collect the white image on the test screen, and then transmit the image to the industrial computer for image processing. The ROI area image is intercepted. Let H be the width of the intercepted image, V be the height of the intercepted image, and the test point diameter be V / 20. The image is divided into 3*3 rectangular blocks, each with a width of H / 3 and a height of V / 3. A test point is set at the center of each rectangular block, and the grayscale values ​​of the 9 test points under the white image condition are calculated to obtain the grayscale mean of the white image at the 9 test points. The illumination uniformity is obtained by the ratio of the grayscale mean of the white image at the 9 test points to the grayscale value of the white image at the central test point.

[0027] Further, the black and white contrast test includes:

[0028] The high-pixel headlamp projects a black image onto the test screen. The industrial camera and industrial lens collect the black image on the test screen, and then transmit the image to the industrial computer for image processing. The ROI area image is intercepted and divided into 3*3 rectangular blocks. A test point is set at the center of each rectangular block. The grayscale values ​​of the 9 test points in the black image are calculated to obtain the black image grayscale mean of the 9 test points. The black and white contrast is obtained by the ratio of the white image grayscale mean to the black image grayscale mean.

[0029] Further, the dark spot test includes:

[0030] Through image processing, the collected white image is segmented according to the pixel number u*v of the high-pixel headlight, and the first pattern block in the upper left corner of the image is taken as point (1, 1), and the last pattern block in the lower right corner of the image is taken as point (u, v). The coordinates of each pattern block are established, and the pattern blocks in the image with grayscale values ​​lower than the grayscale mean of the overall white image are identified through image processing, and the coordinates of the pattern blocks in the image with grayscale values ​​lower than the grayscale mean of the overall white image are automatically recorded in the database.

[0031] Further, the MTF test includes:

[0032] The high-pixel headlamp projects the horizontal line pair diagram and the vertical line pair diagram onto the test screen. The industrial camera and the industrial lens collect the horizontal line pair diagram and the vertical line pair diagram on the test screen. The entire projection frame area is framed, and the distance from the center point to the four corners of the projection frame area is defined as 100% field of view. The center field of view, 0.4 field of view and 0.8 field of view of the horizontal line pair diagram and the vertical line pair diagram are taken respectively. The grayscale values ​​of the black and white stripes in the center field of view, 0.4 field of view and 0.8 field of view of the horizontal line pair diagram and the vertical line pair diagram are obtained, and the MTF values ​​in the horizontal and vertical directions of the high-pixel headlamp are calculated:

[0033] MTF=(Imax-Imin) / (Imax+Imin);

[0034] Among them, Imax is the gray value of the white stripes, and Imin is the gray value of the black stripes.

[0035] Furthermore, the detection method further comprises:

[0036] Step S4: The industrial computer organizes the test data in step S3 and generates a corresponding test report.

[0037] The above technical solution is adopted. The present invention collects the projection pattern of the high-pixel headlamp through an industrial camera, performs certain image processing and calculation, and sequentially performs distortion test, FOV test, illumination uniformity test, black-white contrast test, dark spot test and MTF test. Through the test results, the optical indicators such as distortion, illumination uniformity, black-white contrast, and clarity of the headlamp are reflected. It replaces the traditional measurement method of illuminometer, colorimeter, imaging brightness meter, and imaging colorimeter to meet the test requirements of high-pixel headlamp, so that the test resolution and field of view are not limited by the test equipment, and the applicability is stronger, more economical and convenient. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A schematic diagram of hardware device connections of a high-pixel headlamp detection device of the present invention;

[0039] Figure 2 It is a flow chart of a detection method of a detection device for a high-pixel headlamp of the present invention;

[0040] Figure 3 It is a schematic diagram when the test picture of the present invention is a grid picture;

[0041] Figure 4 It is a schematic diagram when the test picture of the present invention is a black picture;

[0042] Figure 5 It is a schematic diagram when the test picture of the present invention is a horizontal line pair picture;

[0043] Figure 6It is a schematic diagram when the test picture of the present invention is a vertical line pair picture;

[0044] Figure 7 A schematic diagram of a method for defining distortion and FOV measurement length of the present invention;

[0045] Figure 8 The invention discloses an image point taking method for uniformity test and black-white contrast test. DETAILED DESCRIPTION

[0046] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments in conjunction with the accompanying drawings.

[0047] Embodiment 1

[0048] like Figure 1 As shown, this embodiment provides a high-pixel headlamp detection device, which includes a high-pixel headlamp, an industrial lens, an industrial camera, a test screen and an industrial computer.

[0049] The high-pixel headlamp projects a test picture onto a test screen.

[0050] The industrial camera and the industrial lens are used to collect images on the test screen and transmit the collected images to the industrial computer.

[0051] The industrial computer has built-in algorithm software and an image acquisition card, which are used to receive images transmitted by the industrial camera and perform image processing.

[0052] The test screen of this embodiment is a D-type diffuse reflection screen, which produces diffuse reflection of incident light within a 2π solid angle space, and its brightness coefficient polar coordinate characteristic curve is close to an ideal diffuse reflection semicircle.

[0053] The industrial camera of this embodiment is a high-resolution, electrically cooled industrial camera. The operating temperature of the industrial camera is 20°C lower than the ambient temperature, which effectively reduces the noise problem caused by dark current, improves the dynamic response range of the industrial camera, and better identifies the brightness changes of the projected pattern. The high-resolution performance enables the industrial camera to accurately identify the quality of each pixel of the projected test image.

[0054] The test environment of this embodiment is as follows:

[0055] Ambient stray light <0.1lx, temperature 23℃±5℃, humidity 20%RH~80%RH.

[0056] Before testing, high-pixel headlamps need to be preheated until thermal stability is achieved. Stable state is defined as a power change value of less than 3% within 15 minutes to eliminate changes in pattern brightness caused by lamp instability.

[0057] The XYZ three axes and angles of the industrial camera fixing device can be fine-tuned, and the fixing devices of the industrial camera and the high-pixel headlight are integrated tooling to ensure that the optical axes of the industrial camera, the high-pixel headlight and the industrial lens are parallel.

[0058] The resolution of all test images should be the same as the actual resolution used by the high-pixel headlights, that is, full-frame projection.

[0059] Dark field calibration is required before testing industrial cameras to remove the impact of dark current noise on the test.

[0060] Embodiment 2

[0061] like Figure 2 As shown, this embodiment provides a detection method of a high-pixel headlamp detection device, which includes:

[0062] Step S1, a high-pixel headlamp projects a test picture onto a test screen, and an industrial camera and an industrial lens collect an image of the test picture on the test screen;

[0063] Step S2: the industrial camera transmits the collected test image to the industrial computer, which performs image processing;

[0064] Step S3, performing distortion test, FOV test, illumination uniformity test, black and white contrast test, dark spot test and MTF test in sequence;

[0065] Step S4: The industrial computer organizes the test data in step S3 and generates a corresponding test report.

[0066] The distortion test of this embodiment includes:

[0067] like Figure 3 As shown, the high-pixel headlamp projects a grid picture onto the test screen, the industrial camera and the industrial lens collect the image of the grid picture on the test screen, and then transmit the image to the industrial computer for image processing, and then identify the light profile of the image, obtain the number of pixels occupied by the bright line on the image, and calculate the horizontal and vertical distortion values ​​of the high-pixel headlamp. The calculation formulas for the horizontal and vertical distortion values ​​of the high-pixel headlamp are:

[0068]

[0069]

[0070] Among them, Dist(H) is the distortion in the horizontal direction, Dist(V) is the distortion in the vertical direction, H1 is the number of pixels of the upper frame line of the Tianzi grid picture, H2 is the number of pixels of the lower frame line of the Tianzi grid picture, H3 is the number of pixels of the central horizontal frame line of the Tianzi grid picture, V1 is the number of pixels of the left frame line of the Tianzi grid picture, V2 is the number of pixels of the right frame line of the Tianzi grid picture, and V3 is the number of pixels of the central vertical frame line of the Tianzi grid picture.

[0071] The FOV test of this embodiment includes:

[0072] like Figure 3 As shown, the distance D between the high-pixel headlight and the test screen, the industrial lens magnification β, the industrial camera pixel size l are input into the software of the industrial computer, the high-pixel headlight projects the grid picture onto the test screen, the industrial camera and the industrial lens collect the grid picture image on the test screen, and then transmit the image to the industrial computer for image processing, the image is corrected based on the distortion value measured in the distortion test, and the number of pixels occupied by the bright line on the test screen is measured to calculate the FOV of the high-pixel headlight. The calculation formula of the FOV of the high-pixel headlight is:

[0073]

[0074]

[0075] Among them, FOV(H) is the field of view in the horizontal direction, FOV(V) is the field of view in the vertical direction, D is the distance between the high-pixel headlight and the test screen, β is the magnification of the industrial lens, l is the pixel size of the industrial camera, H1 is the number of pixels of the upper frame line of the grid picture, H2 is the number of pixels of the lower frame line of the grid picture, V1 is the number of pixels of the left frame line of the grid picture, and V2 is the number of pixels of the right frame line of the grid picture.

[0076] The illumination uniformity test of this embodiment includes:

[0077] The high-pixel headlamp projects a white image onto the test screen. The industrial camera and industrial lens collect the white image on the test screen, and then transmit the image to the industrial computer for image processing to capture the ROI area image. Figure 8 As shown, let H be the width of the captured image, V be the height of the captured image, the diameter of the test point be V / 20, divide the image into 3*3 rectangular blocks, the width of each rectangular block is H / 3, the height of each rectangular block is V / 3, set a test point in the center of each rectangular block, namely test points 1 to 9, calculate the grayscale values ​​of the 9 test points in the white image case, and obtain the white image grayscale mean of the 9 test points. The illumination uniformity is obtained by the ratio of the white image grayscale mean of the 9 test points to the white image grayscale value of the central test point 5.

[0078] The black-and-white contrast test of this embodiment includes:

[0079] like Figure 4 As shown in the figure, a high-pixel headlamp projects a black image onto the test screen, an industrial camera and an industrial lens collect the black image on the test screen, and then transmit the image to an industrial computer for image processing, and intercept the ROI area image. The point selection method is the same as the illumination uniformity test, and the image is divided into 3*3 rectangular blocks. A test point is set at the center of each rectangular block, which are test points 1 to 9. The grayscale values ​​of the 9 test points in the black image case are calculated, and the black image grayscale mean of the 9 test points is obtained. The black-white contrast ratio is obtained by the ratio of the white image grayscale mean to the black image grayscale mean.

[0080] The dark spot test of this embodiment includes:

[0081] Through image processing, the collected white image is segmented according to the pixel number u*v of the high-pixel headlight, and the first pattern block in the upper left corner of the image is taken as point (1, 1), and the last pattern block in the lower right corner of the image is taken as point (u, v). The coordinates of each pattern block are established, and the pattern blocks in the image with grayscale values ​​lower than the grayscale mean of the overall white image are identified through image processing, and the coordinates of the pattern blocks in the image with grayscale values ​​lower than the grayscale mean of the overall white image are automatically recorded in the database.

[0082] The MTF test of this embodiment includes:

[0083] like Figure 5 , 6 As shown, the high-pixel headlamp projects the horizontal line pair diagram and the vertical line pair diagram onto the test screen. The industrial camera and the industrial lens collect the horizontal line pair diagram and the vertical line pair diagram on the test screen. The entire projection frame area is framed, and the distance from the center point of the projection frame area to the four corners is defined as 100% field of view. The center field of view, 0.4 field of view and 0.8 field of view of the horizontal line pair diagram and the vertical line pair diagram are taken respectively. The grayscale values ​​of the black and white stripes in the center field of view, 0.4 field of view and 0.8 field of view of the horizontal line pair diagram and the vertical line pair diagram are obtained, and the MTF values ​​in the horizontal and vertical directions of the high-pixel headlamp are calculated:

[0084] MTF=(Imax-Imin) / (Imax+Imin);

[0085] Among them, Imax is the gray value of the white stripes, and Imin is the gray value of the black stripes.

[0086] The specific embodiments described above further illustrate the technical problems, technical solutions and beneficial effects solved by the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. 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. A high-pixel headlamp detection method, characterized in that: It includes: Step S1, a high-pixel headlamp projects a test picture onto a test screen, and an industrial camera and an industrial lens collect an image of the test picture on the test screen; Step S2: the industrial camera transmits the collected test image to the industrial computer, which performs image processing; Step S3, performing distortion test, FOV test, illumination uniformity test, black and white contrast test, dark spot test and MTF test in sequence; The distortion test includes: The high-pixel headlamp projects a grid picture onto the test screen, and the industrial camera and industrial lens collect the image of the grid picture on the test screen, and then transmit the image to the industrial computer for image processing, and then identify the light profile of the image, obtain the number of pixels occupied by the bright line on the image, and calculate the horizontal and vertical distortion values ​​of the high-pixel headlamp. The calculation formula for the horizontal and vertical distortion values ​​of the high-pixel headlamp is: ； ； Wherein, Dist(H) is the distortion in the horizontal direction, Dist(V) is the distortion in the vertical direction, H1 is the number of pixels of the upper frame line of the Tianzi grid picture, H2 is the number of pixels of the lower frame line of the Tianzi grid picture, H3 is the number of pixels of the central horizontal frame line of the Tianzi grid picture, V1 is the number of pixels of the left frame line of the Tianzi grid picture, V2 is the number of pixels of the right frame line of the Tianzi grid picture, and V3 is the number of pixels of the central vertical frame line of the Tianzi grid picture; The FOV test includes: Enter the distance D between the high-pixel headlight and the test screen, the industrial lens magnification β, and the industrial camera pixel size in the software of the industrial computer. l , the high-pixel headlamp projects a grid picture onto the test screen, the industrial camera and the industrial lens collect the grid picture image on the test screen, and then transmit the image to the industrial computer for image processing, and perform distortion correction on the image based on the distortion value measured in the distortion test, and measure the number of pixels occupied by the bright line on the test screen, and calculate the FOV of the high-pixel headlamp. The calculation formula of the FOV of the high-pixel headlamp is: ； ； Among them, FOV(H) is the horizontal field of view, FOV(V) is the vertical field of view, D is the distance between the high-pixel headlight and the test screen, β is the magnification of the industrial lens, l is the pixel size of the industrial camera, H1 is the number of pixels of the upper frame line of the Tianzi grid picture, H2 is the number of pixels of the lower frame line of the Tianzi grid picture, V1 is the number of pixels of the left frame line of the Tianzi grid picture, and V2 is the number of pixels of the right frame line of the Tianzi grid picture; The illumination uniformity test includes: The high-pixel headlamp projects a white image onto the test screen. The industrial camera and industrial lens collect the white image on the test screen, and then transmit the image to the industrial computer for image processing. The ROI area image is intercepted. Let H be the width of the intercepted image, V be the height of the intercepted image, and the test point diameter is V / 20. The image is divided into Rectangular blocks, each with a width of H / 3 and a height of V / 3, are set at the center of each rectangular block. The grayscale values ​​of the 9 test points under the white image condition are calculated to obtain the grayscale mean of the 9 test points. The illumination uniformity is obtained by the ratio of the grayscale mean of the 9 test points to the grayscale value of the central test point. The black and white contrast test includes: The high-pixel headlamp projects a black image onto the test screen. The industrial camera and industrial lens collect the black image on the test screen, and then transmit the image to the industrial computer for image processing, intercept the ROI area image, and divide the image into rectangular blocks, set a test point in the center of each rectangular block, calculate the grayscale values ​​of the 9 test points in the black image case, get the black image grayscale mean of the 9 test points, and get the black-white contrast ratio by the ratio of the white image grayscale mean to the black image grayscale mean; The dark spot test includes: Through image processing, the collected white image is converted into the pixel number of the high-pixel headlight Perform image segmentation, take the first pattern block in the upper left corner of the image as point (1, 1), and the last pattern block in the lower right corner of the image as point (u, v), establish the coordinates of each pattern block, identify the pattern blocks in the image whose grayscale value is lower than the grayscale mean of the whole white image through image processing, and automatically record the coordinates of the pattern blocks in the image whose grayscale value is lower than the grayscale mean of the whole white image in the database; The MTF test includes: The high-pixel headlamp projects the horizontal line pair diagram and the vertical line pair diagram onto the test screen. The industrial camera and the industrial lens collect the horizontal line pair diagram and the vertical line pair diagram on the test screen, select the entire projection frame area, define the distance from the center point of the projection frame area to the four corners as 100% field of view, take the center field of view, 0.4 field of view and 0.8 field of view of the horizontal line pair diagram and the vertical line pair diagram respectively, obtain the grayscale value of the black and white stripes of the center field of view, 0.4 field of view and 0.8 field of view of the horizontal line pair diagram and the vertical line pair diagram, and calculate the MTF value of the high-pixel headlamp in the horizontal and vertical directions: ； Among them, Imax is the gray value of the white stripes, and Imin is the gray value of the black stripes.

2. The high-pixel headlamp detection method according to claim 1, characterized in that: Also includes: Step S4: The industrial computer organizes the test data in step S3 and generates a corresponding test report.

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