An image recognition-based vehicle parking safety intelligent monitoring method

Abstract

The application discloses a kind of vehicle parking safety intelligent monitoring methods based on image recognition, it is related to image recognition field;Street video image is acquired, video image processing model is set, street video image is eliminated and is detected by video image processing model, and then parking space image and parking vehicle image are acquired;Single direction transmission chain is set, to parking space and parking vehicle are respectively as center data node, connection is generated parking space real-time data network and parking vehicle real-time data network by single direction transmission chain, and then vehicle parking management model is generated;Based on vehicle parking management model, abnormal parking space image is acquired by processing parking space image, and according to parking space image information data, parking space is safely managed;And according to parking vehicle real-time data network, abnormal parking vehicle is acquired, and according to parking vehicle image information data, abnormal parking vehicle is safely managed;The application improves the standardization of vehicle parking and the convenience of safety monitoring.

Description

Technical Field

[0001] This invention relates to the field of image recognition, specifically to an intelligent monitoring method for vehicle parking safety based on image recognition. Background Technology

[0002] Image recognition refers to the technology of using computers to process, analyze, and understand images in order to identify targets and objects of various patterns. It is a practical application of deep learning algorithms. Currently, image recognition technology is generally divided into face recognition and object recognition. Image recognition is an important field of artificial intelligence. Object recognition mainly refers to the perception and understanding of objects and their environment in the three-dimensional world, belonging to the advanced category of computer vision. It is a research direction that combines artificial intelligence, systems science, and other disciplines based on digital image processing and recognition. Its research results are widely used in various industrial and exploration robots.

[0003] Vehicle parking is ubiquitous in modern life, existing not only in parking lots but also in various parking spaces such as street parking spaces, residential parking spaces, and park parking spaces. However, improper parking leads to parking safety issues. For example, haphazard street parking causes traffic congestion and safety problems. Real-time monitoring of street parking is impossible, requiring manual on-site management, which results in delays in managing parked vehicles. To address these issues, image recognition is used to monitor vehicle parking. Therefore, this paper presents an intelligent monitoring method for vehicle parking safety based on image recognition. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a vehicle parking safety intelligent monitoring method based on image recognition;

[0005] The objective of this invention can be achieved through the following technical solution: a vehicle parking safety intelligent monitoring method based on image recognition, the method comprising the following steps:

[0006] Step S1: Acquire street video images, set up a video image processing model, and use the video image processing model to eliminate and sort the street video images to obtain parking space images and parked vehicle images;

[0007] Step S2: Set up a one-way transmission chain, with parking spaces and parked vehicles as central data nodes, to store parking space image information data and parking vehicle image information data respectively. Connect them through the one-way transmission chain to generate a real-time data network for parking spaces and a real-time data network for parked vehicles, thereby generating a vehicle parking management model.

[0008] Step S3: Process the parking space images based on the vehicle parking management model to obtain abnormal parking space images, and perform security management on the abnormal parking space images according to the corresponding parking space image information data;

[0009] Step S4: Obtain abnormal parking vehicles based on the real-time parking vehicle data network, and perform safety management on abnormal parking vehicles based on the parking vehicle image information data.

[0010] Furthermore, the process of setting up the video image processing model includes:

[0011] A specific acquisition time point is set, and street video images are acquired in real time through street cameras according to the specific acquisition time point; a video image processing model is set, which includes an elimination unit and a sorting unit;

[0012] Acquire and store several vehicle models to generate a vehicle model library; wireless communication connection cancellation unit;

[0013] The elimination unit is used to perform image elimination on street video images according to the vehicle model library to obtain street vehicle video images;

[0014] The sorting unit is used to sort street vehicle video images and obtain parking space images and parked vehicle images.

[0015] Furthermore, the process of acquiring the parking space image and the parked vehicle image includes:

[0016] The street video images are sent to the video image processing model. The elimination unit marks and retains the vehicles corresponding to the vehicle model library in the street video images, and removes the remaining unmarked ones, thereby generating street vehicle video images and sending them to the sorting unit.

[0017] The sorting unit pre-stores a street parking space distribution map, obtains the vehicles corresponding to the street parking space distribution map in the street vehicle video image, and then crops the corresponding street vehicle video image to obtain a parking space image. Finally, it crops the remaining vehicles in the street vehicle video image to obtain a parked vehicle image.

[0018] The shooting times corresponding to the parking images and parked vehicle images are obtained and stored separately.

[0019] Furthermore, the generation process of the parking space real-time data network and the parking vehicle real-time data network includes:

[0020] The unidirectional transmission chain includes an update chain and an early warning chain; the update chain is used to transmit information data to the central data node for updating; the early warning chain is used to transmit information data to the terminal for early warning, the terminal including the vehicle owner's mobile terminal and the management terminal;

[0021] The parking space and the parked vehicle are respectively generated as the central data node for the parking space and the central data node for the parked vehicle.

[0022] Parking space image nodes and parking vehicle image nodes are generated from parking space images and parking vehicle images respectively. Then, the parking space image nodes and parking vehicle image nodes are connected to the parking space central data node and parking vehicle central data node respectively through the update chain, thereby generating the parking space real-time data network and the parking vehicle real-time data network respectively.

[0023] Furthermore, the generation process of the vehicle parking management model includes:

[0024] Acquire parking space image information data and parking vehicle image information data corresponding to the parking space image and the parking vehicle image respectively, and send them to the corresponding parking space center data node and parking vehicle center data node for connection and storage;

[0025] The parking space image information data includes license plate number, contact information, parking space code, and shooting time; the parking vehicle image information data includes license plate number, contact information, parking location, and shooting time.

[0026] A vehicle parking management model is generated by connecting the real-time data network of parking spaces and the real-time data network of parked vehicles through a data link.

[0027] Furthermore, the process of acquiring the abnormal parking space image includes:

[0028] The parking space image is edge-processed according to the street parking space distribution map to obtain a standard parking space image. The vehicle integrity of the standard parking space image is judged according to the vehicle model. If the standard parking space image has a complete vehicle model, the corresponding vehicle is in a complete state and a safe parking space image is generated. Otherwise, the corresponding vehicle is in an incomplete state and an abnormal parking space image is generated.

[0029] Furthermore, the process of managing the safety of parking spaces includes:

[0030] Obtain parking space image information data corresponding to abnormal parking space images, obtain contact information based on parking space image information data, and then send the license plate number and parking space code to the vehicle owner terminal through the early warning chain based on the contact information, and send the vehicle's standard processing time deadline for early warning.

[0031] Based on the deadline for vehicle standard processing, street video images are acquired again, and then the parking space images corresponding to the abnormal parking space images are obtained. The integrity of the abnormal parking space images is checked again. If it is complete, a safe parking space image is generated, and the corresponding parking space image node is removed. If it is incomplete, the parking space image information data is sent to the management terminal through the early warning chain. Upon receiving the corresponding parking space image information data, the management terminal obtains the vehicle corresponding to the license plate number based on the parking space code and issues a penalty warning to the vehicle. If no vehicle model exists in the abnormal parking space image, an empty parking space image is generated, and the corresponding parking space image node is removed from the real-time parking space data network and updated.

[0032] Furthermore, the process of safely managing abnormally parked vehicles includes:

[0033] All parking vehicle images corresponding to all parking vehicle image nodes in the real-time parking vehicle data network are marked as abnormal parking vehicles. The corresponding parking vehicle image information data is obtained from the parking vehicle central data node and sent to the vehicle owner's mobile terminal through the early warning chain according to the contact information. The deadline for standardized vehicle processing is also sent as an early warning.

[0034] Similarly, based on the deadline for standardized vehicle processing, the image of the abnormally parked vehicle is retrieved again and judged. If the vehicle is not parked in accordance with regulations, the image information data of the parked vehicle is sent to the management terminal for penalty management through the early warning chain; if the vehicle is parked in accordance with regulations, the corresponding image node of the parked vehicle is removed and the real-time data network of the parked vehicle is updated.

[0035] Compared with the prior art, the beneficial effects of the present invention are:

[0036] 1. Acquire street video images, set up a video image processing model, and use the video image processing model to eliminate and sort the street video images to obtain parking space images and parked vehicle images; set up a one-way transmission chain, with parking spaces and parked vehicles as central data nodes, and connect them through the one-way transmission chain to generate a real-time data network for parking spaces and a real-time data network for parked vehicles, thereby generating a vehicle parking management model and solving the problem of convenient vehicle parking.

[0037] 2. By judging the integrity of parking space images, abnormal parking space images are obtained. Then, the corresponding parking space image information data is obtained through the central data node and sent to the vehicle owner through the early warning chain. According to the deadline of the vehicle's standardized processing time, abnormal parking space images are obtained again and their integrity is judged again to determine whether the vehicle corresponding to the abnormal parking space image has been properly processed. The corresponding parking space real-time data network is updated. Through the parking space real-time data network, abnormal parking space images can be monitored more clearly, and early warning notification management through the early warning chain improves the standardization of street vehicle parking. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0039] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings. Example

[0041] like Figure 1 As shown, an intelligent monitoring method for vehicle parking safety based on image recognition is disclosed, the method comprising the following steps:

[0042] Step S1: Acquire street video images, and perform removal and sorting to obtain parking space images and parked vehicle images;

[0043] Step S2: Set up a one-way transmission chain, with parking spaces and parked vehicles as central data nodes, to store parking space image information data and parking vehicle image information data respectively. Connect them through the one-way transmission chain to generate a real-time data network for parking spaces and a real-time data network for parked vehicles, thereby generating a vehicle parking management model.

[0044] Step S3: Process the parking space images based on the vehicle parking management model to obtain abnormal parking space images, and perform security management on the abnormal parking space images according to the corresponding parking space image information data;

[0045] Step S4: Obtain abnormal parking vehicles based on the real-time parking vehicle data network, and perform safety management on abnormal parking vehicles based on the parking vehicle image information data; Example

[0046] This embodiment further defines embodiment 1, and step S1 is implemented through the following process:

[0047] A specific acquisition time point is set, and street video images are acquired in real time through street cameras according to the specific acquisition time point; a video image processing model is set, which includes an elimination unit and a sorting unit;

[0048] Acquire and store several vehicle models to generate a vehicle model library; wireless communication connection cancellation unit;

[0049] The elimination unit is used to perform image elimination on street video images according to the vehicle model library to obtain street vehicle video images;

[0050] The sorting unit is used to sort street vehicle video images to obtain parking space images and parked vehicle images;

[0051] It should be further explained that, in the specific implementation process, if the street video images acquired on the street are from a whole day, it is impossible to determine whether a vehicle is parked or in a traffic jam during rush hour. Therefore, feature collection time points are set, including but not limited to morning, noon, evening, and night; the street video images acquired in this way can better determine the parking status of vehicles.

[0052] The street video images are sent to the video image processing model. The elimination unit marks and retains the vehicles corresponding to the vehicle model library in the street video images, and removes the remaining unmarked ones, thereby generating street vehicle video images and sending them to the sorting unit.

[0053] It should be further explained that, in the specific implementation process, the vehicle model is used to represent the shape of a vehicle, including but not limited to cars, trucks, convertibles, etc.; by removing irrelevant people from the street video based on the vehicle model library, the clarity of the street video image and the ease of processing are improved.

[0054] The sorting unit pre-stores a street parking space distribution map, obtains the vehicles corresponding to the street parking space distribution map in the street vehicle video image, and then crops the corresponding street vehicle video image to obtain a parking space image. Finally, it crops the remaining vehicles in the street vehicle video image to obtain a parked vehicle image.

[0055] The capture times corresponding to the parking images and parked vehicle images are obtained and stored respectively;

[0056] It should be further explained that, in the specific implementation process, the images of vehicles on the street are divided into two categories: images of parking spaces and images of parked vehicles. This allows for better analysis of vehicles on the street and, in turn, safe management of vehicle parking. Example

[0057] This embodiment further defines embodiment 1, and step S2 is implemented through the following process:

[0058] The unidirectional transmission chain includes an update chain and an early warning chain; the update chain is used to transmit information data to the central data node for updating; the early warning chain is used to transmit information data to the terminal for early warning, the terminal including the vehicle owner's mobile terminal and the management terminal;

[0059] The parking space and the parked vehicle are respectively generated as the central data node for the parking space and the central data node for the parked vehicle.

[0060] Parking space image nodes and parking vehicle image nodes are generated from parking space images and parking vehicle images respectively. The parking space image nodes and parking vehicle image nodes are then connected to the parking space central data node and parking vehicle central data node respectively through an update chain, thereby generating a parking space real-time data network and a parking vehicle real-time data network respectively.

[0061] Acquire parking space image information data and parking vehicle image information data corresponding to the parking space image and the parking vehicle image respectively, and send them to the corresponding parking space center data node and parking vehicle center data node for connection and storage;

[0062] Furthermore, the parking space image information data includes license plate number, contact information, parking space code, and shooting time; the parking vehicle image information data includes license plate number, contact information, parking location, and shooting time.

[0063] A vehicle parking management model is generated by connecting the real-time data network of parking spaces and the real-time data network of parked vehicles through a data link.

[0064] It should be further explained that, in the specific implementation process, by setting up a one-way transmission chain for the update chain and the early warning chain, information data can be better preserved and leaks can be prevented; generating corresponding data nodes can better process the data. Example

[0065] This embodiment further defines embodiment 1, and step S3 is implemented through the following process:

[0066] The parking space image is edge-processed according to the street parking space distribution map to obtain a standard parking space image. The vehicle integrity of the standard parking space image is judged according to the vehicle model. If the standard parking space image has a complete vehicle model, the corresponding vehicle is in a complete state and a safe parking space image is generated. Otherwise, the corresponding vehicle is in an incomplete state and an abnormal parking space image is generated.

[0067] Obtain parking space image information data corresponding to abnormal parking space images, obtain contact information based on parking space image information data, and then send the license plate number and parking space code to the vehicle owner terminal through the early warning chain based on the contact information, and send the vehicle's standard processing time deadline for early warning.

[0068] The vehicle's standardized processing time is sent to the corresponding parking space image node for storage;

[0069] Based on the deadline for vehicle standard processing, street video images are acquired again, and then the parking space image corresponding to the abnormal parking space image is obtained. The integrity of the abnormal parking space image is checked again. If it is complete, a safe parking space image is generated, and the corresponding parking space image node is removed. If it is incomplete, the parking space image information data is sent to the management terminal through the early warning chain. The management terminal receives the corresponding parking space image information data, obtains the vehicle corresponding to the license plate number according to the parking space code, and issues a penalty warning to the vehicle. If the abnormal parking space image does not contain a vehicle model, an empty parking space image is generated, and the corresponding parking space image node is removed from the real-time parking space data network and updated.

[0070] It should be further explained that, in the specific implementation process, abnormal parking space images are obtained by judging the integrity of parking space images. Then, the corresponding parking space image information data is obtained through the central data node and sent to the vehicle owner through the early warning chain to issue an early warning. Based on the deadline of the vehicle's standardized processing time, abnormal parking space images are obtained again and their integrity is judged again to determine whether the vehicle corresponding to the abnormal parking space image has been properly processed. The corresponding real-time parking space data network is then updated. Through the real-time parking space data network, abnormal parking space images can be monitored more clearly, and early warning notification management through the early warning chain improves the standardization of street vehicle parking. Example

[0071] This embodiment further defines embodiment 1, and step S4 is implemented through the following process:

[0072] All parking vehicle images corresponding to all parking vehicle image nodes in the real-time parking vehicle data network are marked as abnormal parking vehicles. The corresponding parking vehicle image information data is obtained from the parking vehicle central data node and sent to the vehicle owner's mobile terminal through the early warning chain according to the contact information. The deadline for standardized vehicle processing is also sent as an early warning.

[0073] Similarly, based on the deadline for standardized vehicle processing, the image of the abnormally parked vehicle is retrieved again and judged. If the vehicle is not parked in accordance with regulations, the image information data of the parked vehicle is sent to the management terminal for penalty management through the early warning chain; if the vehicle is parked in accordance with regulations, the corresponding image node of the parked vehicle is removed and the real-time data network of the parked vehicle is updated.

[0074] It should be further explained that abnormally parked vehicles on the street are classified into vehicles parked in parking spaces and vehicles parked outside parking spaces. These two types of abnormally parked vehicles are then processed separately, and an early warning chain is set up. The abnormally parked vehicles are then monitored according to their classification level through the early warning chain, which improves the accuracy of monitoring.

[0075] The features and exemplary embodiments of various aspects of this application will be described in detail above. In order to make the purpose, technical solution and advantages of this application clearer, the application will be further described in detail above with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit this application. For those skilled in the art, this application can be implemented without some of the details in these specific details. The above description of the embodiments is only to provide a better understanding of this application by showing examples of this application.

[0076] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A vehicle parking safety intelligent monitoring method based on image recognition, characterized in that, The method includes the following steps: Step S1: Acquire street video images, set up a video image processing model, and use the video image processing model to eliminate and sort the street video images to obtain parking space images and parked vehicle images; Step S2: Set up a one-way transmission chain, and set parking spaces and parked vehicles as central data nodes to store parking space image information data and parking vehicle image information data respectively. Connect them through the one-way transmission chain to generate a real-time data network for parking spaces and a real-time data network for parking vehicles, thereby generating a vehicle parking management model. Step S3: Process the parking space images based on the vehicle parking management model to obtain abnormal parking space images, and perform security management on the abnormal parking space images according to the corresponding parking space image information data; Step S4: Obtain abnormal parking vehicles based on the real-time parking vehicle data network, and perform safety management on abnormal parking vehicles based on the parking vehicle image information data; The process of setting up the video image processing model includes: A specific acquisition time point is set, and street video images are acquired in real time through street cameras according to the specific acquisition time point; a video image processing model is set, which includes an elimination unit and a sorting unit; Acquire and store several vehicle models to generate a vehicle model library; wireless communication connection cancellation unit; The elimination unit is used to perform image elimination on street video images according to the vehicle model library to obtain street vehicle video images; The sorting unit is used to sort street vehicle video images to obtain parking space images and parked vehicle images; The process of acquiring the parking space image and the parked vehicle image includes: The street video images are sent to the video image processing model. The elimination unit marks and retains the vehicles corresponding to the vehicle model library in the street video images, and removes the remaining unmarked ones, thereby generating street vehicle video images and sending them to the sorting unit. The sorting unit pre-stores a street parking space distribution map, obtains the vehicles corresponding to the street parking space distribution map in the street vehicle video image, and then crops the corresponding street vehicle video image to obtain a parking space image. Finally, it crops the remaining vehicles in the street vehicle video image to obtain a parked vehicle image. The shooting times corresponding to the parking images and parked vehicle images are obtained and stored separately.

2. The intelligent monitoring method for vehicle parking safety based on image recognition according to claim 1, characterized in that, The generation process of the parking space real-time data network and the parking vehicle real-time data network includes: The unidirectional transmission chain includes an update chain and an early warning chain; the update chain is used to transmit information data to a central data node for storage; the early warning chain is used to transmit information data to a terminal for early warning; the terminal includes a vehicle owner's mobile terminal and a management terminal. The parking space and the parked vehicle are respectively generated as the central data node for the parking space and the central data node for the parked vehicle. Parking space image nodes and parking vehicle image nodes are generated from parking space images and parking vehicle images respectively. Then, the parking space image nodes and parking vehicle image nodes are connected to the parking space central data node and parking vehicle central data node respectively through the update chain, thereby generating the parking space real-time data network and the parking vehicle real-time data network respectively.

3. The intelligent monitoring method for vehicle parking safety based on image recognition according to claim 2, characterized in that, The generation process of the vehicle parking management model includes: Acquire parking space image information data and parking vehicle image information data corresponding to the parking space image and the parking vehicle image respectively, and send them to the corresponding parking space center data node and parking vehicle center data node for connection and storage; The parking space image information data includes license plate number, contact information, parking space code, and shooting time; the parking vehicle image information data includes license plate number, contact information, parking location, and shooting time. A vehicle parking management model is generated by connecting the real-time data network of parking spaces and the real-time data network of parked vehicles through a data link.

4. The intelligent monitoring method for vehicle parking safety based on image recognition according to claim 3, characterized in that, The process of acquiring the abnormal parking space image includes: The parking space image is edge-processed according to the street parking space distribution map to obtain a standard parking space image. The vehicle integrity of the standard parking space image is judged according to the vehicle model. If the standard parking space image has a complete vehicle model, the corresponding vehicle is in a complete state and a safe parking space image is generated. Otherwise, the corresponding vehicle is in an incomplete state and an abnormal parking space image is generated.

5. The intelligent monitoring method for vehicle parking safety based on image recognition according to claim 4, characterized in that, The process of safe management of parking spaces includes: Obtain parking space image information data corresponding to abnormal parking space images, obtain contact information based on parking space image information data, and then send the license plate number and parking space code to the vehicle owner terminal through the early warning chain based on the contact information, and send the vehicle's standard processing time deadline for early warning. Based on the deadline for vehicle standard processing, street video images are acquired again, and then the parking space images corresponding to the abnormal parking space images are obtained. The integrity of the abnormal parking space images is checked again. If it is complete, a safe parking space image is generated, and the corresponding parking space image node is removed. If it is incomplete, the parking space image information data is sent to the management terminal through the early warning chain. Upon receiving the corresponding parking space image information data, the management terminal obtains the vehicle corresponding to the license plate number based on the parking space code and issues a penalty warning to the vehicle. If no vehicle model exists in the abnormal parking space image, an empty parking space image is generated, and the corresponding parking space image node is removed from the real-time parking space data network and updated.

6. The intelligent monitoring method for vehicle parking safety based on image recognition according to claim 3, characterized in that, The process of safety management for abnormally parked vehicles includes: All parking vehicle images corresponding to all parking vehicle image nodes in the real-time parking vehicle data network are marked as abnormal parking vehicles. The corresponding parking vehicle image information data is obtained from the parking vehicle central data node and sent to the vehicle owner's mobile terminal through the early warning chain according to the contact information. The deadline for standardized vehicle processing is also sent as an early warning. Similarly, based on the deadline for standardized vehicle processing, the image of the abnormally parked vehicle is retrieved again and judged. If the vehicle is not parked in accordance with regulations, the image information data of the parked vehicle is sent to the management terminal for penalty management through the early warning chain; if the vehicle is parked in accordance with regulations, the corresponding image node of the parked vehicle is removed and the real-time data network of the parked vehicle is updated.

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