MicroLED vehicle lamp control method supporting user-defined animation projection

Abstract

The invention belongs to a car lamp control technology, and particularly relates to a Micro LED car lamp control method supporting user-defined animation projection, which comprises the following steps: a user uploads an animation file specified by the user through an interactive terminal, and a system automatically detects a file format; analyzing the animation file, separating an audio stream and a video stream of the animation, extracting a frame sequence in the video stream, and decoding the frame sequence into a picture; auditing the decoded picture through a deep learning model, and automatically shielding a sensitive pattern in the picture; the resolution of each frame of picture is adjusted to be equal to the resolution of the Micro LED vehicle lamp through interpolation or sampling; and transmitting the projection content to a Micro LED driver according to a specified frame rate to realize pixel-level light control. According to the method, the user is allowed to load and project animation files in the formats of GIF, MP4 and the like in real time, the limitation of preset contents of manufacturers is broken through, on the premise that the privacy and compliance of the user are guaranteed, automatic auditing and matching of the animation contents are achieved, and finally the effect of linkage of'projection and sound effect 'is achieved.

Description

Technical Field

[0001] This invention pertains to vehicle lighting control technology, and particularly relates to a Micro LED vehicle lighting control method that supports user-defined animation projection. Background Technology

[0002] Automotive lighting technology is currently at a critical stage of transformation, shifting from basic function-driven to intelligent human-machine interaction. With the rapid improvement of automotive intelligence and the increasing demand for personalized experiences from consumers, traditional single-function lighting systems can no longer meet market needs. In this wave of technological change, megapixel-level Micro LED headlights, with their superior display performance and precise pixel-level light control capabilities, are rapidly becoming a differentiating feature in mid-to-high-end intelligent electric vehicles.

[0003] However, existing Micro LED automotive lights still have limitations. The projected content is mostly fixed patterns such as navigation arrows and welcome animations preset by the manufacturer, lacking user customization capabilities. They cannot load and project user-specified animation content in real time, and can only achieve visual projection, lacking audio synchronization function, resulting in a single dimension of information transmission. Summary of the Invention

[0004] The technical problem that this invention aims to solve is that existing vehicle headlight projection content is limited.

[0005] Therefore, the present invention provides a MicroLED vehicle light control method that supports user-defined animation projection.

[0006] The technical solution adopted by this invention to solve its technical problem is:

[0007] A method for controlling Micro LED vehicle lights that supports user-defined animation projection, comprising:

[0008] Step 1: The user uploads the animation file specified by the user through the interactive terminal, and the system automatically detects the file format;

[0009] Step two: Use the FFmpeg open-source library to parse the animation file, separate the audio and video streams of the animation, extract the frame sequence from the video stream and decode it into images;

[0010] Step 3: The decoded images are reviewed using a deep learning model, and sensitive patterns in the images are automatically blocked.

[0011] Step four: Adjust the resolution of each frame of the image to the same resolution as the Micro LED headlights through interpolation or sampling;

[0012] Step 5: Transmit the projected content to the Micro LED driver at the specified frame rate via vehicle Ethernet or CAN bus to achieve pixel-level light control.

[0013] Furthermore, in step two, the decoding step can be accelerated by hardware such as NVENC / QSV to meet the real-time requirements. If no such acceleration hardware is available, the software decoding method of libx264 is used.

[0014] Furthermore, in step two, if the frame rate of the animation file exceeds the fastest refresh rate of the Micro LED vehicle lights, then frame dropping is performed.

[0015] Furthermore, in step three, the deep learning object detection model identifies target objects in the image, obtains the target category, confidence level, and bounding box coordinates, and then filters the detection results according to preset sensitive content, processing targets with confidence levels exceeding a threshold.

[0016] Furthermore, in step three, the identified sensitive content areas are blurred or made completely black by using pixel-level masks or rectangular black blocks to ensure that the privacy information is unidentifiable.

[0017] Furthermore, in step four, if the resolution of the image processed in step three exceeds the maximum resolution supported by the MicroLED vehicle headlight, downsampling is performed; otherwise, upsampling is performed.

[0018] Furthermore, in step four, if the aspect ratio of the input image after processing in step three is inconsistent with that of the headlight display area, then fill and crop operations are performed to ensure that the image is not distorted and that key content is displayed in the center.

[0019] Furthermore, in step four, the ambient light intensity is acquired in real time by the vehicle-mounted ambient light sensor and divided into different light levels. In strong light environments, the overall grayscale value of the image is increased to offset the weakening effect of ambient light on the projection effect and ensure that the content is clearly visible. In low light environments, the image grayscale value is reduced to avoid glare caused by overly bright projection, which may affect the vision of the driver or pedestrians.

[0020] Furthermore, in step five, the image data after size and brightness adaptation in step four is encapsulated by frame sequence number + timestamp via vehicle Ethernet or CAN bus, and a CRC check code is added to each frame to prevent transmission errors.

[0021] Furthermore, in step five, the audio separated in step two is synchronously transmitted to the vehicle audio system to achieve "projection + sound effect" linkage. Before the audio is played, it is first stored in the buffer and then output after a delay of T ms to compensate for the delay time of image processing.

[0022] The beneficial effects of this invention are that the Micro LED vehicle light system and control method proposed in this invention, which supports user-defined animation projection, allows users to load and project animation files in formats such as GIF and MP4 in real time, breaking through the limitations of manufacturer-preset content. Under the premise of protecting user privacy and compliance, it realizes the automated review and adaptation of animation content, and ultimately achieves the effect of "projection + sound effect" linkage. Attached Figure Description

[0023] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0024] Figure 1 This is a flowchart of a Micro LED vehicle light control method for user-defined animation projection provided in an embodiment of the present invention.

[0025] Figure 2 This is a Micro LED vehicle lighting system with user-defined animation projection provided in this embodiment of the invention. Detailed Implementation

[0026] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, illustrating only the basic structure of the invention, and therefore only show the components relevant to the invention.

[0027] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, features defined with "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0028] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0029] A MicroLED vehicle headlight control method that supports user-defined animation projection is implemented based on a vehicle headlight control system. The vehicle headlight control system includes an interactive terminal, a headlight control server, and a headlight driver. The interactive terminal is connected to the headlight driver through the headlight control server.

[0030] Step 1: The user uploads the animation file specified by the user through the interactive terminal, and the system automatically detects the file format;

[0031] Users select the desired animation file for projection via an interactive terminal (such as a smartphone, in-vehicle central control screen, tablet, or other operable device with a graphical interface). These animation files must conform to mainstream video format standards, such as MP4, AVI, MOV, and other common container formats, and it is recommended to use widely compatible video encoding schemes such as H.264 or H.265 to ensure parsing stability. After the user completes the file selection, the system will upload the file to the vehicle lighting control server deployed within the intelligent cockpit operating system via an encrypted transmission protocol (such as HTTPS or a dedicated in-vehicle communication protocol). This service process, as a core system service that resides in the background, has multi-threaded processing capabilities and resource scheduling priority. It is specifically responsible for receiving user commands, verifying file integrity, parsing media data, and converting the visualized data into executable commands for the vehicle lighting drive module according to the preset animation processing flow.

[0032] Step two: Use the FFmpeg open-source library to parse the animation file, separate the audio and video streams of the animation, extract the frame sequence from the video stream and decode it into images;

[0033] The vehicle lighting control server uses the FFmpeg library to separate the audio and video of the animation, parsing the video file's frame rate, resolution, encoding format, and the encoded image content of each frame. Then, it performs corresponding decoding operations on each frame to obtain the image data. FFmpeg is an open-source, cross-platform multimedia processing framework. Encoding refers to the method of compressing video stream data (H.264 / H.265, etc.) to reduce its storage space; corresponding decoding operations are needed to extract the complete images. The decoding step can be accelerated using hardware such as NVENC / QSV to meet real-time requirements; otherwise, software decoding using libx264 is used. If the animation file's frame rate exceeds the fastest refresh rate of the Micro LED vehicle lights, frame dropping is performed.

[0034] Step 3: Review the images decoded in Step 2 using a deep learning model and block sensitive patterns;

[0035] After step two completes the parsing of the animation file, the system inputs the extracted image data frame by frame into a pre-trained deep learning object detection model for inference to detect whether the image contains sensitive content (such as faces, license plates, specific logos, or other elements involving privacy or compliance issues). Specifically, each parsed frame is input into the model to obtain the target category, confidence score, and bounding box coordinates. Then, the detection results are filtered according to preset rules (such as faces, license plates, specific logos, etc.), and only targets with a confidence score exceeding a threshold (such as 0.7) are processed. For areas determined to be sensitive content, pixel-level masks or rectangular black blocks are used for blurring or pure blacking to ensure that privacy information is unidentifiable.

[0036] The deep learning object detection model can employ the open-source YOLO / Transformer series of algorithms. The training process of the deep learning object detection model is as follows:

[0037] Data collection: Filter from some social media images, or choose open source datasets such as FDDB / CCPD;

[0038] Data annotation (if the images are collected from social media, they need to be labeled using open-source image annotation tools such as Labelme);

[0039] The model was trained using an open-source image detection model (such as YOLO v12).

[0040] Step 4: Adjust the resolution of each frame of the image to the same resolution as the Micro LED car lights through interpolation or sampling, and dynamically adjust the brightness of the projected content according to the vehicle environment.

[0041] The resolution of the image after desensitization in step three (e.g., 2560×1440) is checked. If it exceeds the maximum resolution supported by the Micro LED headlights (e.g., 960×540), downsampling is performed; otherwise, upsampling is performed. If the aspect ratio of the input image is inconsistent with the headlight display area, filling and cropping operations are performed to ensure that the image is not distorted and that key content is centered. The intensity value of the ambient light sensor (e.g., BH1750) is obtained from the vehicle's CAN bus via the I2C interface and classified into different light levels. In strong light environments, the overall grayscale value of the image is increased (e.g., an overall brightness increase of 20%) to offset the weakening effect of ambient light on the projection effect and ensure that the content is clearly visible. In low light environments, the image grayscale value is reduced to avoid glare caused by excessively bright projection, which may affect the driver's or pedestrians' vision.

[0042] Step 5: The image data after size and brightness adaptation in Step 4 is encapsulated by frame sequence number + timestamp via vehicle Ethernet or CAN bus. Each frame is appended with a CRC check code to prevent transmission errors. The data is then transmitted to the Micro LED driver at the original video frame rate to achieve pixel-level light control.

[0043] Simultaneously, the audio separated in step two is transmitted to the vehicle audio system to achieve "projection + sound effect" linkage. Since the image has undergone decoding, model desensitization, and size / brightness adaptation, it will have a certain delay (such as T ms) compared to the audio. Therefore, before the audio is played, it is first stored in the buffer and output after a delay of T ms to achieve a better audio-visual synchronization effect.

[0044] In this embodiment, the Micro LED vehicle lighting control system that supports user-defined animation projection is as follows: Figure 2 As shown. The interactive terminal refers to operable devices with graphical interfaces, such as smartphones, in-vehicle central control screens, and tablets. The headlight control server service is a software process running on the cockpit operating system, possessing multi-threaded processing capabilities and resource scheduling priorities. It is specifically responsible for receiving user commands, verifying file integrity, parsing media data, and converting visual data into executable commands for the headlight driver module according to a preset animation processing flow. The headlight driver is the controller within the Micro LED headlight, capable of parsing and executing headlight control commands, enabling the headlight to project fixed patterns of light based on the content of the image (the grayscale value of each pixel in a 960×540 resolution image corresponds to the brightness of one LED bead).

[0045] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined by the scope of the claims.

Claims

1. A Micro LED vehicle light control method supporting user-defined animation projection, characterized in that, include, Step 1: The user uploads the animation file specified by the user through the interactive terminal, and the system automatically detects the file format; Step two: Use the FFmpeg open-source library to parse the animation file, separate the audio and video streams of the animation, extract the frame sequence from the video stream and decode it into images; Step 3: The decoded images are reviewed using a deep learning model, and sensitive patterns in the images are automatically blocked. Step four: Adjust the resolution of each frame of the image to the same resolution as the Micro LED headlights through interpolation or sampling; Step 5: Transmit the projected content to the Micro LED driver at the specified frame rate via vehicle Ethernet or CAN bus to achieve pixel-level light control.

2. The Micro LED vehicle light control method supporting user-defined animation projection according to claim 1, characterized in that, In step two, the decoding step is accelerated by NVENC or QSV hardware to meet the real-time requirements. If no acceleration hardware is available, the software decoding method of libx264 is used.

3. The Micro LED vehicle light control method supporting user-defined animation projection according to claim 2, characterized in that, In step two, if the frame rate of the animation file exceeds the fastest refresh rate of the Micro LED car lights, then frame dropping is performed.

4. The Micro LED vehicle light control method supporting user-defined animation projection according to claim 1, characterized in that, In step three, the deep learning object detection model identifies target objects in the image, obtains the target category, confidence level, and bounding box coordinates, and then filters the detection results according to preset sensitive content, processing targets with confidence levels exceeding a threshold.

5. The Micro LED vehicle light control method supporting user-defined animation projection according to claim 4, characterized in that, In step three, the identified sensitive content areas are blurred or made completely black by using pixel-level masks or rectangular black blocks to ensure that the privacy information is unidentifiable.

6. The Micro LED vehicle light control method supporting user-defined animation projection according to claim 1, characterized in that, In step four, if the resolution of the image after step three exceeds the maximum resolution supported by the Micro LED vehicle headlights, downsampling is performed; otherwise, upsampling is performed.

7. The Micro LED vehicle light control method supporting user-defined animation projection according to claim 6, characterized in that, In step four, if the aspect ratio of the input image to the vehicle headlight display area is inconsistent after the image resolution processed in step three, then fill and crop operations are performed to ensure that the image is not distorted and that key content is displayed in the center.

8. The Micro LED vehicle light control method supporting user-defined animation projection according to claim 7, characterized in that, In step four, the ambient light intensity is acquired in real time by the vehicle-mounted ambient light sensor and divided into different light levels. In strong light environments, the overall grayscale value of the image is increased to offset the weakening effect of ambient light on the projection effect and ensure that the content is clearly visible. In low light environments, the grayscale value of the image is reduced to avoid glare caused by overly bright projection, which may affect the vision of the driver or pedestrians.

9. The Micro LED vehicle light control method supporting user-defined animation projection according to claim 1, characterized in that, In step five, the image data after size and brightness adaptation in step four is encapsulated by frame sequence number + timestamp via vehicle Ethernet or CAN bus, and a CRC check code is added to each frame to prevent transmission errors.

10. The Micro LED vehicle light control method supporting user-defined animation projection according to claim 9, characterized in that, In step five, the audio separated in step two is synchronously transmitted to the vehicle audio system to achieve "projection + sound effect" linkage. Before the audio is played, it is first stored in the buffer and then output after a delay of T ms to compensate for the delay time of image processing.

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