Head-up display device ghost detection method, device and electronic device

Abstract

The application discloses a head-up display device ghosting detection method and device and electronic equipment. After a virtual image of a test image projected by a head-up display device in a windshield glass, the virtual image is photographed by an image acquisition device to obtain a first image containing the virtual image. By traversing lines and / or points in the first image, the main body center pixel coordinates corresponding to the main body part and the ghost center pixel coordinates corresponding to the ghost part in each row or each column to which each line and / or each point in the first image belongs are determined. According to the difference between the pixel coordinates of the main body center and the ghost center, the ghost value corresponding to the head-up display device is determined. According to the embodiment of the application, the ghost value can be tested before the head-up display device is shipped, so that unqualified products can be intercepted in the factory, the ghost value of the head-up display device shipped is ensured to be within a specified range, the actual use effect of the head-up display device is ensured, and the driving comfort and safety of the driver are improved.

Description

Technical Field

[0001] This application belongs to the field of automotive electronics technology, and in particular relates to a method, device and electronic equipment for detecting ghosting in head-up display devices. Background Technology

[0002] The electrification and intelligentization of the automotive industry continue to deepen, with the intelligent cockpit becoming a core component in the overall intelligent development of vehicles. Head-up displays (HUDs), as an important part of human-machine interaction solutions, are crucial hardware for realizing the intelligence and connectivity of intelligent cockpits. The core components of HUD technology mainly include the image generation unit (PGU), freeform surface mirrors, and the windshield. The HUD device has a built-in PGU imaging system. Through multiple internal optical reflections, the image is projected onto the windshield and reflected into the driver's eyes. The driver can then see a virtual image on the windshield, which can include various information such as vehicle, entertainment, ADAS, and navigation information. This allows the driver to quickly and conveniently access this information without looking down, greatly improving driving safety and comfort.

[0003] However, since the windshield is usually composed of two layers of glass and a polyvinyl butyral (PVB) interlayer, the virtual image displayed by the HUD device on the windshield often appears as a ghost image. The ghost image significantly reduces the image quality of the HUD device, causing an uncomfortable visual experience for the driver.

[0004] To eliminate the effects of ghosting, it is necessary to detect ghosting. Therefore, there is an urgent need for a solution that can detect ghosting in HUD devices. Summary of the Invention

[0005] This application provides a method, apparatus, device, storage medium, and program for detecting ghosting in a head-up display device, which can detect the ghosting value of the head-up display device.

[0006] In a first aspect, embodiments of this application provide a method for detecting ghosting in a head-up display device, including:

[0007] The test image is projected onto the windshield using a head-up display device, and the test image includes an array of lines and / or dots.

[0008] The test image projected onto the windshield is captured by an image acquisition device to obtain a first image containing the virtual image.

[0009] Perform pixel traversal on the lines and / or points contained in the first image to obtain the main center pixel coordinates and ghost center pixel coordinates for each row or column to which each line and / or point belongs in the first image.

[0010] The ghost value corresponding to the head-up display device is determined based on the difference between the main center pixel coordinates and the ghost center pixel coordinates corresponding to each row or column to which each line and / or each point belongs.

[0011] As one possible implementation, the method further includes the following steps before performing pixel traversal on the lines and / or points contained in the first image:

[0012] Apply Gaussian filtering to the first image.

[0013] Based on image processing algorithms, contour recognition and image segmentation are performed on the first image after Gaussian filtering to obtain lines and / or points in the first image.

[0014] As one possible implementation, pixel traversal is performed on the lines and / or points contained in the first image to obtain the main center pixel coordinates and ghost center pixel coordinates corresponding to each row or column to which each line and / or point in the first image belongs, including:

[0015] Perform pixel traversal on each line and / or each point contained in the first image to obtain the pixel peak value corresponding to each row or column to which each line and / or each point belongs in the first image, and record the pixel coordinates of the pixel peak value.

[0016] For each row or column to which each line and / or each point in the first image belongs, determine the main body center pixel coordinates and the ghost center pixel coordinates corresponding to that row or column based on the pixel peak value corresponding to that row or column.

[0017] As one possible implementation, the pixel coordinates of the subject center and the pixel coordinates of the ghost center are determined based on the pixel peak value corresponding to the row or column, including:

[0018] Determine the center pixel coordinates of the subject in that row or column by using the pixel coordinates corresponding to the maximum pixel value among the pixel peaks in that row or column.

[0019] Among the pixel peaks corresponding to that row or column, the pixel peak located between the preset ghosting threshold and the background threshold is determined as the first pixel peak.

[0020] The pixel coordinates corresponding to the maximum pixel value in the first pixel peak are determined as the pixel coordinates of the ghost center corresponding to that row or column.

[0021] As one possible implementation, the ghost value corresponding to the head-up display device is determined based on the difference between the subject center pixel coordinates and the ghost center pixel coordinates corresponding to each row or column to which each line and / or each point belongs, including:

[0022] For each row or column to which each line and / or each point in the first image belongs, the difference between the center pixel coordinates of the main subject and the center pixel coordinates of the ghost image corresponding to that row or column is determined as the ghost image value corresponding to that row or column.

[0023] For each line and / or each point in the first image, the ghost value with the highest probability among the ghost values ​​corresponding to the row or column to which that line or point belongs is determined as the ghost value corresponding to that line or point.

[0024] The maximum value among all lines and / or all points in the first image is determined as the ghost value corresponding to the head-up display device.

[0025] As one possible implementation, the method also includes:

[0026] The ghosting value corresponding to the head-up display device is converted according to a preset conversion formula to obtain the ghosting deviation angle corresponding to the head-up display device.

[0027] The conversion formulas include:

[0028]

[0029] In the formula, α represents the ghosting deviation angle, d represents the ghosting value before conversion, P represents the pixel size of the image acquisition device, and f represents the focal length of the image acquisition device.

[0030] As one possible implementation, the method also includes projecting the test image onto the windshield using a head-up display device:

[0031] Distortion correction is performed on the test image.

[0032] Projecting test images onto the windshield using a head-up display device includes:

[0033] The distortion-corrected test image is projected onto the windshield using a head-up display device.

[0034] As one possible implementation, before obtaining the first image, the method further includes: acquiring a virtual image of the test image projected onto the windshield using an image acquisition device.

[0035] Adjust the position of the head-up display device and / or the image acquisition device to ensure that the virtual image projected onto the windshield based on the test image captured by the image acquisition device is complete, the tilt angle is less than a preset tilt angle threshold, and / or the exposure is less than a preset exposure threshold.

[0036] The first image is obtained by acquiring a virtual image of the test image projected onto the windshield using an image acquisition device, and includes:

[0037] After adjusting the head-up display and / or image acquisition device, the first image is obtained by acquiring a virtual image of the test image projected onto the windshield using the image acquisition device.

[0038] Secondly, embodiments of this application also provide a ghosting detection device for a head-up display device, comprising:

[0039] An image projection module is used to project a test image onto the windshield based on a head-up display device, wherein the test image includes an array of lines and / or dots.

[0040] The image acquisition module is used to capture a virtual image of the test image projected onto the windshield using an image acquisition device, thereby obtaining a first image containing the virtual image.

[0041] The pixel traversal module is used to perform pixel traversal on the lines and / or points contained in the first image, and obtain the main center pixel coordinates and ghost center pixel coordinates for each row or column to which each line and / or point belongs in the first image.

[0042] The device ghost value determination module is used to determine the ghost value corresponding to the head-up display device based on the difference between the main body center pixel coordinates and the ghost center pixel coordinates corresponding to each row or column to which each line and / or each point belongs.

[0043] Thirdly, embodiments of this application also provide an electronic device, the device comprising: a processor and a memory storing computer program instructions.

[0044] When the processor executes the computer program instructions, it implements the ghosting detection method for head-up display devices as described in the first aspect.

[0045] Fourthly, embodiments of this application also provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the head-up display device ghosting detection method as described in the first aspect.

[0046] Fifthly, embodiments of this application also provide a computer program product, wherein instructions in the computer program product, when executed by a processor of an electronic device, enable the electronic device to perform the head-up display device ghost detection method as described in the first aspect.

[0047] The method, apparatus, device, storage medium, and program for detecting ghosting in head-up display (HUD) devices according to embodiments of this application, after projecting a virtual image of a test image onto the windshield using the HUD device, an image acquisition device captures the virtual image to obtain a first image containing the virtual image. By traversing the lines and / or points in the first image, the pixel coordinates of the main body center of the virtual image corresponding to each row or column of each line and / or point in the first image and the pixel coordinates of the ghosting center corresponding to the ghosting part are determined. Based on the difference between the pixel coordinates of the main body center and the ghosting center, the ghosting value corresponding to the HUD device is determined. According to embodiments of this application, the ghosting size can be tested and evaluated before the HUD device leaves the factory, thus intercepting defective products at the factory and ensuring that the ghosting value of the HUD devices leaving the factory is within the specified range, guaranteeing the actual use effect of the HUD device and improving the driving comfort and safety of the driver. In addition, the ghosting effect of the HUD device can also be evaluated during the design verification stage to help R&D personnel make design improvements. Attached Figure Description

[0048] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a schematic flowchart of the ghosting detection method for head-up display devices provided in an embodiment of this application.

[0050] Figure 2 This is a schematic diagram of the test images provided in the embodiments of this application.

[0051] Figure 3 This is a schematic diagram of the test images provided in the embodiments of this application.

[0052] Figure 4 This is a schematic diagram of the structure of the ghosting system for the head-up display device provided in an embodiment of this application.

[0053] Figure 5 This is a partial schematic diagram of the first image provided in this application after contour recognition and segmentation.

[0054] Figure 6 This is a flowchart illustrating a ghosting detection method for a head-up display device according to another embodiment of this application.

[0055] Figure 7 This is a schematic diagram of the structure of the ghost detection device for head-up display provided in an embodiment of this application.

[0056] Figure 8This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0057] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0058] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0059] The basic hardware architecture of a HUD device mainly includes a data acquisition unit, a control unit, and a projection display unit. The data acquisition unit is mainly responsible for collecting vehicle condition information (such as vehicle speed, navigation, temperature, fuel consumption, and entertainment information) and road condition information. The control unit is mainly used to receive the information collected by the data acquisition unit, process the information, and output it. The projection display unit is mainly responsible for generating images based on the information output by the control unit and using a projection device to project the images onto the windshield of the car through a reflector / refractor.

[0060] In the imaging optical path of a HUD (Head-Up Display) device, the windshield is a crucial optical component, and its design is closely related to the display effect of the virtual image. Typically, a windshield consists of two layers of glass and an interlayer film (such as a polyvinyl butyral (PVB) film), resulting in two surfaces. When incident light is projected onto the windshield, both surfaces reflect the light. Since the thickness of the interlayer film is usually uniform, meaning the two surfaces are parallel, the same incident light will create two reflected rays on the glass. When these are simultaneously received by the human eye, a ghosting effect occurs, resulting in two virtual images on the windshield. This phenomenon is called ghosting. Ghosting significantly reduces the image quality of the HUD device, causing discomfort for the driver. To reduce the negative impact of ghosting on users, ghosting can be included as an important evaluation item during the end-of-life (EOL) testing phase on the automotive production line. The ghosting test results can be used to assess whether the HUD meets product standards, allowing for timely adjustments when ghosting issues are identified. Therefore, there is an urgent need for a solution that can detect ghosting in head-up display devices.

[0061] To achieve ghosting detection of head-up display devices, embodiments of this application provide a method, apparatus, device, storage medium, and program for ghosting detection of head-up display devices.

[0062] The ghosting detection method for head-up display devices provided in the embodiments of this application will be described below.

[0063] See Figure 1 This is a flowchart illustrating a method for detecting ghosting in a head-up display (HUD) according to an embodiment of this application. This method can be implemented based on a HUD ghosting detection system, which may include a HUD, a windshield, and an image acquisition device, such as... Figure 1 As shown, the method may include the following steps S11-S14.

[0064] S11. Project the test image onto the windshield using a head-up display device.

[0065] The test image is used for ghosting detection of head-up display (HUD) devices. It includes lines and / or dots arranged in an array. For example, the number of rows and columns in the test image can be M, where M and N are positive integers greater than or equal to 1. The specific number of rows and columns can be set according to the virtual image size of the HUD device being tested, and is generally set to an odd number of rows and columns, such as 5 rows and 9 columns, 5 rows and 11 columns, etc. It is generally recommended to have at least 5 rows and 5 columns.

[0066] As an example, test images may include, but are not limited to, Figure 2 and / or Figure 3 The image shown.

[0067] The diameter of the points and / or the dimensions (width and length) of the lines contained in the test image can be set according to the chip resolution of the head-up display device being tested. When setting it, it is necessary to ensure that the stretching and deformation of the projected virtual image after HUD projection will not affect the ghost detection. The test image needs to cover different fields of view and be able to measure the size of the ghost in both the horizontal and vertical directions at the same time.

[0068] When it is determined that ghosting detection of the head-up display device is required, the head-up display device can be turned on, and the test image can be projected onto the windshield based on the head-up display device.

[0069] S12. Take a picture of the virtual image of the test image projected on the windshield using an image acquisition device to obtain a first image containing the virtual image.

[0070] Image acquisition equipment can be devices with image acquisition capabilities, such as test cameras.

[0071] After the head-up display projects the test image onto the windshield, the image acquisition device is turned on and used to capture the virtual image of the test image projected onto the windshield, thus obtaining the first image, which contains the virtual image projected onto the windshield.

[0072] S13. Perform pixel traversal on the lines and / or points contained in the first image to obtain the main center pixel coordinates and ghost center pixel coordinates corresponding to each row or column to which each line and / or point in the first image belongs.

[0073] In the first image, the virtual image actually includes the main body and the ghosting part of the virtual image. The center pixel coordinates of the main body of each line and / or each point in each row or column refer to the center coordinates of the main body of the virtual image in that row or column. The center pixel coordinates of the ghosting part of each line and / or each point in each row or column refer to the center coordinates of the ghosting part of the virtual image in that row or column.

[0074] By performing pixel traversal on the lines and / or points in the first image, the center point of the region corresponding to the main body of the virtual image and the center point of the region corresponding to the ghost image in each row or column to which each line and / or point belongs are distinguished. Since each pixel in the first image corresponds to a pixel coordinate, the pixel coordinates of the center point of the region corresponding to the main body of the virtual image are determined as the center pixel coordinates of the main body, and the pixel coordinates of the center point of the region corresponding to the ghost image are determined as the center pixel coordinates of the ghost image.

[0075] Using the above method, the center pixel coordinates of the subject and the center pixel coordinates of the ghost image can be determined for each row or column to which each line and / or each point in the first image belongs.

[0076] S14. Determine the ghost value corresponding to the head-up display device based on the difference between the main center pixel coordinates and the ghost center pixel coordinates corresponding to each row or column to which each line and / or each point belongs.

[0077] Typically, when a head-up display (HUD) device exhibits ghosting, there is a positional deviation between the ghost and the main subject. This results in the center point of the main subject area and the center point of the ghost area being different in the same row or column, i.e., their pixel coordinates are different. Therefore, based on the difference between the center pixel coordinates of the main subject and the center pixel coordinates of the ghost, the ghosting value corresponding to the HUD device can be estimated.

[0078] If the preceding data provides the subject center pixel coordinates and ghost center pixel coordinates for each row to which each line and / or point belongs, then the ghost value corresponding to the head-up display device can be determined based on the subject center pixel coordinates and ghost center pixel coordinates for multiple rows. If the preceding data provides the subject center pixel coordinates and ghost center pixel coordinates for each column to which each line and / or point belongs, then the ghost value corresponding to the head-up display device can be determined based on the subject center pixel coordinates and ghost center pixel coordinates for multiple columns.

[0079] The ghosting detection method for head-up display (HUD) devices provided in this application involves, after the HUD projects a virtual image of a test image onto the windshield, an image acquisition device captures the virtual image to obtain a first image containing the virtual image. By traversing the lines and / or points in the first image, the pixel coordinates of the main body center of the virtual image and the pixel coordinates of the ghosting center of the ghosting portion are determined for each row or column of the first image, corresponding to each line and / or each point. Based on the difference between the pixel coordinates of the main body center and the ghosting center, the ghosting value corresponding to the HUD device is determined. According to this application embodiment, the ghosting size can be tested and evaluated before the HUD device leaves the factory, thus intercepting defective products and ensuring that the ghosting value of the HUD devices leaving the factory is within the specified range, guaranteeing the actual use effect of the HUD device and improving the driving comfort and safety of the driver. In addition, the ghosting effect of the HUD device can also be evaluated during the design verification stage to help R&D personnel make design improvements.

[0080] In some embodiments, before performing S11, the brightness of the head-up display device can be adjusted to the set brightness level corresponding to the test environment. After adjusting the brightness to the set brightness level, the test image is then projected onto the windshield based on the head-up display device.

[0081] The brightness level set for the test environment can be the brightness level commonly used by users in real-world scenarios corresponding to the test environment.

[0082] By using the above method, different brightness levels are set for different test environments, so that the brightness level of the head-up display device during testing is more consistent with the actual situation during use. This makes the ghosting value of the head-up display device obtained based on the test environment more consistent with the actual usage scenario.

[0083] In some embodiments, the following steps may be performed before executing S11:

[0084] If it is determined that there is image distortion in the head-up display device, the test image is distorted and then the distortion correction is performed. After the distortion correction is completed, S11 is executed.

[0085] For example, the test image can be subjected to T-shaped inverse distortion processing before performing S11.

[0086] By correcting the distortion of the test image, it can be ensured that the projected image is free of distortion or has minimal distortion, thereby reducing the impact of the head-up display device's distortion on the ghosting detection results.

[0087] In some embodiments, the following steps may be performed before executing S12:

[0088] Adjust the position of the image acquisition device so that the optical center of the image acquisition device is located in the driver's eye position in the vehicle coordinate system. After the adjustment is completed, execute S12.

[0089] By adjusting the optical center of the image acquisition device to the mid-eye position of the driver's mid-eye box, the virtual image in the first image captured by the image acquisition device can be made closer to the virtual image seen by the human eye, thereby improving the accuracy of the ghosting detection results.

[0090] In some embodiments, the following steps may be performed before executing S12:

[0091] Adjust the position of the head-up display device and / or the image acquisition device to ensure that the virtual image projected onto the windshield based on the test image acquired by the image acquisition device is complete, the tilt angle is less than a preset tilt angle threshold, and / or the exposure is less than a preset exposure threshold. After the adjustment is completed, execute S12.

[0092] When adjusting the position of the head-up display (HUD) and / or the image acquisition device, the image acquisition device can be used to capture a virtual image of the test image projected onto the windshield, and then adjustments can be made based on the captured image. During adjustment, it can be determined whether there are any missing virtual images of the test image in the captured image. This can be done by using software to identify the number of lines and / or points in the captured image. If the number of lines and / or points in the captured image is less than the known number of lines and / or points in the test image, the captured image is considered incomplete and missing. In this case, the installation positions of the HUD and the image acquisition device can be checked. Furthermore, it can be determined whether the tilt of the captured image is greater than or equal to a tilt threshold. This can be done by considering whether the tilt is greater than or equal to the tilt threshold if the coordinate deviation between the first point or line in each row or column and the center point of the last point or line in that row or column is greater than a preset pixel (e.g., 10 pixels). In this case, the relative positions of the image acquisition device and the HUD can be adjusted. Furthermore, the signal strength displayed in the video stream of the image acquisition device can be used to determine whether the exposure of the captured image is greater than or equal to the preset exposure threshold, i.e., whether it is overexposed. If it is overexposed, an attenuator can be added to the image acquisition device.

[0093] The above adjustments can effectively improve the quality of the final captured first image, ensuring that a high-quality first image can be obtained.

[0094] In some embodiments, the ghosting detection method for head-up display devices provided in this application can be based on, for example, Figure 4 The ghosting detection system of the head-up display device shown is used to acquire the first image, such as... Figure 4 As shown, the system may include:

[0095] Head-up display device 410, head-up display device stand 420, windshield 430, image acquisition device 440 and image acquisition device fixing device 450.

[0096] The head-up display (HUD) stand 420 comprises a fixed base and a mounting frame. The HUD 410 is fixed to the HUD stand 420 and connected to the mounting frame by screws. The installation coordinates of the HUD 410 are consistent with the coordinates specified in the design.

[0097] The windshield 430 is located in front of the head-up display 410. Its position coordinates are determined by the design coordinate values. The windshield 430 should be used in conjunction with the head-up display 410. Both are products of the same model and are products used in the design.

[0098] The image acquisition device 440 can be a high-resolution, high-quality camera, such as a camera with over 10 megapixels. The field of view of the image acquisition device 440 is larger than that of the head-up display device 410, and its distortion is small, avoiding the influence of distortion on the captured image. Before performing ghosting detection, the image acquisition device 440 can be calibrated to determine its intrinsic and extrinsic parameter matrices.

[0099] The image acquisition device fixing device 450 plays a role in fixing and adjusting the position of the image acquisition device 440. It enables the image acquisition device 440 to translate in the x, y, and z directions and rotate the coordinate axes. When performing ghost detection, the image acquisition device 440 can be moved to the driver's middle eye position in the vehicle coordinate system through the image acquisition device fixing device 450.

[0100] In order to ensure the degree of freedom of position adjustment of the image acquisition device 440, the image acquisition device fixing device 450 can adopt a six-axis robotic arm.

[0101] Based on this, before executing S12, the position of the image acquisition device 440 can be adjusted by the image acquisition device fixing device 450, and the position of the head-up display device 410 can be adjusted based on the head-up display device stand 420. After the adjustment is completed, in S12, the first image can be acquired based on the adjusted image acquisition device.

[0102] In some embodiments, before performing S13 above, each line and / or point contained in the first image may be determined first, so that pixel traversal can be performed in S13 based on the determined lines and / or points.

[0103] The process of determining each line and / or each point in the first image includes the following steps:

[0104] Apply Gaussian filtering to the first image.

[0105] Based on image processing algorithms, contour recognition and image segmentation are performed on the first image after Gaussian filtering to obtain each line and / or each point in the first image.

[0106] By applying Gaussian filtering to the first image, the virtual image main body and the ghosting part of the lines and / or points in the first image can be connected into a connected region. Furthermore, by using image processing algorithms such as OpenCV algorithm functions to perform contour recognition and segmentation on the Gaussian-filtered first image, every line and / or every point in the first image can be found, where the found lines and / or points contain the virtual image main body and the ghosting part.

[0107] As an example, using the test image as... Figure 3 For example, see the image shown. Figure 5 This is a partial schematic diagram of contour recognition and segmentation of the first image after Gaussian filtering using image processing algorithms, where each small rectangle contains a segmented line.

[0108] Using the above method, each line and / or point in the first image can be accurately and quickly identified, facilitating traversal.

[0109] In some embodiments, the specific implementation of S13 above may include:

[0110] Perform pixel traversal on the lines and / or points contained in the first image to obtain the pixel peak value corresponding to each row or column to which each line and / or point belongs in the first image, and record the pixel coordinates of the pixel peak value.

[0111] For each row or column to which each line and / or each point in the first image belongs, determine the main body center pixel coordinates and the ghost center pixel coordinates corresponding to that row or column based on the pixel peak value corresponding to that row or column.

[0112] Ghosting in head-up display (HUD) devices typically includes horizontal and vertical ghosting. To detect both horizontal and vertical ghosting simultaneously, the test image, if containing lines, usually includes lines with inconsistent directions, such as... Figure 3 The image shows both horizontal and vertical lines. Therefore, in cases where the test image contains lines with inconsistent orientations, to facilitate traversal, the following steps can be performed before performing pixel-by-pixel traversal of the lines and / or points in the first image:

[0113] The lines in the first image are classified, with lines in the same direction grouped into the same category and lines in different directions grouped into different categories. The direction of each type of line is then unified into a target direction, which can be set to horizontal or vertical depending on the actual situation.

[0114] As an example, taking the first image as containing horizontal and vertical lines, the horizontal lines are divided into one category and the vertical lines into another. If the target direction is horizontal, the vertical lines are rotated into horizontal lines, and if the target direction is vertical, the horizontal lines are rotated into vertical lines, thereby unifying the direction of all lines.

[0115] If the first image contains lines and the direction of the lines is uniformly the target direction, when performing pixel traversal on the lines and / or points contained in the first image, if the target direction is horizontal, the traversal is performed by column; if the target direction is vertical, the traversal is performed by row.

[0116] If the first image contains only points, it can be traversed by row or by column.

[0117] Different brightness levels typically correspond to different pixel values ​​in an image; a larger pixel value indicates greater brightness. The test image contains lines and / or dots, as well as a background. In the first image, lines and / or dots are brighter than the background, meaning their pixel values ​​are larger. Therefore, for each row or column, after traversing the pixels in that row or column, the pixels are sorted, the pixel peak of the pixel curve for that row or column is identified, and the pixel coordinates corresponding to the peak are recorded. The pixel peak contains the pixels corresponding to the lines and / or dots in that row or column.

[0118] Using the above method, we can obtain the pixel peak value and corresponding pixel coordinates of each row to which each line and / or each point belongs, or obtain the pixel peak value and corresponding pixel coordinates of each column to which each line and / or each point belongs.

[0119] Furthermore, for each row or column to which each line and / or each point belongs, the center pixel coordinates of the main body and the center pixel coordinates of the ghost image can be determined based on the pixel peak value corresponding to that row or column.

[0120] Typically, the brightness of the main body of a virtual image is greater than the brightness of the ghosted portion, while the brightness of the ghosted portion is greater than the brightness of the background. Based on this, the following steps can be performed to determine the center pixel coordinates of the main body and the center pixel coordinates of the ghosted portion for that row or column:

[0121] Determine the center pixel coordinates of the subject in the row or column by using the pixel coordinates corresponding to the maximum pixel value among the pixel peaks in that row or column.

[0122] Among the pixel peaks corresponding to that row or column, the pixel peak located between the preset ghosting threshold and the background threshold is determined as the first pixel peak.

[0123] The pixel coordinates corresponding to the maximum pixel value in the first pixel peak are determined as the pixel coordinates of the ghost center corresponding to that row or column.

[0124] The ghosting threshold and background threshold can be set according to the test environment and the test product. Generally, the ghosting threshold is not less than 40%, and the background threshold is not less than 10%. The pixel peak value located between the preset ghosting threshold and background threshold is determined as the first pixel peak value, which can be considered as the pixel value corresponding to the ghosting part.

[0125] Using the above method, based on the brightness differences presented by the virtual image's main body, the ghost image's shadow, and the background in the first image, a threshold method can be used to distinguish the main body's center and the ghost image's center in the first image, accurately determining the main body's center pixel coordinates and the ghost image's center pixel coordinates for each row or column.

[0126] In some embodiments, after obtaining the subject center pixel coordinates and ghost center pixel coordinates corresponding to each row or column to which each line and / or each point belongs, the ghost value corresponding to the head-up display device can be determined by executing S14.

[0127] In some embodiments, S14 may be implemented in the following ways:

[0128] For each row or column to which each line and / or each point in the first image belongs, the difference between the center pixel coordinates of the main subject and the center pixel coordinates of the ghost image corresponding to that row or column is determined as the ghost image value corresponding to that row or column.

[0129] For each line and / or each point in the first image, the ghost value with the highest probability among the ghost values ​​corresponding to the row or column to which that line or point belongs is determined as the ghost value corresponding to that line or point.

[0130] The maximum value among all lines and / or all points in the first image is determined as the ghost value corresponding to the head-up display device.

[0131] Specifically, for each row or column to which each line and / or each point in the first image belongs, the difference between the pixel coordinates of the subject center and the pixel coordinates of the ghost center corresponding to that row or column can be used as the ghost value corresponding to that row or column. The difference between the pixel coordinates of the subject center and the pixel coordinates of the ghost center is the distance between the subject center and the ghost center. This distance can be used to reflect the size of the ghost. Therefore, determining the difference between the pixel coordinates of the subject center and the pixel coordinates of the ghost center as the ghost value corresponding to that row or column can reflect the size of the ghost in each row or column.

[0132] For each line and / or point in the first image, when determining the ghost value corresponding to that line or point, the ghost values ​​of all rows or columns to which that line or point belongs can be recorded. Through statistical analysis, the ghost value with the highest probability of occurrence is determined from the recorded ghost values ​​and identified as the ghost value corresponding to that line or point. The higher the probability of occurrence, the better the degree of ghosting of that line or point can be guaranteed. Therefore, determining the ghost value with the highest probability of occurrence as the ghost value corresponding to that line or point is more accurate.

[0133] After obtaining the ghost values ​​corresponding to all lines and / or points, the maximum ghost value is determined as the ghost value corresponding to the head-up display device. This ensures higher accuracy when testing or designing the head-up display device based on the ghost value corresponding to the head-up display device.

[0134] In some embodiments, since the ghost value corresponding to the head-up display device obtained in S14 is based on pixels in the first image, it is actually a pixel value in the camera coordinate system corresponding to the image acquisition device. However, different image acquisition devices typically have different pixel sizes. Therefore, to understand this deviation value, it is necessary to know the pixel size corresponding to the image acquisition device. Consequently, the ghost value obtained in the above manner is not intuitive and is not easy for users to understand. Therefore, to make the ghost value corresponding to the head-up display device more intuitive and easier to understand, the following steps can be performed after S14:

[0135] The ghosting value corresponding to the head-up display device is converted according to a preset conversion formula to obtain the ghosting deviation angle corresponding to the head-up display device.

[0136] The conversion formulas include:

[0137]

[0138] In the formula, α represents the ghosting deviation angle, d represents the ghosting value before conversion, P represents the pixel size of the image acquisition device, and f represents the focal length of the image acquisition device.

[0139] The ghosting deviation angle obtained through transformation reflects the deviation angle between the main part of the virtual image and the ghosting part as seen by the human eye. The larger the ghosting deviation angle, the larger the ghosting, which is more intuitive.

[0140] See Figure 6 This is a schematic diagram of a preferred embodiment of a ghost detection method for a head-up display device provided in this application, as shown below. Figure 6 As shown, it may include the following steps S61-S69.

[0141] S61. Turn on the head-up display device and adjust its brightness to a reasonable range to project the test image used for ghosting detection onto the windshield.

[0142] S62. Adjust the position of the image acquisition device by means of the image acquisition device fixing device so that the optical center of the image acquisition device is located at the middle eye position of the driver's middle eye box in the vehicle coordinate system.

[0143] S63. Use an image acquisition device to capture a virtual image of the test image projected onto the windshield.

[0144] S64. Perform contour recognition on the image captured by the image acquisition device to segment each line or point.

[0145] S65. For each line or point, perform pixel traversal by column or row, find the peak value of the pixel curve in each column or row, and record its coordinate position.

[0146] S66. Process the peak value of each column or row of pixels to obtain the coordinates of the main body center and the position coordinates of the ghost center.

[0147] S67. Perform statistical analysis on the ghost values ​​of all columns or rows to which each line or point belongs, and take the ghost value with the highest probability as its ghost value.

[0148] S68. Statistically analyze the ghost values ​​of all lines or points in the images captured by the image acquisition device, and determine the largest ghost value as the ghost value d of the head-up display device.

[0149] S69. Transform the ghost value d to obtain the final ghost value α.

[0150] The implementation methods for each step can be found in the above examples, and will not be elaborated further here to avoid repetition.

[0151] Based on the ghosting detection method for head-up display devices provided in the above embodiments, this application also provides specific implementation methods for a ghosting detection device for head-up display devices. Please refer to the following embodiments.

[0152] See Figure 7 The ghost detection device for head-up display provided in this application includes the following modules:

[0153] Image projection module 701 is used to project a test image onto a windshield based on a head-up display device, wherein the test image includes an array of lines and / or dots.

[0154] The image acquisition module 702 is used to capture a virtual image of the test image projected onto the windshield based on the image acquisition device, and obtain a first image containing the virtual image.

[0155] The pixel traversal module 703 is used to perform pixel traversal on the lines and / or points contained in the first image, and obtain the main center pixel coordinates and ghost center pixel coordinates corresponding to each row or column to which each line and / or each point in the first image belongs.

[0156] The device ghost value determination module 704 is used to determine the ghost value corresponding to the head-up display device based on the difference between the main center pixel coordinates and the ghost center pixel coordinates corresponding to each row or column to which each line and / or each point belongs.

[0157] The ghosting detection device for head-up display (HUD) devices in this application embodiment, after projecting a virtual image of a test image onto the windshield based on the HUD device, captures the virtual image using an image acquisition device to obtain a first image containing the virtual image. By traversing the lines and / or points in the first image, the device determines the pixel coordinates of the main body center of the virtual image and the pixel coordinates of the ghosting center of the ghosting portion in each row or column of each line and / or point in the first image. Based on the difference between the pixel coordinates of the main body center and the ghosting center, the ghosting value corresponding to the HUD device is determined. According to this application embodiment, the ghosting size can be tested and evaluated before the HUD device leaves the factory, thus intercepting defective products within the factory and ensuring that the ghosting value of the HUD devices leaving the factory is within the specified range, guaranteeing the actual use effect of the HUD device and improving the driving comfort and safety of the driver. In addition, the ghosting effect of the HUD device can also be evaluated during the design verification stage to help R&D personnel make design improvements.

[0158] In some embodiments, the head-up display device ghost detection device may further include (not shown in the figure):

[0159] The image processing module is used to perform Gaussian filtering on the first image before performing pixel traversal on the lines and / or points contained in the first image.

[0160] Based on image processing algorithms, contour recognition and image segmentation are performed on the first image after Gaussian filtering to obtain each line and / or each point in the first image.

[0161] In some embodiments, the pixel traversal module 703 includes:

[0162] The peak value determination submodule is used to perform pixel traversal on the lines and / or points contained in the first image to obtain the pixel peak value corresponding to each row or column to which each line and / or each point belongs in the first image, and to record the pixel coordinates of the pixel peak value.

[0163] The center determination submodule is used to determine the main body center pixel coordinates and ghost center pixel coordinates for each row or column to which each line and / or each point belongs in the first image, based on the pixel peak value corresponding to that row or column.

[0164] In some embodiments, the central determining submodule is used for:

[0165] Determine the center pixel coordinates of the subject in that row or column by using the pixel coordinates corresponding to the maximum pixel value among the pixel peaks in that row or column.

[0166] Among the pixel peaks corresponding to that row or column, the pixel peak located between the preset ghosting threshold and the background threshold is determined as the first pixel peak.

[0167] The pixel coordinates corresponding to the maximum pixel value in the first pixel peak are determined as the pixel coordinates of the ghost center corresponding to that row or column.

[0168] In some embodiments, the device ghost value determination module 704 includes:

[0169] The row and column ghost value determination submodule is used to determine the ghost value corresponding to each row or column for each line and / or each point in the first image, based on the difference between the main body center pixel coordinates and the ghost center pixel coordinates.

[0170] The dot-line ghosting value determination submodule is used to determine the dot-line value or ...

[0171] The device ghost value determination submodule is used to determine the maximum value among all lines and / or all points in the first image as the ghost value corresponding to the head-up display device.

[0172] In some embodiments, the head-up display device ghost detection device may further include (not shown in the figure):

[0173] The conversion module is used to convert the ghost value corresponding to the head-up display device according to a preset conversion formula to obtain the ghost deviation angle corresponding to the head-up display device.

[0174] The conversion formulas include:

[0175]

[0176] In the formula, α represents the ghosting deviation angle, d represents the ghosting value before conversion, P represents the pixel size of the image acquisition device, and f represents the focal length of the image acquisition device.

[0177] In some embodiments, the head-up display device ghost detection apparatus may further include (not shown in the figure): a distortion correction module, used for:

[0178] The test image is distorted before being projected onto the windshield using a head-up display device.

[0179] Correspondingly, the image projection module 701 is used for:

[0180] The distortion-corrected test image is projected onto the windshield using a head-up display device.

[0181] In some embodiments, the head-up display device ghost detection device may further include (not shown in the figure):

[0182] The equipment adjustment module is used to adjust the position of the head-up display device and / or the image acquisition device before obtaining the first image by acquiring a virtual image of the test image projected onto the windshield based on the image acquisition device. This ensures that the virtual image projected onto the windshield by the test image captured by the image acquisition device is complete, its tilt angle is less than a preset tilt angle threshold, and / or its exposure is less than a preset exposure threshold.

[0183] Accordingly, the image acquisition module 702 is used for:

[0184] After adjusting the head-up display and / or image acquisition device, the first image is obtained by acquiring a virtual image of the test image projected onto the windshield using the image acquisition device.

[0185] The head-up display ghost detection device provided in this application embodiment can realize the various processes implemented in the above-described head-up display ghost detection method embodiments, and will not be described again here to avoid repetition.

[0186] Figure 8 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.

[0187] Electronic devices may include a processor 801 and a memory 802 storing computer program instructions.

[0188] Specifically, the processor 801 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0189] Memory 802 may include mass storage for data or instructions. For example, and not limitingly, memory 802 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 802 may include removable or non-removable (or fixed) media. Where appropriate, memory 802 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 802 is non-volatile solid-state memory.

[0190] Memory 802 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, typically, memory 802 includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it can perform the operations described in any of the head-up display device ghosting detection methods in the above embodiments.

[0191] The processor 801 reads and executes computer program instructions stored in the memory 802 to implement any of the head-up display device ghost detection methods in the above embodiments.

[0192] In one example, the electronic device may also include a communication interface 803 and a bus 810. For example, Figure 8 As shown, the processor 801, memory 802, and communication interface 803 are connected through bus 810 and complete communication with each other.

[0193] The communication interface 803 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0194] Bus 810 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 810 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0195] Furthermore, in conjunction with the head-up display device ghosting detection method in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions, which, when executed by a processor, implement any of the head-up display device ghosting detection methods in the above embodiments.

[0196] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0197] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0198] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0199] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0200] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for detecting ghosting in a head-up display device, characterized in that, include: A test image is projected onto the windshield using a head-up display device, wherein the test image includes an array of lines and / or dots. A first image containing the virtual image is obtained by capturing a virtual image of the test image projected onto the windshield using an image acquisition device. By performing pixel traversal on the lines and / or points contained in the first image, the main center pixel coordinates and ghost center pixel coordinates corresponding to each row or column to which each line and / or point belongs in the first image are obtained. The ghost value corresponding to the head-up display device is determined based on the difference between the main center pixel coordinates and the ghost center pixel coordinates corresponding to each row or column to which each line and / or each point belongs. The step of performing pixel traversal on the lines and / or points contained in the first image to obtain the main center pixel coordinates and ghost center pixel coordinates corresponding to each row or column to which each line and / or point belongs includes: For each line and / or each point contained in the first image, perform pixel traversal to obtain the pixel peak value corresponding to each row or column to which each line and / or each point belongs, and record the pixel coordinates of the pixel peak value. For each row or column to which each line and / or each point in the first image belongs, the main body center pixel coordinates and the ghost center pixel coordinates corresponding to the row or column are determined based on the pixel peak value corresponding to that row or column. The step of determining the main body center pixel coordinates and ghost center pixel coordinates corresponding to the row or column based on the pixel peak value of the row or column includes: Determine the center pixel coordinates of the subject in that row or column by using the pixel coordinates corresponding to the maximum pixel value among the pixel peaks in that row or column. Among the pixel peaks corresponding to that row or column, the pixel peak located between the preset ghosting threshold and the background threshold is determined as the first pixel peak. The pixel coordinates corresponding to the maximum pixel value in the first pixel peak are determined as the pixel coordinates of the ghost center corresponding to that row or column.

2. The method according to claim 1, characterized in that, Before performing pixel traversal of the lines and / or points contained in the first image, the method further includes: Apply Gaussian filtering to the first image. Based on image processing algorithms, contour recognition and image segmentation are performed on the first image after Gaussian filtering to obtain each line and / or each point in the first image.

3. The method according to claim 1 or 2, characterized in that, The step of determining the ghost value corresponding to the head-up display device based on the difference between the main center pixel coordinates and the ghost center pixel coordinates corresponding to each row or column to which each line and / or each point belongs includes: For each row or column to which each line and / or each point in the first image belongs, the difference between the center pixel coordinates of the main subject and the center pixel coordinates of the ghost image corresponding to that row or column is determined as the ghost image value corresponding to that row or column. For each line and / or each point in the first image, the ghost value with the highest probability of occurrence among the ghost values ​​corresponding to the row or column to which the line or point belongs is determined as the ghost value corresponding to that line or point. The maximum value among the ghost values ​​corresponding to all lines and / or all points in the first image is determined as the ghost value corresponding to the head-up display device.

4. The method according to claim 3, characterized in that, The method further includes: The ghost value corresponding to the head-up display device is converted according to a preset conversion formula to obtain the ghost deviation angle corresponding to the head-up display device. The conversion formula includes: In the formula, Indicates the ghosting deviation angle. This represents the ghosting value before conversion. Indicates the pixel size of the image acquisition device. This indicates the focal length of the image acquisition device.

5. The method according to claim 1, characterized in that, Before the test image is projected onto the windshield using the head-up display device, the method further includes: Distortion correction is performed on the test image. The projection of the test image onto the windshield based on the head-up display device includes: The distortion-corrected test image is projected onto the windshield using a head-up display device.

6. The method according to claim 1, characterized in that, Before obtaining the first image by acquiring a virtual image of the test image projected onto the windshield using an image acquisition device, the method further includes: Adjust the position of the head-up display device and / or the image acquisition device so that the virtual image projected onto the windshield based on the test image captured by the image acquisition device is complete, the tilt angle is less than a preset tilt angle threshold, and / or the exposure is less than a preset exposure threshold. The first image is obtained by acquiring a virtual image of the test image projected onto the windshield using an image acquisition device, including: After adjusting the head-up display device and / or the image acquisition device, a first image is obtained by acquiring a virtual image of the test image projected onto the windshield based on the image acquisition device.

7. A ghosting detection device for a head-up display device, characterized in that, include: An image projection module is used to project a test image onto a windshield based on a head-up display device, wherein the test image includes an array of lines and / or dots. The image acquisition module is used to capture a virtual image of the test image projected onto the windshield based on the image acquisition device, thereby obtaining a first image containing the virtual image. The pixel traversal module is used to perform pixel traversal on the lines and / or points contained in the first image, and obtain the main center pixel coordinates and ghost center pixel coordinates corresponding to each row or column to which each line and / or each point belongs in the first image. The device ghost value determination module is used to determine the ghost value corresponding to the head-up display device based on the difference between the main center pixel coordinates and the ghost center pixel coordinates corresponding to each row or column to which each line and / or each point belongs. The pixel traversal module includes: The peak value determination submodule is used to perform pixel traversal on the lines and / or points contained in the first image to obtain the pixel peak value corresponding to each row or column to which each line and / or each point belongs in the first image, and to record the pixel coordinates of the pixel peak value. The center determination submodule is used to determine the main body center pixel coordinates and ghost center pixel coordinates for each row or column to which each line and / or each point belongs in the first image, based on the pixel peak value corresponding to that row or column. The central determination submodule is used for: Determine the center pixel coordinates of the subject in that row or column by using the pixel coordinates corresponding to the maximum pixel value among the pixel peaks in that row or column. Among the pixel peaks corresponding to that row or column, the pixel peak located between the preset ghosting threshold and the background threshold is determined as the first pixel peak. The pixel coordinates corresponding to the maximum pixel value in the first pixel peak are determined as the pixel coordinates of the ghost center corresponding to that row or column.

8. An electronic device, characterized in that, The electronic device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the ghosting detection method for head-up display devices as described in any one of claims 1-6.

Images