CN117689620A - Image processing method, device, terminal equipment and storage medium - Google Patents
Image processing method, device, terminal equipment and storage medium Download PDFInfo
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Abstract
The application discloses an image processing method, an image processing device, terminal equipment and a storage medium, and relates to the field of intelligent auxiliary driving, wherein the method comprises the following steps: acquiring an intelligent driving auxiliary system signal; based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image; based on a monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image; based on the monitoring image processing component, the intelligent driving auxiliary system image and the monitoring image are compared to obtain a comparison result, and the safety of ADAS display is improved.
Description
Technical Field
The present disclosure relates to the field of intelligent driving assistance, and in particular, to an image processing method, an image processing device, a terminal device, and a storage medium.
Background
ADAS (Advanced Driving Assistance System, intelligent assisted driving system) is an automotive safety system employing advanced technology, aimed at providing driver assistance and enhancing driving experience. The system senses the surrounding environment by using devices such as a sensor, a camera, a radar, a computer and the like, and provides warning, automatic control or assisting operation for a driver through data processing and algorithm analysis. For example, real-time warning and support of the driver for forward traffic conditions may be provided by active braking, adaptive cruise control, lane keeping assistance, and the like.
The instrument display or the head-up display is used for providing information about the state of the vehicle, the driving environment and the running condition of the system for the driver in the ADAS, so that the driver is helped to better understand and control the whole driving process, and the head-up display plays a vital role. However, no safety design is currently made on the display of the ADAS on the meter or the head-up display, so that potential safety hazards exist, and the ADAS cannot meet the functional safety requirements, so that the life safety of drivers and passengers is endangered.
Disclosure of Invention
The main object of the present application is to provide an image processing method, an image processing device, a terminal device and a storage medium, which aim to improve security of ADAS display.
To achieve the above object, the present application provides an image processing method including:
acquiring an intelligent driving auxiliary system signal;
based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image;
based on a monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image;
and comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing component to obtain a comparison result.
Optionally, the step of acquiring the intelligent driving assistance system signal further includes:
according to a preset time period and a signal identity number rule, grouping and aggregating the acquired intelligent driving assistance system signals to acquire grouped and aggregated intelligent driving assistance system signals;
the step of performing image rendering on the intelligent driving assistance system signal based on the intelligent driving assistance system image processing component to obtain an intelligent driving assistance system image comprises the following steps:
based on the intelligent driving assistance system image processing component, performing image rendering on the grouped and aggregated intelligent driving assistance system signals to obtain the intelligent driving assistance system image;
the step of performing image rendering on the intelligent driving auxiliary system signal based on the monitoring image processing component to obtain a monitoring image comprises the following steps:
and based on the monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signals after grouping and aggregation to obtain the monitoring image.
Optionally, the step of comparing the intelligent driving assistance system image with the monitoring image based on the monitoring image processing component to obtain a comparison result includes:
Based on the monitoring image processing component, comparing the intelligent driving auxiliary system image with the monitoring image at a pixel level to obtain a picture difference value;
and comparing the picture difference value with a preset difference threshold value to obtain the comparison result.
Optionally, the step of comparing the intelligent driving assistance system image with the monitoring image based on the monitoring image processing component to obtain a comparison result further includes:
and if the comparison result is passed, performing cyclic redundancy check on the intelligent driving auxiliary system image and the monitoring image to obtain a check result.
Optionally, if the comparison result is passing, performing cyclic redundancy check on the intelligent driving assistance system image and the monitoring image, and after the step of obtaining the check result, further including:
and if the check result is passed, sending the intelligent driving assistance system image to a display screen component for display.
Optionally, the step of comparing the intelligent driving assistance system image with the monitoring image based on the monitoring image processing component to obtain a comparison result includes:
And if the comparison result is not passed, sending out signal fault information.
Optionally, the acquiring the intelligent driving assistance system signal includes:
the method comprises the steps of obtaining signals through a camera and a radar, obtaining physical information and sending the physical information to an electronic control unit ECU;
based on the ECU, converting the physical information into an intelligent driving auxiliary system signal and sending the intelligent driving auxiliary system signal to a Micro Controller Unit (MCU);
and based on the MCU, carrying out signal function safety inspection on the intelligent driving assistance system signal, and sending the intelligent driving assistance system signal to a system-on-chip (SOC) when the intelligent driving assistance system signal passes the safety inspection, wherein the SOC comprises the intelligent driving assistance system image processing component and the monitoring image processing component.
The embodiment of the application also provides an image processing device, which comprises:
the information acquisition module is used for acquiring signals of the intelligent driving auxiliary system;
the intelligent driving assistance system image processing module is used for performing image rendering on the intelligent driving assistance system signal based on the intelligent driving assistance system image processing component to obtain an intelligent driving assistance system image;
The monitoring image processing module is used for carrying out image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image;
and the monitoring image processing module is also used for comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing assembly to obtain a comparison result.
The embodiment of the application also provides a terminal device, which comprises a memory, a processor and an image processing program stored on the memory and capable of running on the processor, wherein the image processing program realizes the steps of the image processing method when being executed by the processor.
The embodiments of the present application also propose a computer-readable storage medium on which an image processing program is stored, which when executed by a processor implements the steps of the image processing method as described above.
The image processing method, the device, the terminal equipment and the storage medium provided by the embodiment of the application acquire the intelligent driving auxiliary system signal; based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image; based on a monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image; and comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing component to obtain a comparison result. After the intelligent driving assistance system signal is obtained, the rendering processing mode of the ADAS signal designed by the original ADAS system is changed into the synchronous rendering processing mode of the intelligent driving assistance system signal through the intelligent driving assistance system image processing component and the monitoring image processing component, the intelligent driving assistance system image and the monitoring image are obtained, and the comparison result is obtained by comparing the intelligent driving assistance system image and the monitoring image. It can be understood that after the same image signal is rendered and output by different rendering modes, the original image (the image of the intelligent driving auxiliary system) can be monitored for failure by comparing the differences of the rendering and output of the two different modes, so that the design meeting the functional safety requirements is met, and the safety of ADAS display is improved.
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FIG. 1 is a schematic diagram of functional modules of a terminal device to which an image processing apparatus of the present application belongs;
FIG. 2 is a flowchart of a first exemplary embodiment of an image processing method of the present application;
FIG. 3 is a schematic diagram of an image processing hardware flow according to the present application;
FIG. 4 is a schematic diagram of a synchronous rendering flow of an intelligent driving assistance system image processing module and a monitoring image processing module according to the present application;
fig. 5 is a schematic diagram of an image processing flow of the KANZI module and the OPENGL module according to the present application.
The realization, functional characteristics and advantages of the present application will be further described with reference to the embodiments, referring to the attached drawings.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The main solutions of the embodiments of the present application are: acquiring an intelligent driving auxiliary system signal; based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image; based on a monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image; and comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing component to obtain a comparison result. After the intelligent driving assistance system signal is obtained, the rendering processing mode of the ADAS signal designed by the original ADAS system is changed into the synchronous rendering processing mode of the intelligent driving assistance system signal through the intelligent driving assistance system image processing component and the monitoring image processing component, the intelligent driving assistance system image and the monitoring image are obtained, and the comparison result is obtained by comparing the intelligent driving assistance system image and the monitoring image. It can be understood that after the same image signal is rendered and output by different rendering modes, the original image (the image of the intelligent driving auxiliary system) can be monitored for failure by comparing the differences of the rendering and output of the two different modes, so that the design meeting the functional safety requirements is met, and the safety of ADAS display is improved.
In the embodiment of the application, an intelligent auxiliary driving system (Advanced Driving Assistance System, ADAS) is an automobile safety system adopting advanced technology, and aims to provide an auxiliary function for a driver and enhance driving experience. The system senses the surrounding environment by using devices such as a sensor, a camera, a radar, a computer and the like, and provides warning, automatic control or assisting operation for a driver through data processing and algorithm analysis. For example, real-time warning and support of the driver for forward traffic conditions may be provided by active braking, adaptive cruise control, lane keeping assistance, and the like.
The instrument display or the head-up display is used for providing information about the state of the vehicle, the driving environment and the running condition of the system for the driver in the ADAS, so that the driver is helped to better understand and control the whole driving process, and the head-up display plays a vital role. However, no safety design is currently made on the display of the ADAS on the meter or the head-up display, so that potential safety hazards exist, and the ADAS cannot meet the functional safety requirements, so that the life safety of drivers and passengers is endangered.
Based on this, the embodiment of the application proposes a solution, after the intelligent driving assistance system signal is obtained, the original ADAS signal designed by the ADAS system is only rendered by the intelligent driving assistance system image processing component, and the intelligent driving assistance system image and the monitoring image are obtained by changing the processing mode of synchronously rendering the intelligent driving assistance system signal by the intelligent driving assistance system image processing component and the monitoring image processing component, and the comparison result is obtained by comparing the intelligent driving assistance system image and the monitoring image. It can be understood that after the same image signal is rendered and output by different rendering modes, the original image (the image of the intelligent driving assistance system) can be monitored for failure by comparing the differences of the rendering and output of the two different modes, so that the design meeting the functional safety requirements is satisfied.
Specifically, referring to fig. 1, fig. 1 is a schematic functional block diagram of a terminal device to which an image processing apparatus of the present application belongs. The image processing device may be a device independent of the terminal device and capable of performing data processing, or may be carried on the terminal device in a form of hardware or software.
In this embodiment, the terminal device to which the image processing apparatus belongs includes at least an output module 110, a processor 120, a memory 130, and a communication module 140.
The memory 130 stores an operating system and an image processing program, and acquires an intelligent driving assistance system signal; based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image; based on a monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image; based on the monitoring image processing component, comparing the intelligent driving assistance system image with the monitoring image to obtain a comparison result and storing the comparison result in the memory 130; the output module 110 may be a display screen, a speaker, etc. The communication module 140 may include a WIFI module, a mobile communication module, a bluetooth module, and the like, and communicates with an external device or a server through the communication module 140.
Wherein the image processing program in the memory 130 when executed by the processor performs the steps of:
acquiring an intelligent driving auxiliary system signal; based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image; based on a monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image; and comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing component to obtain a comparison result.
Further, the image processing program in the memory 130 when executed by the processor also realizes the following steps:
according to a preset time period and a signal identity number rule, grouping and aggregating the acquired intelligent driving assistance system signals to acquire grouped and aggregated intelligent driving assistance system signals; the step of performing image rendering on the intelligent driving assistance system signal based on the intelligent driving assistance system image processing component to obtain an intelligent driving assistance system image comprises the following steps: based on the intelligent driving assistance system image processing component, performing image rendering on the grouped and aggregated intelligent driving assistance system signals to obtain the intelligent driving assistance system image; the step of performing image rendering on the intelligent driving auxiliary system signal based on the monitoring image processing component to obtain a monitoring image comprises the following steps: and based on the monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signals after grouping and aggregation to obtain the monitoring image.
Further, the image processing program in the memory 130 when executed by the processor also realizes the following steps:
based on the monitoring image processing component, comparing the intelligent driving auxiliary system image with the monitoring image at a pixel level to obtain a picture difference value; and comparing the picture difference value with a preset difference threshold value to obtain the comparison result.
Further, the image processing program in the memory 130 when executed by the processor also realizes the following steps:
and if the comparison result is passed, performing cyclic redundancy check on the intelligent driving auxiliary system image and the monitoring image to obtain a check result.
Further, the image processing program in the memory 130 when executed by the processor also realizes the following steps:
and if the check result is passed, sending the intelligent driving assistance system image to a display screen component for display.
Further, the image processing program in the memory 130 when executed by the processor also realizes the following steps:
and if the comparison result is not passed, sending out signal fault information.
Further, the image processing program in the memory 130 when executed by the processor also realizes the following steps:
The method comprises the steps of obtaining signals through a camera and a radar, obtaining physical information and sending the physical information to an electronic control unit ECU; based on the ECU, converting the physical information into an intelligent driving auxiliary system signal and sending the intelligent driving auxiliary system signal to a Micro Controller Unit (MCU); and based on the MCU, carrying out signal function safety inspection on the intelligent driving assistance system signal, and sending the intelligent driving assistance system signal to a system-on-chip (SOC) when the intelligent driving assistance system signal passes the safety inspection, wherein the SOC comprises the intelligent driving assistance system image processing component and the monitoring image processing component.
According to the embodiment, through the scheme, the intelligent driving auxiliary system signal is acquired; based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image; based on a monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image; and comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing component to obtain a comparison result. After the intelligent driving assistance system signal is obtained, the rendering processing mode of the ADAS signal designed by the original ADAS system is changed into the synchronous rendering processing mode of the intelligent driving assistance system signal through the intelligent driving assistance system image processing component and the monitoring image processing component, the intelligent driving assistance system image and the monitoring image are obtained, and the comparison result is obtained by comparing the intelligent driving assistance system image and the monitoring image. It can be understood that after the same image signal is rendered and output by different rendering modes, the original image (the image of the intelligent driving auxiliary system) can be monitored for failure by comparing the differences of the rendering and output of the two different modes, so that the design meeting the functional safety requirements is met, and the safety of ADAS display is improved.
Based on the above terminal device architecture, but not limited to the above architecture, the method embodiments of the present application are presented.
Referring to fig. 2, fig. 2 is a flowchart illustrating a first exemplary embodiment of an image processing method according to the present application.
An embodiment of the present invention provides an image processing method, including:
step S10, acquiring an intelligent driving auxiliary system signal;
an intelligent driving assistance system (Advanced Driving Assistance System, ADAS) is an automotive safety system employing advanced technology, aimed at providing driver assistance functionality and enhancing driving experience. The system senses the surrounding environment by using devices such as a sensor, a camera, a radar, a computer and the like, and provides warning, automatic control or assisting operation for a driver through data processing and algorithm analysis. For example, real-time warning and support of the driver for forward traffic conditions may be provided by active braking, adaptive cruise control, lane keeping assistance, and the like.
The instrument is displayed on the ADAS and used for providing information on the state of the vehicle, the driving environment and the running condition of the system for the driver, so that the driver is helped to better understand and control the whole driving process, and the instrument plays a vital role. However, no safety design is currently made on the display of the ADAS on the meter, so that potential safety hazards exist, and the ADAS cannot meet the functional safety requirements, and the life safety of drivers and passengers is endangered.
Therefore, after the intelligent driving assistance system signal is obtained, the method for rendering the ADAS signal designed by the original ADAS system by the intelligent driving assistance system image processing component is changed into the method for synchronously rendering the intelligent driving assistance system signal by the intelligent driving assistance system image processing component and the monitoring image processing component, so that the intelligent driving assistance system image and the monitoring image are obtained, and a comparison result is obtained by comparing the intelligent driving assistance system image and the monitoring image. It can be understood that after the same image signal is rendered and output by different rendering modes, the original image (the image of the intelligent driving auxiliary system) can be monitored for failure by comparing the differences of the rendering and output of the two different modes, so that the design meeting the functional safety requirements is met, and the safety of ADAS display is improved.
Specifically, in the prior art, an intelligent driving assistance system image is obtained based on individual image rendering of an intelligent driving assistance system image processing component. However, the independent image rendering cannot ensure that information is always accurately displayed on the instrument, and if the ADAS or the intelligent driving assistance system image processing component fails, the intelligent driving assistance system image is also displayed on the instrument panel, so that the independent image rendering in the prior art cannot meet the requirement of functional safety implementation.
More specifically, in intelligent driving assistance systems, there are typically a number of sensors and algorithms for acquiring and processing information of the surrounding environment of the vehicle. For example, sensors such as cameras, radars, lidars, etc. are used to sense the condition of objects and roads around the vehicle, and then these information are analyzed and understood through algorithms such as image processing, target detection, and tracking, etc., thereby implementing an automatic driving assistance function. If only a single rendering mode is relied on to display the information, when a problem or a fault occurs in the rendering mode, the related information cannot be accurately displayed, and the driver may be caused to judge the surrounding situation of the vehicle. To avoid this, two or more different rendering modes may be used, such as displaying numbers and graphics on the dashboard at the same time, or displaying information on the HUD (heads up display) and on-board display at the same time.
Compared with the prior art, the method and the device realize the safe redundancy design of the rendering part by decomposing the safety requirement of the original ASIL A into ASIL A (A) +QM (A) through the safety decomposition of the display safety path, judge and compare pixel levels through the two-way rendering image output (output of ASIL A (A) +QM (A)), and prove that equipment fails if the difference of the comparison results of the rendering output in two different modes is too large, so that the display design meeting the functional safety requirement is realized and met.
In this embodiment, ASIL a (a) corresponds to an intelligent driving assistance system image processing component, and QM (a) corresponds to a monitoring image processing component.
Specifically, ASIL a (a) and QM (a) are one way of resolving functional security requirements defined in the ISO 26262 standard. ASIL a (a) represents a breakdown of the safety requirements of a particular function. In the ISO 26262 standard, ASIL a level is the lowest level of security integrity, which is relatively less stringent to security requirements. ASIL a (a) is a further refinement and splitting of the security requirements of the ASIL a level to meet more specific functional security requirements.
QM (a) represents a quality management (Quality Management) requirement. In functional security design, quality management is an important link in ensuring that the system meets security requirements. QM (a) describes the quality management measures that need to be taken in achieving the security requirements at the ASIL a (a) level, including requirements in terms of process specifications, flow control, document management, risk assessment, etc.
By breaking down the ASIL a level security requirements into ASIL a (a) and QM (a), the specific requirements required for functional security design can be defined in more detail and the quality management measures can be ensured to be effectively implemented. The decomposition mode can improve the control and the guarantee of the functional safety, thereby meeting the requirements of an automobile electronic system in the aspect of safety.
Specifically, as shown in fig. 3, the high-pass domain master can receive an intelligent driving assistance system signal from the ADAS, where the intelligent driving assistance system signal includes information such as a target vehicle state, a target vehicle position, and a curvature state of a lane line.
Step S20, based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image;
step S30, performing image rendering on the intelligent driving auxiliary system signal based on a monitoring image processing component to obtain a monitoring image;
in particular, the intelligent driving assistance system image processing component may be a KANZI module, wherein KANZI is used to create various graphical user interfaces on the vehicle interior display screen, including dashboards, center control screens, entertainment systems, navigation interfaces, and the like.
In particular, the monitoring image processing component may be an OPENGL module, where OPENGL is a cross-platform graphics library for writing 2D and 3D graphics applications that provides a series of functions for handling operations in graphics rendering, graphics acceleration, and graphics effects. OpenGL is widely used in various fields including computer game development, virtual reality, scientific visualization, engineering design, medical image processing, and the like.
In addition, besides OpenGL and KANZI, modules in the set of Vulkan, CUDA and DirectX algorithms may be used to make an intelligent driving assistance system image processing component or a monitoring image processing component. Wherein, vulkan is another cross-platform graphics API, similar to OpenGL, but more bottom-layer and efficient, especially suitable for applications requiring high-performance graphics processing; CUDA is a parallel computing platform and programming model derived by NVIDIA for general purpose parallel computing with GPU, which can be used to accelerate image processing and rendering, and is very efficient for image processing tasks requiring massive parallel processing.
Specifically, the KANZI module (intelligent driving assistance system image processing component) performs image rendering of the ADAS dynamic display area according to the received intelligent driving assistance system signal, obtains an intelligent driving assistance system image, and caches the intelligent driving assistance system image.
Meanwhile, the OPENGL module (monitoring image processing component) receives intelligent driving auxiliary system signals sent from different data channels to conduct image rendering of the monitoring part ADAS dynamic display area, and a monitoring image is obtained.
And step S40, comparing the intelligent driving assistance system image with the monitoring image based on the monitoring image processing component to obtain a comparison result.
It can be appreciated that by comparing the differences between the two rendering modes, a fault or abnormal condition of one mode can be found in time. If the information presented by the two rendering modes is inconsistent, this may mean that one of the modes is problematic. The design can help a driver to discover system faults early and take corresponding measures to ensure driving safety.
The purpose of rendering the intelligent driving assistance system signal in two ways is to detect potential faults through differences, and the embodiment is based on a monitoring image processing component, and the intelligent driving assistance system image and the monitoring image are compared to obtain a comparison result. The comparison result reflects the difference between the two images, if the difference is too large, the device is indicated to be faulty, and if the difference is within a preset range, the device is indicated to be normal.
In general, images are rendered and output in different rendering modes, and then failure monitoring is performed on the original images by comparing the differences of the rendering and output in two different modes. Therefore, the design meeting the functional safety requirements is met, and the safety of ADAS display is improved.
Further, in step S50, if the comparison result is not passed, a signal failure message is sent.
And when the comparison result is that the signal fails, the monitoring image processing component sends out signal failure information. When the MCU receives the signal fault information, the affected functions can be selectively turned off or weakened to prevent fault diffusion and continue to provide basic safety functions. For example, if a sensor of an ADAS system fails, the system may perform degradation processing based on data from other sensors to ensure that basic safe driving functions remain available.
In some cases, the image processing system may take over the affected functions by the standby system or standby components to ensure continuity and stability of the system. For example, if a certain control unit of the ADAS system fails, the image processing system may switch to a standby control unit to continue to provide the necessary security functions.
The image processing system may send an alert or notification to the driver informing him that a fault or abnormal situation has occurred in the system and providing a corresponding advice or indication. Such alerts and notifications may assist the driver in taking appropriate actions to reduce potential safety risks.
According to the image processing method, the intelligent driving auxiliary system signal is obtained; based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image; based on a monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image; and comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing component to obtain a comparison result. After the intelligent driving assistance system signal is obtained, the rendering processing mode of the ADAS signal designed by the original ADAS system is changed into the synchronous rendering processing mode of the intelligent driving assistance system signal through the intelligent driving assistance system image processing component and the monitoring image processing component, the intelligent driving assistance system image and the monitoring image are obtained, and the comparison result is obtained by comparing the intelligent driving assistance system image and the monitoring image. It can be understood that after the same image signal is rendered and output by different rendering modes, the original image (the image of the intelligent driving auxiliary system) can be monitored for failure by comparing the differences of the rendering and output of the two different modes, so that the design meeting the functional safety requirements is met, and the safety of ADAS display is improved.
Based on the first embodiment, a second embodiment of the present application is presented, which differs from the first embodiment in that:
the step of obtaining the intelligent driving assistance system signal is supplemented after the step S10, wherein the step of supplementing may include:
and S11, grouping and aggregating the acquired intelligent driving assistance system signals according to a preset time period and a signal identity number rule, and acquiring the grouped and aggregated intelligent driving assistance system signals.
In order to realize synchronous rendering of the image processing component and the monitoring image processing component of the intelligent driving assistance system, the signals of the intelligent driving assistance system can be subjected to grouping fusion according to a preset time period and a signal identity number rule. Specifically, as shown in fig. 4, the preset time period and the signal identity number rule may be that the set timing is 2 seconds and the signal ID of the intelligent driving assistance system is greater than 5, that is, 5 intelligent driving assistance system signals are acquired every 2 seconds, and the intelligent driving assistance system signals after grouping and aggregation are obtained by aggregating every 5 intelligent driving assistance system signals.
Step S21, based on the intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signals subjected to grouping aggregation to obtain the intelligent driving assistance system image;
Step S31, performing image rendering on the intelligent driving auxiliary system signal based on a monitoring image processing component to obtain a monitoring image;
and simultaneously sending the intelligent driving assistance system signals aggregated by each group to KANZI and OpenGL for rendering. KANZI can complete rendering faster than OpenGL, obtain intelligent driving assistance system images and monitoring images, and cache the rendered images.
And based on the monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signals after grouping and aggregation to obtain the monitoring image.
And when the KANZI and the OpenGL are rendered, sending the image of the intelligent driving assistance system cached by the KANZI to the OpenGL, and then comparing the images. By comparing the images rendered by KANZI and OpenGL, it is possible to detect whether there is an inconsistency, thereby performing fault detection or verifying consistency of rendering results.
By synchronizing the rendering, it can be ensured that the image content presented by KANZI and OpenGL is consistent. So that the rendering difference between KANZI and OpenGL can be more easily detected. If the two rendering results are not consistent, this may mean that one of the systems has failed or is abnormal, which may help to find and remove problems early.
Meanwhile, the synchronous rendering can rapidly complete differential comparison, a comparison result is rapidly obtained, and the safety of ADAS can be guaranteed in real time.
According to the image processing method, the acquired intelligent driving assistance system signals are grouped and aggregated according to the preset time period and the signal identity number rule, so that the grouped and aggregated intelligent driving assistance system signals are acquired; the step of performing image rendering on the intelligent driving assistance system signal based on the intelligent driving assistance system image processing component to obtain an intelligent driving assistance system image comprises the following steps: based on the intelligent driving assistance system image processing component, performing image rendering on the grouped and aggregated intelligent driving assistance system signals to obtain the intelligent driving assistance system image; the step of performing image rendering on the intelligent driving auxiliary system signal based on the monitoring image processing component to obtain a monitoring image comprises the following steps: based on the monitoring image processing component, image rendering is carried out on the intelligent driving auxiliary system signals after grouping and aggregation to obtain the monitoring image, differential comparison can be rapidly completed through synchronous rendering, a comparison result can be rapidly obtained, and the safety of ADAS can be guaranteed in real time.
Based on the first embodiment, a third embodiment of the present application is presented, which differs from the first embodiment in that:
comparing the intelligent driving assistance system image with the monitoring image based on the monitoring image processing component in step S40 to refine the step of obtaining the comparison result, wherein the step of refining may include:
step S41, based on the monitoring image processing component, comparing the intelligent driving auxiliary system image with the monitoring image at a pixel level to obtain a picture difference value;
step S42, comparing the picture difference value with a preset difference threshold value to obtain the comparison result.
In order to accurately compare the difference between the intelligent driving assistance system image and the monitoring image, a pixel level comparison algorithm is used for comparing to obtain a picture difference value.
Specifically, the formula of the pixel level contrast algorithm is as follows:
c＝0，1，2，…，C-1.
x＝0，1，2，…，W-1.
y＝0，1，2，…，H-1.
wherein W is the width of the image, H is the height of the image, C is the channel of the image, I 1 (x, y, c) is image I 1 A channel c component of the pixel value of the (x, y) coordinate of (x, y); i 2 (x, y, c) is image I 2 Channel c component of pixel values of (x, y) coordinates of (x, y), wherein image I 1 And I 2 The image is an intelligent driving assistance system image and a monitoring image, and MAD is a picture difference value.
It will be appreciated that the above formula represents that the difference value of the pictures is obtained by accumulating the difference values of each pixel of the two pictures in each channel.
And finally comparing the picture difference value with a preset difference threshold value to obtain the comparison result. If the picture difference value is larger than the difference threshold value, the comparison result is that the picture does not pass, the monitoring image processing component sends out a fault signal, and the system adopts corresponding operation; if the picture difference value is smaller than the difference threshold value, the comparison result is that the picture passes, and the system operates normally.
According to the image processing method, the image of the intelligent driving assistance system and the image of the monitoring image are subjected to pixel level comparison based on the monitoring image processing component, so that a picture difference value is obtained; and comparing the picture difference value with a preset difference threshold value to obtain the comparison result, and accurately comparing the difference between the intelligent driving auxiliary system image and the monitoring image.
Based on the first embodiment, a fourth embodiment of the present application is presented, which differs from the first embodiment in that:
and step S40, comparing the intelligent driving assistance system image with the monitoring image based on the monitoring image processing component, and supplementing after the step of obtaining a comparison result, wherein the step of supplementing comprises the following steps:
And S50, if the comparison result is passed, performing cyclic redundancy check on the intelligent driving assistance system image and the monitoring image to obtain a check result.
In order to further improve the security of ADAS display, an auxiliary hard check mode may be added, and in this embodiment, cyclic redundancy check is added to obtain a check result.
If the rendering comparison result of KANZI and OpenGL passes, cyclic redundancy check (Cyclic Redundancy Check, CRC) can be continuously carried out on the intelligent driving assistance system image and the monitoring image to further verify the integrity of the data. CRC is a check algorithm that detects whether an error has occurred in data transmission or storage by calculating a check value of the data.
Specifically, CRC calculation is performed on the intelligent driving assistance system image and the monitoring image, respectively, to generate corresponding check values. Then, the intelligent driving assistance system image check value is compared with the monitoring image check value. If the two check values are identical, it is indicated that no error has occurred in the data during transmission or storage.
And obtaining a checking result according to the comparison result. If the check values are consistent, the data integrity is good, and the check result is passed. If the check values are not consistent, it is indicated that the data may have errors and require further processing or correction.
The CRC check method may help to detect the integrity of data, but is not capable of repairing or correcting data errors. If the verification result fails, the correct data may need to be retrieved or restored to ensure that the system is functioning properly.
It can be appreciated that the present embodiment double-ensures the security of ADAS display by image contrast and CRC check.
Further, in step S60, if the check result is passed, the image of the intelligent driving assistance system is sent to a display screen assembly for display.
And sending the intelligent driving assistance system image data passing through the image comparison and CRC verification to a display screen assembly. After the display screen component receives the image data of the intelligent driving auxiliary system, the image is displayed according to the set parameters and rules, and the quality and stability of the image in the display process are ensured.
According to the image processing method, if the comparison result is passing, cyclic redundancy check is conducted on the intelligent driving assistance system image and the monitoring image to obtain a check result, if the check result is passing, the intelligent driving assistance system image is sent to the display screen assembly to be displayed, if the comparison result is not passing, signal fault information is sent, and safety of ADAS display is guaranteed through image comparison and CRC check.
Based on the first embodiment, a fifth embodiment of the present application is presented, which differs from the first embodiment in that:
the step of acquiring the intelligent driving assistance system signal is refined in step S10, wherein the step of refining may include:
step S101, signal acquisition is carried out through a camera and a radar, physical information is acquired and sent to an electronic control unit ECU;
step S102, converting the physical information into an intelligent driving auxiliary system signal based on the ECU and sending the intelligent driving auxiliary system signal to a micro controller unit MCU;
step S103, based on the MCU, carrying out signal function safety inspection on the intelligent driving assistance system signal, and when the intelligent driving assistance system signal passes the safety inspection, sending the intelligent driving assistance system signal to a system-on-chip (SOC), wherein the SOC comprises the intelligent driving assistance system image processing component and the monitoring image processing component.
Specifically, as shown in fig. 5 and 3, the ECU of the ADAS converts physical information detected by the camera and the radar, including the target state, the position, and the lane curvature state, and then transmits a CAN signal (intelligent driving assistance system signal).
The MCU receives and verifies the correctness of the intelligent driving assistance system signal and then forwards the intelligent driving assistance system signal to the SOC.
The SOC receives and transmits the intelligent driving assistance system signal to the image rendering module and the image monitoring module of the KANZI.
And the KANZI module performs intelligent driving assistance system image rendering of the ADAS dynamic display area according to the intelligent driving assistance system signal and stores the intelligent driving assistance system image rendering in the data memory, and the safety monitoring module receives the intelligent driving assistance system signal to perform picture rendering of the monitoring part of the ADAS dynamic display area to obtain a monitoring image.
And then the cached intelligent driving assistance system image is transmitted to a monitoring image processing component for comparison.
And the monitoring image processing component outputs a comparison result, if the comparison is correct, the rendered dynamic ADAS picture is displayed, if the comparison is failed, the SOC informs the MCU module of a fault state, and the MCU converts the signal into a CAN signal and sends the CAN signal to the ADAS ECU module.
On the other hand, the intelligent driving auxiliary system image and the monitoring image are input into a multi-input signature register to carry out CRC verification, and if the verification is successful, the images are sent to a display to be displayed.
The steps relate to the steps of information acquisition, transmission, verification, processing, display and the like, so that the normal operation and the safety of the ADAS system are ensured.
According to the image processing method, signals are acquired through the camera and the radar, physical information is acquired, and the physical information is sent to the electronic control unit ECU; based on the ECU, converting the physical information into an intelligent driving auxiliary system signal and sending the intelligent driving auxiliary system signal to a Micro Controller Unit (MCU); based on the MCU, carrying out signal function safety inspection on the intelligent driving auxiliary system signal, and when the intelligent driving auxiliary system signal passes through the safety inspection, sending the intelligent driving auxiliary system signal to a system-on-chip (SOC), wherein the SOC comprises an intelligent driving auxiliary system image processing component and a monitoring image processing component, and the steps relate to multiple steps of information acquisition, transmission, verification, processing, display and the like so as to ensure the normal operation and safety of an ADAS system.
In addition, an embodiment of the present application further proposes an image processing apparatus, including:
the information acquisition module is used for acquiring signals of the intelligent driving auxiliary system;
the intelligent driving assistance system image processing module is used for performing image rendering on the intelligent driving assistance system signal based on the intelligent driving assistance system image processing component to obtain an intelligent driving assistance system image;
The monitoring image processing module is used for carrying out image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image;
and the monitoring image processing module is also used for comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing assembly to obtain a comparison result.
The principle and implementation process of image processing are implemented in this embodiment, please refer to the above embodiments, and are not repeated here.
In addition, the embodiment of the application also provides a terminal device, which comprises a memory, a processor and an image processing program stored on the memory and capable of running on the processor, wherein the image processing program realizes the steps of the image processing method when being executed by the processor.
Because the image processing program is executed by the processor and adopts all the technical schemes of all the embodiments, the image processing program at least has all the beneficial effects brought by all the technical schemes of all the embodiments and is not described in detail herein.
Furthermore, the embodiments of the present application also propose a computer-readable storage medium on which an image processing program is stored, which when executed by a processor implements the steps of the image processing method as described above.
Because the image processing program is executed by the processor and adopts all the technical schemes of all the embodiments, the image processing program at least has all the beneficial effects brought by all the technical schemes of all the embodiments and is not described in detail herein.
Compared with the prior art, the image processing method, the device, the terminal equipment and the storage medium provided by the embodiment of the application are used for acquiring the intelligent driving auxiliary system signal; based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image; based on a monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image; and comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing component to obtain a comparison result. After the intelligent driving assistance system signal is obtained, the rendering processing mode of the ADAS signal designed by the original ADAS system is changed into the synchronous rendering processing mode of the intelligent driving assistance system signal through the intelligent driving assistance system image processing component and the monitoring image processing component, the intelligent driving assistance system image and the monitoring image are obtained, and the comparison result is obtained by comparing the intelligent driving assistance system image and the monitoring image. It can be understood that after the same image signal is rendered and output by different rendering modes, the original image (the image of the intelligent driving auxiliary system) can be monitored for failure by comparing the differences of the rendering and output of the two different modes, so that the design meeting the functional safety requirements is met, and the safety of ADAS display is improved.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present application are merely for describing, and do not represent advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as above, including several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, a controlled terminal, or a network device, etc.) to perform the method of each embodiment of the present application.
The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the claims, and all equivalent structures or equivalent processes using the descriptions and drawings of the present application, or direct or indirect application in other related technical fields are included in the scope of the claims of the present application.
Claims (10)
1. An image processing method, characterized in that the image processing method comprises:
acquiring an intelligent driving auxiliary system signal;
based on an intelligent driving assistance system image processing component, performing image rendering on the intelligent driving assistance system signal to obtain an intelligent driving assistance system image;
based on a monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image;
and comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing component to obtain a comparison result.
2. The image processing method according to claim 1, characterized in that the step of acquiring the intelligent driving assistance system signal further comprises, after:
according to a preset time period and a signal identity number rule, grouping and aggregating the acquired intelligent driving assistance system signals to acquire grouped and aggregated intelligent driving assistance system signals;
The step of performing image rendering on the intelligent driving assistance system signal based on the intelligent driving assistance system image processing component to obtain an intelligent driving assistance system image comprises the following steps:
based on the intelligent driving assistance system image processing component, performing image rendering on the grouped and aggregated intelligent driving assistance system signals to obtain the intelligent driving assistance system image;
the step of performing image rendering on the intelligent driving auxiliary system signal based on the monitoring image processing component to obtain a monitoring image comprises the following steps:
and based on the monitoring image processing component, performing image rendering on the intelligent driving auxiliary system signals after grouping and aggregation to obtain the monitoring image.
3. The image processing method according to claim 1, wherein the step of comparing the intelligent driving assistance system image with the monitoring image based on the monitoring image processing component, and obtaining a comparison result includes:
based on the monitoring image processing component, comparing the intelligent driving auxiliary system image with the monitoring image at a pixel level to obtain a picture difference value;
and comparing the picture difference value with a preset difference threshold value to obtain the comparison result.
4. The image processing method according to claim 1, wherein the step of comparing the intelligent driving assistance system image with the monitoring image based on the monitoring image processing component, and obtaining a comparison result further comprises:
and if the comparison result is passed, performing cyclic redundancy check on the intelligent driving auxiliary system image and the monitoring image to obtain a check result.
5. The image processing method according to claim 4, wherein if the comparison result is a pass, performing cyclic redundancy check on the intelligent driving assistance system image and the monitoring image, and further comprising, after the step of obtaining the check result:
and if the check result is passed, sending the intelligent driving assistance system image to a display screen component for display.
6. The image processing method according to claim 1, wherein the step of comparing the intelligent driving assistance system image with the monitoring image based on the monitoring image processing component, and obtaining a comparison result includes:
and if the comparison result is not passed, sending out signal fault information.
7. The image processing method according to claim 1, wherein the acquiring the intelligent driving assistance system signal includes:
the method comprises the steps of obtaining signals through a camera and a radar, obtaining physical information and sending the physical information to an electronic control unit ECU;
based on the ECU, converting the physical information into an intelligent driving auxiliary system signal and sending the intelligent driving auxiliary system signal to a Micro Controller Unit (MCU);
and based on the MCU, carrying out signal function safety inspection on the intelligent driving assistance system signal, and sending the intelligent driving assistance system signal to a system-on-chip (SOC) when the intelligent driving assistance system signal passes the safety inspection, wherein the SOC comprises the intelligent driving assistance system image processing component and the monitoring image processing component.
8. An image processing apparatus, characterized in that the image processing apparatus comprises:
the information acquisition module is used for acquiring signals of the intelligent driving auxiliary system;
the intelligent driving assistance system image processing module is used for performing image rendering on the intelligent driving assistance system signal based on the intelligent driving assistance system image processing component to obtain an intelligent driving assistance system image;
the monitoring image processing module is used for carrying out image rendering on the intelligent driving auxiliary system signal to obtain a monitoring image;
And the monitoring image processing module is also used for comparing the intelligent driving auxiliary system image with the monitoring image based on the monitoring image processing assembly to obtain a comparison result.
9. A terminal device, characterized in that it comprises a memory, a processor and an image processing program stored on the memory and executable on the processor, which image processing program, when executed by the processor, realizes the steps of the image processing method according to any of claims 1-7.
10. A computer-readable storage medium, on which an image processing program is stored, which when executed by a processor implements the steps of the image processing method according to any one of claims 1 to 7.
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