Expressway patrol robot patrol method and system based on image processing

Abstract

The invention relates to the technical field of patrol image processing, and discloses an expressway patrol robot patrol method and system based on image processing, and the method comprises the steps: building a traffic sign image library, carrying out the image shooting of an indication board disposed on an expressway through a patrol robot during the patrol process of the expressway, comparing the shot image with a standard image in an image library to obtain the similarity of the mark image; and setting a clear similarity threshold. According to the invention, the patrol robot automatically executes the patrol task, the patrol robot can collect the traffic sign image on the road in real time, compares the collected image with the standard image in the image library for real-time analysis, quickly judges whether the sign is clear or not, and can find the problem in time and make a response.

Description

Technical Field

[0001] The present invention relates to the technical field of inspection image processing, and specifically provides a highway inspection robot inspection method and system based on image processing. Background Art

[0002] Highway inspection refers to the regular or irregular inspection and monitoring of highways and their related facilities through manual or automated equipment, real-time monitoring of traffic flow, detection of violations (such as speeding, illegal parking, etc.) to ensure road safety, smoothness, and intact facilities, and timely discovery and handling of various potential problems. Currently, highway inspection robots patrol along the fixed track of the highway steel guardrail, automatically move, and monitor traffic conditions and the inspection of related facilities according to the traveling route.

[0003] Many traffic signs and indicators are set on highways to improve traffic efficiency and standardize traffic order. However, due to long-term exposure to sunlight and rain, the traffic signs on the signs fade in color and the fonts become blurred, resulting in a decline in the readability of the signs. If the problem of unclear traffic signs cannot be discovered and handled in a timely manner, the unclear traffic signs may cause drivers to ignore traffic regulations and result in illegal acts such as speeding, illegal parking, and not driving in the correct lane.

[0004] Therefore, the present invention provides a highway inspection robot inspection method and system based on image processing. Summary of the Invention

[0005] Aiming at the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a highway inspection robot inspection method and system based on image processing, so that when the inspection robot inspects the highway, it can obtain the image information of the traffic signs on the signs through the camera and analyze whether there are unclear traffic signs, so as to timely discover the problem of blurred signs and make a response.

[0006] To achieve the above purpose, the present invention provides the following technical solution: A highway inspection robot inspection method based on image processing, the method includes the following steps:

[0007] Establish a traffic sign image library, use the inspection robot to take images of the signs set on the highway during the inspection of the highway, compare the taken images with the standard images in the image library, and obtain the sign image similarity;

[0008] Set a clear similarity threshold, compare the sign image similarity with the clear similarity threshold. When the sign image similarity is less than the clear similarity threshold, mark the traffic signs on the sign as suspected defective signs, and control the inspection robot to stop moving on the steel guardrail to continuously take pictures of the suspected defective signs and collect image information.

[0009] During continuous monitoring of suspected defect signs, obtain whether there is a change in the similarity after comparing it with the standard images in the image library. After the inspection robot stops on the steel guardrail for a time exceeding the preset stay and shooting time, if the similarity changes, the inspection robot will move in a cycle within a preset length range along the steel guardrail;

[0010] Obtain the maximum similarity after comparing the suspected defect signs collected when the inspection robot moves with the standard images in the image library. Compare the maximum similarity collected when the inspection robot moves with the clear similarity threshold, and make corresponding responses according to the comparison results.

[0011] In some embodiments, when the maximum similarity collected when the inspection robot moves is less than the clear similarity threshold, mark the sign with suspected defect signs as a faulty sign and notify the maintenance personnel to repair and replace the traffic sign. The inspection robot continues to move along the steel guardrail to perform the inspection task; when the maximum similarity collected when the inspection robot moves is greater than or equal to the clear similarity threshold, it is determined that the traffic sign on the sign is clear and no response is made. The inspection robot continues to move along the steel guardrail to perform the inspection task.

[0012] In some embodiments, set a minimum similarity threshold. When the maximum similarity collected when the inspection robot moves is less than the clear similarity threshold, compare the maximum similarity it collected with the minimum similarity threshold, and make corresponding responses according to the comparison results.

[0013] In some embodiments, if the maximum similarity collected when the inspection robot moves is less than the minimum similarity threshold, continue to perform the operation of notifying of a fault and make no additional response; if the maximum similarity collected when the inspection robot moves is greater than or equal to the minimum similarity threshold, then execute the similarity change analysis strategy.

[0014] In some embodiments, the similarity change analysis strategy includes setting a change amount threshold, obtaining the similarity change data of the suspected defect signs collected when the inspection robot moves in a cycle within a preset length range along the steel guardrail with the standard images, obtaining the difference between the maximum similarity and the minimum similarity collected to get the similarity change amount, and comparing the similarity change amount with the change amount threshold, and making corresponding responses according to the comparison results.

[0015] In some embodiments, if the similarity change amount is less than or equal to the change amount threshold, continue to perform the operation of notifying of a fault; if the similarity change amount is greater than the change amount threshold, it is determined that the traffic sign on the sign is clear, and the inspection robot continues to move along the steel guardrail to perform the inspection task.

[0016] In some embodiments, a monitoring time is set. When the detected change in similarity is greater than the change threshold, the inspection robot will move on the steel guardrail to the position where the maximum similarity between the suspected fault sign and the standard image is captured. When the robot remains stationary, continuous image information collection of the suspected fault sign will be carried out until the monitoring time is reached. The average similarity will be obtained by averaging all the similarities acquired during the monitoring time, and the average similarity will be compared with the minimum similarity threshold, and corresponding responses will be made according to the comparison result.

[0017] In some embodiments, if the average similarity is greater than or equal to the minimum similarity threshold, the judgment that the traffic sign on the signboard is clear will be maintained without additional response; if the average similarity is less than the minimum similarity threshold, the maintenance personnel will be notified to go to the position of the signboard to check the reason and perform maintenance.

[0018] The present invention also provides the following technical solution: A highway inspection robot inspection system based on image processing, including:

[0019] An image acquisition module, which is used to establish a traffic sign image library, take images of the signboards set on the highway during the inspection of the highway by the inspection robot, compare the captured images with the standard images in the image library, and obtain the similarity of the sign images;

[0020] An image comparison module, which is used to set a clear similarity threshold, compare the sign image similarity with the clear similarity threshold. When the sign image similarity is less than the clear similarity threshold, the traffic sign on the signboard will be marked as a suspected defective sign, and the inspection robot will be controlled to stop moving on the steel guardrail to continuously capture and collect image information of the suspected defective sign;

[0021] A change monitoring module, which is used to continuously monitor the suspected defective sign to obtain whether there is a change in the similarity after comparing it with the standard image in the image library. After the inspection robot stops on the steel guardrail for more than the preset stay and shooting time, if the similarity changes, the inspection robot will move in a loop within a preset length range along the steel guardrail;

[0022] A result feedback module, which is used to obtain the maximum similarity after comparing the suspected defective sign collected when the inspection robot moves with the standard image in the image library, compare the maximum similarity collected when the inspection robot moves with the clear similarity threshold, and make corresponding responses according to the comparison result.

[0023] The present invention further provides a computer-readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above-mentioned highway inspection robot inspection method based on image processing.

[0024] The technical solution provided by the present invention has the following beneficial effects compared with the prior art:

[0025] First, the inspection robot of the present invention automatically executes the inspection task. The inspection robot can collect the traffic sign images on the road in real time, and through comparing the collected images with the standard images in the image library for real-time analysis, it can quickly judge whether the signs are clear, and can timely discover problems and make responses.

[0026] Second, through the design of the clarity similarity threshold, when the similarity in the images collected by the inspection robot is lower than the clarity similarity threshold, the robot can be controlled to change the inspection method, so that it can collect images at different angles and different time states at the position where a suspected defective sign is detected, reducing the situation that non-faulty signs are misjudged as faulty signs.

[0027] Third, by implementing the similarity change analysis strategy, the present invention can analyze the degree of interference of external factors to distinguish the degree of interference of a suspected faulty sign close to clarity by external factors, avoiding unnecessary maintenance operations caused by external factor influences.

[0028] Fourth, by comparing the average similarity with the lowest similarity threshold, the present invention can timely discover external interference factors that are not easy to eliminate and seriously affect the readability of signs, and issue a fault notification to ensure that the actual problems of traffic signs on the signboard can be timely discovered and repaired. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic flowchart of a highway inspection robot inspection method based on image processing according to the present invention;

[0030] Figure 2 It is a schematic diagram of the modules of a highway inspection robot inspection system based on image processing according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0032] It can be understood that the term "one" should be understood as "at least one" or "one or more". That is, in one embodiment, the number of one element can be one, while in other embodiments, the number of this element can be multiple. The term "one" cannot be understood as a limitation on the number.

[0033] The present invention provides a highway patrol robot inspection method based on image processing, as Figure 1 shown, the method includes the following steps:

[0034] Step 1: Establish a traffic sign image library. The image library contains high-definition standard images of all traffic signs used along the patrol route. During the process of the patrol robot patrolling along the highway, images of the signs set on the highway are taken to obtain the traffic sign image information on the signs. The captured images are compared with the standard images in the image library to obtain the sign image similarity. The sign image similarity represents the degree of closeness between the traffic signs on the signs captured by the patrol robot and the standard images in the image library. The sign image similarity is at most 100%. The larger its value, the clearer and more standard the traffic signs on the signs are. The smaller its value, the more blurred and difficult to identify the traffic signs on the signs are;

[0035] Step 2: Set a clear similarity threshold, and compare the sign image similarity with the clear similarity threshold. When the sign image similarity is greater than or equal to the clear similarity threshold, it means that the traffic signs on the signs captured by the patrol robot are relatively similar to the standard images in the sign image library, and the traffic signs on the highway signs are clear, and no reaction is made; when the sign image similarity is less than the clear similarity threshold, it means that the similarity degree of the traffic signs on the signs captured by the patrol robot and the standard images in the sign image library is not ideal. Mark the traffic signs on the signs as suspected defective signs, and control the patrol robot to stop advancing on the steel guardrail to continuously take pictures of the suspected defective signs and acquire image information;

[0036] Step 3: In the continuous monitoring of suspected defective signs, obtain whether there is a change in the similarity after comparing it with the standard image in the image library. After the inspection robot stops on the steel guardrail for more than the preset stop shooting time, if the similarity has not changed, the sign with the suspected defective sign is marked as a faulty sign, and the maintenance personnel are notified to repair and replace the traffic sign. The inspection robot continues to move along the steel guardrail to perform the inspection task; if the similarity changes, it means that the image information of the traffic sign on the signboard when the inspection robot collected it has changed from the image information of the subsequent continuous monitoring. This change The previous similarity may be caused by light reflection, angle problems, weather conditions (such as rain and fog), camera shaking, or dynamic occlusions (shaking branches, advertising cloth or partial occlusion by moving vehicles), which cannot represent that the traffic signs on the signs have substantial blur and defects. The inspection robot will move along the steel guardrail in a cycle within a preset length range (such as 10-20 meters), and the camera end of the inspection robot will focus on the suspected defective sign while moving, so as to obtain the maximum similarity after comparing the suspected defective sign collected by the inspection robot while moving with the standard image in the image library;

[0037] Step 4: compare the maximum similarity collected when the patrol robot moves with the clear similarity threshold, and make corresponding responses according to the comparison results. Specifically, when the maximum similarity collected when the patrol robot moves is less than the clear similarity threshold, it means that after changing the shooting angle and distance to collect image information of the traffic sign on the sign, the collected traffic sign image and the standard image in the image library still have a large gap, and the sign with suspected defective signs is marked as a faulty sign, and the maintenance personnel are notified to repair and replace the traffic sign, and the patrol robot continues to move along the steel guardrail to perform the inspection task; when the maximum similarity collected when the patrol robot moves is greater than or equal to the clear similarity threshold, it means that after changing the shooting angle and distance to collect image information of the traffic sign on the sign, the collected traffic sign image can be close to the standard image similarity in the image library, which means that the reason for the previous unsatisfactory similarity is that it is affected by external factors. It will be judged that the traffic sign on the sign is clear, and no additional response will be made. The patrol robot continues to move along the steel guardrail to perform the inspection task.

[0038] Furthermore, a minimum similarity threshold is set. The minimum similarity threshold should be less than and close to the clear similarity threshold. For example, the clear similarity threshold can be set at 80%, and the minimum similarity threshold can be set between 70% and 75%. When the maximum similarity collected by the inspection robot during movement is less than the clear similarity threshold, the maximum similarity it collected is compared with the minimum similarity threshold, and corresponding reactions are made according to the comparison results. Specifically, if the maximum similarity collected by the inspection robot during movement is less than the minimum similarity threshold, it means that the similarity between the traffic sign image collected after the inspection robot moves and the standard image in the image library is not ideal, and the operation of fault notification is continued without additional reaction; if the maximum similarity collected by the inspection robot during movement is greater than or equal to the minimum similarity threshold, it means that the similarity between the traffic sign image collected after the inspection robot moves and the standard image in the image library has changed, indicating that the traffic sign on the signboard is affected by external factors, and its maximum similarity is close to the clear similarity threshold. At this time, external factors may still interfere with the image information of the traffic sign collected by the inspection robot. Therefore, a similarity change analysis strategy is executed.

[0039] The similarity change analysis strategy includes setting a change amount threshold, obtaining the similarity change data between the suspected defect sign and the standard image collected by the inspection robot during a single cycle of movement along the preset length range of the steel guardrail, calculating the difference between the maximum similarity and the minimum similarity collected to obtain the similarity change amount, and comparing the similarity change amount with the change amount threshold, and making corresponding reactions according to the comparison results: if the similarity change amount is less than or equal to the change amount threshold, it means that after the inspection robot moves and takes pictures, the change range of similarity does not change significantly, indicating that the degree of interference of external factors on image information during image acquisition is low, and the operation of fault notification is continued; if the similarity change amount is greater than the change amount threshold, it means that after the inspection robot moves and takes pictures, the change range of similarity has changed significantly, indicating that the interference of external factors on image information during image acquisition is obvious. The main reason for the low similarity between the traffic sign on the signboard and the standard image in the image library is external interference factors, and it should not be considered as a fuzzy fault of the sign itself. Therefore, when the maximum similarity collected by the inspection robot during movement is greater than or equal to the minimum similarity threshold, it is determined that the traffic sign on the signboard is clear, and the inspection robot continues to move along the steel guardrail to perform the inspection task.

[0040] As another preferred embodiment of the present invention, a holding monitoring time is set. When the change amount of the monitored similarity is greater than the change amount threshold, the inspection robot will move on the steel guardrail to the position where the maximum similarity between the suspected fault sign and the standard image is captured. Without moving, the robot continuously collects image information of the suspected fault sign until the holding monitoring time is reached. The average similarity is obtained by averaging all the similarities acquired during the holding monitoring time, and the average similarity is compared with the minimum similarity threshold: If the average similarity is greater than or equal to the minimum similarity threshold, it means that when the traffic sign on the signboard is observed at a suitable position, even with external factor interference, it can still maintain a certain readability. Then, the judgment on the clarity of the traffic sign on the signboard is maintained without additional reaction; If the average similarity is less than the minimum similarity threshold, it means that the influence of external factors on the clarity of the traffic sign is obvious, resulting in unsatisfactory readability of the traffic sign. Although there may be no problems such as blurring or fading of the traffic sign itself, there may be floating dynamic objects hanging on the signboard, or the position of the signboard is blocked by objects such as branches or advertising cloth, which will still cause the driver to be unable to accurately observe the traffic sign. Therefore, the maintenance personnel will be notified to go to the position of the signboard to check the reason and perform maintenance; The reason for doing this is that traffic signs on highways are often affected by environmental factors (such as light, weather, dynamic objects, etc.). This external interference may temporarily affect the clarity of the image, but it does not mean that there is a problem with the sign itself. Therefore, it is necessary to filter out external interference through continuous monitoring and multiple image acquisitions to accurately judge the actual state of the sign. However, external interference factors can also cause the traffic sign to be substantially unreadable. Therefore, by moving the inspection robot in a single cycle to find the position with the maximum similarity, most of the temporary external factors such as light reflection, angle, and moving vehicle occlusion have been excluded. By setting the holding monitoring time, the inspection robot can take multiple photos of the suspected fault sign. If the suspected fault sign still deviates significantly from the standard image in the image library at this time, it means that the interference factors affecting the sign readability on this signboard are serious and the interference factors are not easily excluded. It should also be maintained and repaired according to the fault signboard to ensure the readability of traffic signs on highways.

[0041] Generally speaking, the present invention aims to design an inspection method for highway patrol robots based on image processing. Aiming at the problem that traffic signs on highways cannot be detected and responded to in a timely manner when damaged, the present invention automatically executes inspection tasks through patrol robots. The patrol robots can collect traffic sign images on the road in real time, and conduct real-time analysis by comparing the collected images with the standard images in the image library, quickly judge whether the signs are clear, can discover problems and make responses in a timely manner, and reduce the time and labor costs of manual inspections. Through the design of the clear similarity threshold, when the similarity in the images collected by the patrol robot is lower than the clear similarity threshold, the robot can be controlled to change the inspection method, so that it can collect images at different angles and at different time states at the position where a suspected defective sign is detected, and eliminate the interference of external factors on the collected image information. This process helps to improve the accuracy of judgment and reduce the situation where non-faulty signs are misjudged as faulty signs. By implementing the similarity change analysis strategy, the degree of interference of external factors on a suspected faulty sign close to being clear can be analyzed. If the interference has a significant impact on the image quality, it can be judged that the image problem is caused by external interference rather than the sign itself, avoiding unnecessary maintenance operations caused by external factors. At the same time, after excluding accidental interference, by comparing the average similarity with the lowest similarity threshold, external interference factors that are not easy to exclude and have a serious impact on the readability of the sign can be discovered in a timely manner. When the interference factor is obvious, it can be judged that the readability of the traffic sign is seriously affected, and a fault notification is issued to ensure that the actual problems of the traffic signs on the sign can be discovered and repaired in a timely manner.

[0042] The present invention provides an inspection system for highway patrol robots based on image processing, as Figure 2 shown, including:

[0043] An image acquisition module, which is used to establish a traffic sign image library, use a patrol robot to take images of the signs set on the highway during the patrol along the highway, and compare the taken images with the standard images in the image library to obtain the sign image similarity;

[0044] An image comparison module, which is used to set a clear similarity threshold, compare the sign image similarity with the clear similarity threshold in terms of size. When the sign image similarity is less than the clear similarity threshold, mark the traffic sign on the sign as a suspected defective sign, and control the patrol robot to stop moving on the steel guardrail to continuously take pictures of the suspected defective sign and collect image information;

[0045] A change monitoring module, which is used to continuously monitor the suspected defect signs and obtain whether there is a change in the similarity after comparing them with the standard images in the image library. After the inspection robot stops on the steel guardrail for a time exceeding the preset stay and shooting time, if the similarity changes, the inspection robot will move in a loop within a preset length range along the steel guardrail;

[0046] A result feedback module, which is used to obtain the maximum similarity after comparing the suspected defect signs collected during the movement of the inspection robot with the standard images in the image library, compare the maximum similarity collected during the movement of the inspection robot with the clear similarity threshold, and make corresponding responses according to the comparison results.

[0047] In the embodiments disclosed in the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. The embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part, and / or installed from a removable medium. When the computer program is executed by the central processing unit, the above-mentioned functions defined in the methods of the present application are executed. It should be noted that the computer-readable medium in the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wire segments, a portable computer disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or combined with an instruction execution system, apparatus, or device. In the present application, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, in which the computer-readable program code is carried. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable medium can send, propagate, or transmit a program for use by or combined with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless segments, wire segments, optical cables, RF, etc., or any suitable combination of the above.

[0048] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0049] Those skilled in the art should understand that the above description is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed in the present application should be covered by the protection scope of the present application.

Claims

1. A highway patrol robot inspection method based on image processing, characterized in that, The method includes the following steps: Establish a traffic sign image library. During the inspection of the highway by the inspection robot, take images of the signs set on the highway, compare the captured images with the standard images in the image library, and obtain the similarity of the sign images; Set a clear similarity threshold, compare the sign image similarity with the clear similarity threshold. When the sign image similarity is less than the clear similarity threshold, mark the traffic sign on the sign as a suspected defective sign, and control the inspection robot to stop moving on the steel guardrail to continuously take pictures of the suspected defective sign and collect image information; During the continuous monitoring of the suspected defective sign, obtain whether the similarity after comparison with the standard image in the image library has changed. After the inspection robot stops on the steel guardrail for more than the preset stay and shooting time, if the similarity changes, the inspection robot will move in a cycle within the preset length range along the steel guardrail; Obtain the maximum similarity of the suspected defective sign collected when the inspection robot moves compared with the standard image in the image library, compare the maximum similarity collected when the inspection robot moves with the clear similarity threshold, and make corresponding responses according to the comparison results.

2. The inspection method of the highway patrol robot based on image processing according to claim 1, characterized in that, When the maximum similarity collected when the inspection robot moves is less than the clear similarity threshold, mark the sign with the suspected defective sign as a faulty sign, and notify the maintenance personnel to repair and replace the traffic sign. The inspection robot continues to move along the steel guardrail to perform the inspection task; When the maximum similarity collected when the inspection robot moves is greater than or equal to the clear similarity threshold, it is determined that the traffic sign on the sign is clear and no response is made. The inspection robot continues to move along the steel guardrail to perform the inspection task.

3. The inspection method of the highway patrol robot based on image processing according to claim 2, wherein, Set a minimum similarity threshold. When the maximum similarity collected when the inspection robot moves is less than the clear similarity threshold, compare the maximum similarity it collects with the minimum similarity threshold, and make corresponding responses according to the comparison results.

4. The inspection method of a highway patrol robot based on image processing according to claim 3, characterized in that, If the maximum similarity collected when the inspection robot moves is less than the minimum similarity threshold, continue to perform the operation of notifying of the fault without making additional responses; if the maximum similarity collected when the inspection robot moves is greater than or equal to the minimum similarity threshold, then execute the similarity change analysis strategy.

5. The inspection method of a highway patrol robot based on image processing according to claim 4, wherein The similarity change analysis strategy includes setting a change amount threshold, obtaining the similarity change data of the suspected defective sign and the standard image collected when the inspection robot moves in a cycle within the preset length range along the steel guardrail, calculating the difference between the maximum similarity and the minimum similarity to obtain the similarity change amount, and comparing the similarity change amount with the change amount threshold, and making corresponding responses according to the comparison results.

6. The inspection method of a highway patrol robot based on image processing according to claim 5, characterized in that, If the similarity change amount is less than or equal to the change amount threshold, continue to perform the operation of notifying of the fault; if the similarity change amount is greater than the change amount threshold, it is determined that the traffic sign on the sign is clear, and the inspection robot continues to move along the steel guardrail to perform the inspection task.

7. The inspection method of a highway patrol robot based on image processing according to claim 6, characterized in that Set the retention monitoring time. When the change amount of the monitored similarity is greater than the change amount threshold, the inspection robot will move on the steel guardrail to the position with the maximum similarity between the suspected fault sign and the standard image captured. When the robot remains stationary, continuous image information collection of the suspected fault sign will be carried out until the retention monitoring time is reached. The average similarity will be obtained by averaging all the similarities acquired during the retention monitoring time, and the average similarity will be compared with the minimum similarity threshold, and corresponding responses will be made according to the comparison result.

8. A highway patrol robot inspection method based on image processing according to claim 7, characterized in that, If the average similarity is greater than or equal to the minimum similarity threshold, the judgment that the traffic sign on the signboard is clear will be maintained without additional response; if the average similarity is less than the minimum similarity threshold, the maintenance personnel will be notified to go to the signboard position to check the reason and perform maintenance.

9. An inspection system for highway patrol robots based on image processing, characterized in that, The highway inspection robot inspection method based on image processing according to any one of claims 1-8 includes: An image acquisition module, which is used to establish a traffic sign image library, use the inspection robot to take images of the signboards set on the highway during the inspection along the highway, compare the captured images with the standard images in the image library, and obtain the sign image similarity. An image comparison module, which is used to set a clear similarity threshold, compare the sign image similarity with the clear similarity threshold. When the sign image similarity is less than the clear similarity threshold, the traffic sign on the signboard will be marked as a suspected defective sign, and the inspection robot will be controlled to stop moving on the steel guardrail to continuously capture and collect image information of the suspected defective sign. A change monitoring module, which is used to obtain whether there is a change in the similarity after comparing the suspected defective sign with the standard image in the image library during the continuous monitoring of the suspected defective sign. After the inspection robot stops on the steel guardrail for more than the preset stay and shooting time, if the similarity changes, the inspection robot will make a cyclic movement within a preset length range along the steel guardrail. A result feedback module, which is used to obtain the maximum similarity after comparing the suspected defective sign captured when the inspection robot moves with the standard image in the image library, compare the maximum similarity captured when the inspection robot moves with the clear similarity threshold, and make corresponding responses according to the comparison result.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the highway inspection robot inspection method based on image processing according to any one of claims 1-8 above.

Images