Traffic road environment data processing and transmitting system

Abstract

The invention relates to a traffic road environment data processing and transmitting system, and the system comprises a directional monitoring mechanism which is disposed right above a no-parking area corresponding to a set vehicle type, and is used for carrying out the visual monitoring operation of the no-parking area; and the wireless uploading equipment is used for packaging the area number corresponding to the no-parking area corresponding to the set vehicle type and then wirelessly uploading the packaged area number to a far-end big data server when receiving the object identification instruction. The traffic pavement environment data processing and transmitting system is simple and convenient to operate and wide in application. According to the invention, each edge pixel point in the optimized picture of the traffic road surface imaging image can be determined by adopting a targeted analysis mechanism, and a plurality of image blocks divided from each edge pixel point in the optimized picture are subjected to matching processing based on the reference contour of the set vehicle type; therefore, whether the set vehicle type exists in the no-parking area corresponding to the set vehicle type of the traffic road environment is determined in a targeted manner.

Description

Technical Field

[0001] This invention relates to the field of traffic monitoring, and more particularly to a traffic road surface environmental data processing and transmission system. Background Technology

[0002] To improve traffic efficiency, maintain order, and facilitate the management of various vehicle types, traffic management operators have designated different stopping areas for different vehicle types. These areas are considered no-parking zones compared to other vehicle types. For example, yellow grid lines indicate no-parking zones, and these lines are often found in front of buildings or at intersections. When queuing at an intersection, if there is insufficient space ahead, vehicles should wait outside the grid lines; parking along the grid lines is prohibited. Yellow dashed lines on the curb indicate temporary parking is permitted. Long-term parking may result in being asked to move, and this is often accompanied by signs prohibiting prolonged parking.

[0003] In traffic environments, it is common to designate no-parking zones corresponding to different vehicle types, such as buses or taxis. However, existing technologies lack specific detection mechanisms for buses or taxis appearing in these no-parking zones, making it difficult to maintain traffic environments and regulate traffic order.

[0004] Among the publicly available vehicle type recognition technologies, for example, Southeast University proposed "A Vehicle Type Recognition Method Based on a Deep Learning Fusion Model" (application publication number CN116863412A). This method involves constructing a dataset of top-view images of vehicles in highway scenes; building a deep learning-based vehicle type detection and recognition method, CenterNet, for highway scenes, and using the crop function to crop the vehicle target region; constructing a deep learning-based vehicle type recognition model, VTR-NASNetLarge, to obtain a one-dimensional feature vector FN; constructing a deep learning-based vehicle type recognition model, VTR-VGG16, to obtain a one-dimensional feature vector FV; constructing a deep learning-based vehicle type recognition model, VTR-MobileNetV2, to obtain a one-dimensional feature vector FM; and then fusing the feature vectors FN, FV, and FM in parallel to construct a deep learning-based vehicle type recognition fusion model, DFN-VTR, for vehicle type recognition in highway scenes at toll booths. This invention proposes obtaining the vehicle target region from the top-view image and constructing a deep learning fusion model, which can more accurately identify vehicle types and provide technical support for vehicle information perception. Summary of the Invention

[0005] To address technical issues in related fields, this invention provides a traffic road surface environment data processing and transmission system. This system employs a targeted analytical mechanism to determine each edge pixel in an optimized image of the traffic road surface. It then performs matching processing on multiple image blocks defined by each edge pixel in the optimized image, based on a baseline contour of a specified vehicle type. This determines whether a specific vehicle type exists within a no-stopping zone corresponding to that vehicle type in the traffic road surface environment. Finally, it packages the area number corresponding to the no-stopping zone of the specified vehicle type and wirelessly uploads it to a remote big data server, thereby achieving synchronous management of multiple no-stopping zones.

[0006] The present invention provides a traffic road surface environment data processing and transmission system comprising:

[0007] A directional monitoring device is set directly above the no-parking zone corresponding to a set vehicle type. It is used to perform visual monitoring operations on the no-parking zone to obtain and output the corresponding area monitoring image. The no-parking zone corresponding to the set vehicle type is located in the traffic road environment.

[0008] A band-stop filter device, connected to the directional monitoring mechanism, is used to perform band-stop filtering on the received area monitoring image to obtain and output the corresponding band-stop filtered image.

[0009] A contrast enhancement device, connected to the band-stop filter device, is used to perform contrast enhancement processing on the received band-stop filtered image to obtain and output a corresponding clear image.

[0010] A cubic interpolation device, connected to the contrast enhancement device, is used to perform cubic polynomial interpolation on the received sharpened image to obtain and output the corresponding cubic interpolated image.

[0011] The first analysis device is connected to the cubic interpolation device and is used to obtain the brightness values ​​corresponding to each pixel in the received cubic interpolation image. Taking each pixel in the cubic interpolation image as the center pixel, the brightness value gradient of the center pixel is determined based on the brightness values ​​of the center pixel and the surrounding pixels.

[0012] The second analysis device, connected to the first analysis device, is used to determine that the center pixel is an edge pixel when the brightness value gradient of the center pixel exceeds the limit, so as to obtain each edge pixel in the cubic interpolation image.

[0013] The third analysis device, connected to the second analysis device, is used to take the image blocks enclosed by the edge pixels in the cubic interpolation image as reference image blocks. When the outline of a certain reference image block in the cubic interpolation image matches the baseline outline of the standard vehicle body corresponding to the set vehicle type, an object recognition command is issued; otherwise, an object unrecognized command is issued.

[0014] For example, different types of SOC devices can be used to implement the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device respectively;

[0015] The wireless upload device is connected to the third analysis device and a remote big data server. When the object identification instruction is received, it packages the area number corresponding to the no-parking area for the set vehicle type and wirelessly uploads it to the remote big data server.

[0016] Specifically, upon receiving the object identification instruction, packaging the area number corresponding to the no-parking zone for the specified vehicle type into a data packet and wirelessly uploading it to a remote big data server includes: upon receiving the object identification instruction, packaging the area number corresponding to the no-parking zone for the specified vehicle type into an IP data packet and wirelessly uploading the IP data packet to a remote big data server.

[0017] The traffic road surface environment data processing and transmission system of the present invention is easy to operate and widely applicable. Because it can use a targeted analysis mechanism to determine each edge pixel in the optimized image of the traffic road surface, and perform matching processing on multiple image blocks divided from each edge pixel in the optimized image based on a reference contour of a set vehicle type, it can thus complete a targeted determination of whether a set vehicle type exists within a no-stopping zone corresponding to that vehicle type in the traffic road surface environment. Attached Figure Description

[0018] The embodiments of the present invention will now be described with reference to the accompanying drawings.

[0019] Figure 1 This is a schematic diagram of the internal structure of a traffic surface environment data processing and transmission system according to an embodiment A of the present invention.

[0020] Figure 2 This is a schematic diagram of the internal structure of a traffic surface environment data processing and transmission system according to embodiment B of the present invention.

[0021] Figure 3 This is a schematic diagram of the internal structure of a traffic surface environment data processing and transmission system according to embodiment C of the present invention. Detailed Implementation

[0022] The embodiments of the traffic road surface environment data processing and transmission system of the present invention will now be described in detail with reference to the accompanying drawings.

[0023] Example A

[0024] Figure 1 The diagram illustrates the internal structure of a traffic surface environment data processing and transmission system according to an embodiment A of the present invention. The system includes:

[0025] A directional monitoring device is set directly above the no-parking zone corresponding to a set vehicle type. It is used to perform visual monitoring operations on the no-parking zone to obtain and output the corresponding area monitoring image. The no-parking zone corresponding to the set vehicle type is located in the traffic road environment.

[0026] A band-stop filter device, connected to the directional monitoring mechanism, is used to perform band-stop filtering on the received area monitoring image to obtain and output the corresponding band-stop filtered image.

[0027] A contrast enhancement device, connected to the band-stop filter device, is used to perform contrast enhancement processing on the received band-stop filtered image to obtain and output a corresponding clear image.

[0028] A cubic interpolation device, connected to the contrast enhancement device, is used to perform cubic polynomial interpolation on the received sharpened image to obtain and output the corresponding cubic interpolated image.

[0029] The first analysis device is connected to the cubic interpolation device and is used to obtain the brightness values ​​corresponding to each pixel in the received cubic interpolation image. Taking each pixel in the cubic interpolation image as the center pixel, the brightness value gradient of the center pixel is determined based on the brightness values ​​of the center pixel and the surrounding pixels.

[0030] The second analysis device, connected to the first analysis device, is used to determine that the center pixel is an edge pixel when the brightness value gradient of the center pixel exceeds the limit, so as to obtain each edge pixel in the cubic interpolation image.

[0031] The third analysis device, connected to the second analysis device, is used to take the image blocks enclosed by the edge pixels in the cubic interpolation image as reference image blocks. When the outline of a certain reference image block in the cubic interpolation image matches the baseline outline of the standard vehicle body corresponding to the set vehicle type, an object recognition command is issued; otherwise, an object unrecognized command is issued.

[0032] The wireless upload device is connected to the third analysis device and a remote big data server. When the object identification instruction is received, it packages the area number corresponding to the no-parking area for the set vehicle type and wirelessly uploads it to the remote big data server.

[0033] The step of wirelessly uploading the area number corresponding to the no-parking zone for the vehicle type to a remote big data server when the object identification instruction is received includes: packaging the area number corresponding to the no-parking zone for the vehicle type into an IP data packet and wirelessly uploading the IP data packet to a remote big data server when the object identification instruction is received.

[0034] The device is positioned directly above the no-parking zone corresponding to a specific vehicle type, and is used to perform visual monitoring of the no-parking zone to obtain and output the corresponding area monitoring image. The no-parking zone corresponding to the specific vehicle type is located within the traffic road environment, including cases where there are two or more specific vehicle types.

[0035] Example B

[0036] Figure 2 This is a schematic diagram of the internal structure of a traffic surface environment data processing and transmission system according to embodiment B of the present invention.

[0037] Figure 2 The traffic surface environment data processing and transmission system includes the following components:

[0038] A directional monitoring device is set directly above the no-parking zone corresponding to a set vehicle type. It is used to perform visual monitoring operations on the no-parking zone to obtain and output the corresponding area monitoring image. The no-parking zone corresponding to the set vehicle type is located in the traffic road environment.

[0039] A band-stop filter device, connected to the directional monitoring mechanism, is used to perform band-stop filtering on the received area monitoring image to obtain and output the corresponding band-stop filtered image.

[0040] A contrast enhancement device, connected to the band-stop filter device, is used to perform contrast enhancement processing on the received band-stop filtered image to obtain and output a corresponding clear image.

[0041] A cubic interpolation device, connected to the contrast enhancement device, is used to perform cubic polynomial interpolation on the received sharpened image to obtain and output the corresponding cubic interpolated image.

[0042] The first analysis device is connected to the cubic interpolation device and is used to obtain the brightness values ​​corresponding to each pixel in the received cubic interpolation image. Taking each pixel in the cubic interpolation image as the center pixel, the brightness value gradient of the center pixel is determined based on the brightness values ​​of the center pixel and the surrounding pixels.

[0043] The second analysis device, connected to the first analysis device, is used to determine that the center pixel is an edge pixel when the brightness value gradient of the center pixel exceeds the limit, so as to obtain each edge pixel in the cubic interpolation image.

[0044] The third analysis device, connected to the second analysis device, is used to take the image blocks enclosed by the edge pixels in the cubic interpolation image as reference image blocks. When the outline of a certain reference image block in the cubic interpolation image matches the baseline outline of the standard vehicle body corresponding to the set vehicle type, an object recognition command is issued; otherwise, an object unrecognized command is issued.

[0045] The wireless upload device is connected to the third analysis device and a remote big data server. When the object identification instruction is received, it packages the area number corresponding to the no-parking area for the set vehicle type and wirelessly uploads it to the remote big data server.

[0046] A user input device is disposed near the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, and is connected to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, respectively.

[0047] The user input device, located near and connected to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, includes: the user input device being used to configure the working parameters of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device in real time based on user input.

[0048] Example C

[0049] Figure 3 This is a schematic diagram of the internal structure of a traffic surface environment data processing and transmission system according to embodiment C of the present invention.

[0050] Figure 3 The traffic surface environment data processing and transmission system includes the following components:

[0051] A directional monitoring device is set directly above the no-parking zone corresponding to a set vehicle type. It is used to perform visual monitoring operations on the no-parking zone to obtain and output the corresponding area monitoring image. The no-parking zone corresponding to the set vehicle type is located in the traffic road environment.

[0052] A band-stop filter device, connected to the directional monitoring mechanism, is used to perform band-stop filtering on the received area monitoring image to obtain and output the corresponding band-stop filtered image.

[0053] A contrast enhancement device, connected to the band-stop filter device, is used to perform contrast enhancement processing on the received band-stop filtered image to obtain and output a corresponding clear image.

[0054] A cubic interpolation device, connected to the contrast enhancement device, is used to perform cubic polynomial interpolation on the received sharpened image to obtain and output the corresponding cubic interpolated image.

[0055] The first analysis device is connected to the cubic interpolation device and is used to obtain the brightness values ​​corresponding to each pixel in the received cubic interpolation image. Taking each pixel in the cubic interpolation image as the center pixel, the brightness value gradient of the center pixel is determined based on the brightness values ​​of the center pixel and the surrounding pixels.

[0056] The second analysis device, connected to the first analysis device, is used to determine that the center pixel is an edge pixel when the brightness value gradient of the center pixel exceeds the limit, so as to obtain each edge pixel in the cubic interpolation image.

[0057] The third analysis device, connected to the second analysis device, is used to take the image blocks enclosed by the edge pixels in the cubic interpolation image as reference image blocks. When the outline of a certain reference image block in the cubic interpolation image matches the baseline outline of the standard vehicle body corresponding to the set vehicle type, an object recognition command is issued; otherwise, an object unrecognized command is issued.

[0058] The wireless upload device is connected to the third analysis device and a remote big data server. When the object identification instruction is received, it packages the area number corresponding to the no-parking area for the set vehicle type and wirelessly uploads it to the remote big data server.

[0059] A parallel data bus is located near the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, and is connected to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, respectively.

[0060] The parallel data bus, located near and connected to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, includes the following: the parallel data bus is used to establish parallel data communication links between each of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device.

[0061] Next, the specific structure of the traffic road surface environment data processing and transmission system of the present invention will be further described.

[0062] In the traffic surface environment data processing and transmission system according to various embodiments of the present invention:

[0063] A data augmentation mechanism is used to perform image data processing on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the corresponding output processed data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, respectively.

[0064] The method of using a data augmentation mechanism to perform image data processing on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the output processing data corresponding to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device respectively includes: performing Lanczos interpolation on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the output processing data corresponding to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device respectively;

[0065] The method of using a data augmentation mechanism to perform image data processing on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the output processing data corresponding to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device respectively includes: performing median blurring processing on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the output processing data corresponding to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device respectively;

[0066] The process of using a data augmentation mechanism to perform image data processing on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the corresponding output processing data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device includes: performing spatial domain differential sharpening on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the corresponding output processing data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device.

[0067] The method of using a data augmentation mechanism to perform image data processing on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the output processing data corresponding to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device respectively includes: performing logarithmic image augmentation on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the output processing data corresponding to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device respectively.

[0068] In addition, in the traffic road environment data processing and transmission system, a device is set directly above the no-parking zone corresponding to a set vehicle type to perform visual monitoring operations on the no-parking zone, so as to obtain and output the corresponding area monitoring image. The no-parking zone corresponding to the set vehicle type is located within the traffic road environment and also includes buses and taxis.

[0069] This invention has at least the following two beneficial technical effects:

[0070] First technical effect: A targeted analysis mechanism is used to obtain the brightness value gradient of each pixel. Based on the brightness value gradient of each pixel, multiple edge pixels are determined. The multiple edge pixels are divided into multiple image blocks in the cubic interpolation image and matched with the baseline contour based on the set vehicle type. This completes the targeted identification of whether the set vehicle exists in the cubic interpolation image at the pixel level with precision.

[0071] The second technical effect is that when a designated vehicle is present in the cubic interpolated image, it is determined that the designated vehicle type exists in the no-parking area corresponding to the designated vehicle type in the traffic road environment. The area number corresponding to the no-parking area of ​​the designated vehicle type is packaged and wirelessly uploaded to the remote big data server, thereby realizing the synchronous management of multiple no-parking areas.

[0072] The above specific embodiments can be implemented entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, they can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0073] It should be noted that, in this document, relational terms such as "first" and "second" are used only 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 one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0074] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A traffic road surface environment data processing and transmission system, characterized in that, The system includes: A directional monitoring device is set directly above the no-parking zone corresponding to a set vehicle type. It is used to perform visual monitoring operations on the no-parking zone to obtain and output the corresponding area monitoring image. The no-parking zone corresponding to the set vehicle type is located in the traffic road environment. A band-stop filter device, connected to the directional monitoring mechanism, is used to perform band-stop filtering on the received area monitoring image to obtain and output the corresponding band-stop filtered image. A contrast enhancement device, connected to the band-stop filter device, is used to perform contrast enhancement processing on the received band-stop filtered image to obtain and output a corresponding clear image. A cubic interpolation device, connected to the contrast enhancement device, is used to perform cubic polynomial interpolation on the received sharpened image to obtain and output the corresponding cubic interpolated image. The first analysis device is connected to the cubic interpolation device and is used to obtain the brightness values ​​corresponding to each pixel in the received cubic interpolation image. Taking each pixel in the cubic interpolation image as the center pixel, the brightness value gradient of the center pixel is determined based on the brightness values ​​of the center pixel and the surrounding pixels. The second analysis device, connected to the first analysis device, is used to determine that the center pixel is an edge pixel when the brightness value gradient of the center pixel exceeds the limit, so as to obtain each edge pixel in the cubic interpolation image. The third analysis device, connected to the second analysis device, is used to take the image blocks enclosed by the edge pixels in the cubic interpolation image as reference image blocks. When the outline of a certain reference image block in the cubic interpolation image matches the baseline outline of the standard vehicle body corresponding to the set vehicle type, an object recognition command is issued; otherwise, an object unrecognized command is issued. The wireless upload device is connected to the third analysis device and a remote big data server. When the object identification instruction is received, it packages the area number corresponding to the no-parking area for the set vehicle type and wirelessly uploads it to the remote big data server. Specifically, upon receiving the object identification instruction, packaging the area number corresponding to the no-parking zone for the specified vehicle type into a data packet and wirelessly uploading it to a remote big data server includes: upon receiving the object identification instruction, packaging the area number corresponding to the no-parking zone for the specified vehicle type into an IP data packet and wirelessly uploading the IP data packet to a remote big data server.

2. The traffic road surface environment data processing and transmission system as described in claim 1, characterized in that: It is positioned directly above the no-parking zone corresponding to a set vehicle type, and is used to perform visual monitoring operations on the no-parking zone to obtain and output the corresponding area monitoring image. The no-parking zone corresponding to the set vehicle type is located within the traffic road environment, including: the set vehicle type is two or more.

3. The traffic road surface environment data processing and transmission system as described in claim 2, characterized in that, The system also includes: A user input device is disposed near the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, and is connected to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, respectively. The user input device, located near and connected to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, includes: the user input device being used to configure the working parameters of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device in real time based on user input.

4. The traffic surface environment data processing and transmission system as described in claim 2, characterized in that, The system also includes: A parallel data bus is located near the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, and is connected to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, respectively. The parallel data bus, located near and connected to the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, includes the following: the parallel data bus is used to establish parallel data communication links between each of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device.

5. The traffic surface environment data processing and transmission system as described in any one of claims 2-4, characterized in that: A data augmentation mechanism is used to perform image data processing on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the corresponding output processed data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device, respectively.

6. The traffic surface environment data processing and transmission system as described in claim 5, characterized in that: The image data processing performed on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device using a data augmentation mechanism to obtain the corresponding output processing data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device includes: performing Lanczos interpolation on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the corresponding output processing data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device.

7. The traffic surface environment data processing and transmission system as described in claim 5, characterized in that: The image data processing performed on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device using a data augmentation mechanism to obtain the corresponding output processing data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device includes: performing median blurring processing on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the corresponding output processing data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device.

8. The traffic surface environment data processing and transmission system as described in claim 5, characterized in that: The image data processing performed on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device using a data augmentation mechanism to obtain the corresponding output processing data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device includes: performing spatial domain differential sharpening on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the corresponding output processing data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device.

9. The traffic surface environment data processing and transmission system as described in claim 5, characterized in that: The method of using a data augmentation mechanism to perform image data processing on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the corresponding output processing data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device includes: performing logarithmic image augmentation on the output data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device to obtain the corresponding output processing data of the cubic interpolation device, the first analysis device, the second analysis device, and the third analysis device.

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