Fake-licensed vehicle identification method, device, equipment and medium

Abstract

The invention discloses a fake-licensed vehicle identification method and device, equipment and a medium. The method comprises the following steps: acquiring a driving route of a target vehicle in a preset time period, and determining the driving time accessibility of the target vehicle between any two camera points according to the acquisition time of the two camera points in the driving route and the positions in a road network map. And for a road network path between any two camera points in the road network map, determining the space accessibility of the target vehicle running between the two camera points according to a second camera in the path. And performing space-time analysis based on the time accessibility and the space accessibility of the target vehicle among the camera points to determine whether the vehicle is a fake-licensed vehicle. According to the process, the driving track of the target vehicle among the camera points in the driving route is subjected to time and space dimension reachability analysis, and whether the vehicle is the fake-licensed vehicle is judged according to the analysis result, so that the identification precision of the fake-licensed vehicle is improved.

Description

Technical Field

[0001] The present application relates to the field of traffic safety technology, and in particular to a method, device, equipment and medium for identifying fake license plate vehicles. Background Art

[0002] A fake license plate vehicle refers to a vehicle with a fake license plate number and a fake license plate number on the same model and color as the real vehicle. The operation of fake license plate vehicles poses a serious safety hazard to traffic safety. The core logic of the fake license plate vehicle identification algorithm in the industry currently relies mainly on the algorithm model to perform spatiotemporal identification and feature comparison of vehicles.

[0003] Although research has shown that the current accuracy of license plate recognition and feature recognition for front-end equipment can reach more than 95%, with the continuous expansion of the transportation network, the number of misidentified data in the millions of vehicle passing data per day can still reach more than six digits when integrated, and there are nearly 10,000 suspected duplicate license plate cases caused by space-time discrimination collisions every day, which brings a huge workload to the confirmation of suspected duplicate license plates. Summary of the invention

[0004] The embodiments of the present application provide a method, device, equipment and medium for identifying vehicles with fake license plates, which are used to improve the recognition accuracy of vehicles with fake license plates.

[0005] To achieve the above purpose, the technical solution of the embodiment of the present application is implemented as follows:

[0006] In a first aspect, an embodiment of the present application provides a method for identifying a vehicle with a fake license plate, the method comprising:

[0007] In response to the vehicle identification indication, a driving route of the target vehicle within a preset time period is obtained; wherein the driving route is composed of a plurality of camera points, each camera point corresponds to a unique first camera; any first camera is a bayonet camera that captures the target vehicle within the preset time period;

[0008] Determine the time accessibility of the target vehicle traveling between any two camera points in the driving route according to the acquisition time and the position in the road network map of any two camera points in the driving route; wherein the acquisition time of any camera point is the time when the first camera corresponding to the camera point acquires the target vehicle;

[0009] For a road network path between any two camera points in a road network map, determine the spatial accessibility of a target vehicle traveling between the two camera points according to a second camera in the road network path; wherein the second camera is a bayonet camera that has not captured the target vehicle within the preset time period;

[0010] Whether the target vehicle is a fake license plate vehicle is determined based on the temporal accessibility and spatial accessibility of the target vehicle between the camera points.

[0011] In some possible embodiments, determining the time accessibility of the target vehicle traveling between any two camera points in the driving route according to the acquisition time and the position in the road network map of the two camera points includes:

[0012] For any two camera points, determine the average speed of the target vehicle traveling between the two camera points according to the acquisition time of the two camera points and the positions in the road map;

[0013] If the average vehicle speed is greater than the vehicle speed threshold, determining the temporal reachability of the target vehicle between the two camera points as temporally unreachable;

[0014] If the average vehicle speed is not greater than the vehicle speed threshold, the temporal reachability of the target vehicle between the two camera points is determined to be temporally reachable.

[0015] In some possible embodiments, determining the spatial accessibility of the target vehicle traveling between the two camera points according to the second camera in the road network path includes:

[0016] For any road network path, determine all traffic intersections included in the road network path;

[0017] If there are at least a specified number of consecutive problem checkpoints in each traffic intersection included in each road network path, the spatial accessibility of the target vehicle traveling between the two camera points is determined to be spatially inaccessible;

[0018] If the specified number of consecutive problem checkpoints do not exist, the spatial accessibility of the target vehicle traveling between the two camera points is determined to be spatially accessible; wherein the checkpoint camera at the problem checkpoint is the second camera.

[0019] In some possible embodiments, determining whether the target vehicle is a fake license plate vehicle based on the temporal accessibility and spatial accessibility of the target vehicle between camera points includes:

[0020] The camera points are grouped according to the spatial accessibility between the camera points to obtain camera subsets; wherein any camera subset includes at least one camera point; and the camera points in different camera subsets are different;

[0021] Combining the camera subsets in pairs to obtain a camera point set;

[0022] Whether the target vehicle is a fake-license vehicle is determined based on the spatial accessibility and temporal accessibility between the first camera point and the second camera point in the camera point set; wherein, the first camera point of any camera point set is the camera point with the latest acquisition time in the first subset in the camera point set, and the second camera point is the camera point with the earliest acquisition time in the second subset in the camera point set; the camera subset in which the camera point with the earliest acquisition time in any camera point set is located is the first subset of the camera point set, and the camera subset in the camera point set that is not the first subset is the second subset.

[0023] In some possible embodiments, the grouping of camera points according to the spatial reachability between the camera points to obtain the camera subset includes:

[0024] The following process is performed for each camera point in order of acquisition time from earliest to latest:

[0025] Determine whether a camera subset currently exists; if no camera subset exists, generate a camera subset containing the camera point;

[0026] If a camera subset exists, determining whether there is spatial reachability between the camera point and the first target point in each camera subset; wherein the first target point is the camera point with the latest sampling time in the camera subset;

[0027] If there is spatial reachability, the camera point is added to the camera subset where the second target point is located; wherein the second target point is the first target point that is spatially reachable from the camera point and has the latest sampling time; if there is no spatial inaccessibility, a camera subset containing the camera point is generated.

[0028] In some possible embodiments, determining whether the target vehicle is a fake-license vehicle based on spatial accessibility and temporal accessibility between the first camera point and the second camera point in the camera point set includes:

[0029] For any camera point set, if the spatial reachability between the first camera point and the second camera point in the camera point set is spatially unreachable, the camera point set is used as the first problem point set; and,

[0030] For any camera point set, if the time reachability between the first camera point and the second camera point in the camera point set is time unreachable, the camera point set is used as the second problem point set;

[0031] The number of the first problem point set and the number of the second problem point set in each camera point set are summed, and if the sum result is greater than a preset threshold, it is determined that the target vehicle is a fake license plate vehicle.

[0032] In some possible embodiments, before combining the camera subsets in pairs, the method further includes:

[0033] Determining that the number of the camera subset is not less than a first threshold;

[0034] After grouping the camera points according to the spatial accessibility between the camera points to obtain the camera subset, the method further includes:

[0035] If the number of the camera subset is not greater than the first threshold, it is determined that the target vehicle is not a fake-license vehicle.

[0036] In some possible embodiments, before determining whether the number of the camera subset is not less than a first threshold, the method further includes:

[0037] The camera subset whose number of camera points is less than a second threshold is eliminated.

[0038] In a second aspect, an embodiment of the present application provides a device for identifying a fake license plate vehicle, the device comprising:

[0039] A route acquisition unit is configured to execute, in response to the vehicle identification indication, to acquire a driving route of the target vehicle within a preset time period; wherein the driving route is composed of a plurality of camera points, each camera point corresponds to a unique first camera; any first camera is a bayonet camera that captures the target vehicle within the preset time period;

[0040] The time analysis unit is configured to determine the time accessibility of the target vehicle traveling between any two camera points in the driving route according to the acquisition time and the position in the road network map of any two camera points in the driving route; wherein the acquisition time of any camera point is the time when the first camera corresponding to the camera point acquires the target vehicle;

[0041] The spatial analysis unit is configured to determine the spatial accessibility of a target vehicle traveling between any two camera points according to a second camera in the road network path for a road network path between any two camera points in the road network map; wherein the second camera is a bayonet camera that has not captured the target vehicle within the preset time period;

[0042] The fake license plate identification unit is configured to determine whether the target vehicle is a fake license plate vehicle based on the temporal accessibility and spatial accessibility of the target vehicle between various camera points.

[0043] In some possible embodiments, the step of determining the time accessibility of the target vehicle traveling between any two camera points in the driving route according to the acquisition time and the position in the road network map of any two camera points in the driving route is performed, and the time analysis unit is configured as follows:

[0044] For any two camera points, determine the average speed of the target vehicle traveling between the two camera points according to the acquisition time of the two camera points and the positions in the road map;

[0045] If the average vehicle speed is greater than the vehicle speed threshold, determining the temporal reachability of the target vehicle between the two camera points as temporally unreachable;

[0046] If the average vehicle speed is not greater than the vehicle speed threshold, the temporal reachability of the target vehicle between the two camera points is determined to be temporally reachable.

[0047] In some possible embodiments, the determining of the spatial accessibility of the target vehicle traveling between the two camera points according to the second camera in the road network path is performed, and the spatial analysis unit is configured as follows:

[0048] For any road network path, determining the traffic intersections included in the road network path;

[0049] If there are at least a specified number of consecutive problem checkpoints in each traffic intersection included in each road network path, the spatial accessibility of the target vehicle traveling between the two camera points is determined to be spatially inaccessible;

[0050] If the specified number of consecutive problem checkpoints do not exist, the spatial accessibility of the target vehicle traveling between the two camera points is determined to be spatially accessible; wherein the checkpoint camera at the problem checkpoint is the second camera.

[0051] In some possible embodiments, to determine whether the target vehicle is a fake license plate vehicle based on the temporal accessibility and spatial accessibility of the target vehicle between the camera points, the fake license plate recognition unit is configured as follows:

[0052] The camera points are grouped according to the spatial accessibility between the camera points to obtain camera subsets; wherein any camera subset includes at least one camera point; and the camera points in different camera subsets are different;

[0053] Combining the camera subsets in pairs to obtain a camera point set;

[0054] Whether the target vehicle is a fake-license vehicle is determined based on the spatial accessibility and temporal accessibility between the first camera point and the second camera point in the camera point set; wherein, the first camera point of any camera point set is the camera point with the latest acquisition time in the first subset in the camera point set, and the second camera point is the camera point with the earliest acquisition time in the second subset in the camera point set; the camera subset in which the camera point with the earliest acquisition time in any camera point set is located is the first subset of the camera point set, and the camera subset in the camera point set that is not the first subset is the second subset.

[0055] In some possible embodiments, the grouping of camera points according to the spatial accessibility between the camera points is performed to obtain a camera subset, and the card identification unit is configured as follows:

[0056] The following process is performed for each camera point in order of acquisition time from earliest to latest:

[0057] Determine whether a camera subset currently exists; if no camera subset exists, generate a camera subset containing the camera point;

[0058] If a camera subset exists, determining whether there is spatial reachability between the camera point and the first target point in each camera subset; wherein the first target point is the camera point with the latest sampling time in the camera subset;

[0059] If there is spatial reachability, the camera point is added to the camera subset where the second target point is located; wherein the second target point is the first target point that is spatially reachable to the camera point and has the latest sampling time; if there is no spatial inaccessibility, a camera subset containing the camera point is generated.

[0060] In some possible embodiments, the determining whether the target vehicle is a fake license plate vehicle based on the spatial accessibility and temporal accessibility between the first camera point and the second camera point in the camera point set is performed, and the fake license plate recognition unit is configured as follows:

[0061] For any camera point set, if the spatial reachability between the first camera point and the second camera point in the camera point set is spatially unreachable, the camera point set is used as the first problem point set; and,

[0062] For any camera point set, if the time reachability between the first camera point and the second camera point in the camera point set is time unreachable, the camera point set is used as the second problem point set;

[0063] The number of the first problem point set and the number of the second problem point set in each camera point set are summed, and if the sum result is greater than a preset threshold, it is determined that the target vehicle is a fake license plate vehicle.

[0064] In some possible embodiments, before performing the step of combining the camera subsets in pairs, the counterfeit identification unit is further configured to:

[0065] Determining that the number of the camera subset is not less than a first threshold;

[0066] After grouping the camera points according to the spatial accessibility between the camera points to obtain the camera subset, the method further includes:

[0067] If the number of the camera subset is not greater than the first threshold, it is determined that the target vehicle is not a fake-license vehicle.

[0068] In some possible embodiments, before performing the step of determining whether the number of the camera subset is not less than a first threshold, the counterfeit identification unit is further configured to:

[0069] The camera subset whose number of camera points is less than a second threshold is eliminated.

[0070] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0071] A memory for storing program instructions;

[0072] The processor is used to call the program instructions stored in the memory, and execute the steps included in any one of the methods in the first aspect according to the obtained program instructions.

[0073] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes any one of the methods described in the first aspect.

[0074] In a fifth aspect, an embodiment of the present application provides a computer program product, comprising: a computer program code, when the computer program code is run on a computer, the computer executes any one of the methods described in the first aspect.

[0075] In an embodiment of the present application, the driving route of the target vehicle within a preset time period is obtained to determine the temporal accessibility of the target vehicle traveling between any two camera points in the driving route based on the acquisition time and the position of the two camera points in the road network map. In addition, for the road network path between any two camera points in the road network map, the spatial accessibility of the target vehicle traveling between the two camera points is determined based on the second camera located in the path. Finally, a spatiotemporal analysis is performed based on the temporal accessibility and spatial accessibility of the target vehicle between each camera point to determine whether the vehicle is a fake license plate vehicle. The above process improves the recognition accuracy of fake license plate vehicles by performing a time and space dimension accessibility analysis on the driving trajectory of the target vehicle between each camera point in the driving route, and determining whether the vehicle is a fake license plate vehicle based on the analysis results.

[0076] Other features and advantages of the present application will be described in the subsequent description, and partly become apparent from the description, or be understood by practicing the present disclosure. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 An overall flow chart of a method for identifying a fake license plate vehicle provided in an embodiment of the present application;

[0078] Figure 2A schematic diagram of a video frame image including a target vehicle provided in an embodiment of the present application;

[0079] Figure 3 A schematic diagram of the travel route of the target vehicle provided in the embodiment of the present application;

[0080] Figure 4 A schematic diagram of determining the time reachability between two points provided in an embodiment of the present application;

[0081] Figure 5 A schematic diagram of a road network path between two points provided in an embodiment of the present application;

[0082] Figure 6 A flowchart of generating a camera subset provided in an embodiment of the present application;

[0083] Figure 7 A schematic diagram of generating a camera subset provided in an embodiment of the present application;

[0084] Figure 8 Another schematic diagram of generating a camera subset provided in an embodiment of the present application;

[0085] Fig. 9 Another schematic diagram of generating a camera subset according to an embodiment of the present application;

[0086] Fig.10 A flowchart of generating a camera point set provided in an embodiment of the present application;

[0087] Fig.11 A schematic diagram of a camera point set provided in an embodiment of the present application;

[0088] Fig.12 A schematic diagram of the first and second camera points provided in an embodiment of the present application;

[0089] Fig.13 A schematic diagram of a problem point set provided in an embodiment of the present application;

[0090] Fig.14 A structural diagram of a fake license plate vehicle identification device 140 provided in an embodiment of the present application;

[0091] Fig.15 A schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0092] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is only a part of the embodiment of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be arbitrarily combined with each other. In addition, although the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in an order different from that here.

[0093] The terms "first" and "second" in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the term "comprising" and any of their variations are intended to cover non-exclusive protection. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices. "Multiple" in the present application can mean at least two, for example, two, three or more, and the embodiments of the present application are not limited.

[0094] As mentioned above, the core logic of the current fake license plate identification algorithm in the industry mainly relies on the algorithm model to perform time-space identification and feature comparison on vehicles. It calculates the time threshold required for a vehicle to pass through two locations by the longitude and latitude of the two locations and the speed of the vehicle, or calculates the time threshold required to pass through two locations by counting the time taken by all vehicles to pass through the two locations. If the time taken by a vehicle to pass through the two locations is much less than the above-mentioned time threshold, the vehicle is determined to be a fake license plate vehicle.

[0095] Although research shows that the accuracy of license plate recognition and feature recognition for front-end equipment can reach more than 95%, with the continuous expansion of the traffic network, the number of misidentified data in the millions of vehicles passing by every day can still reach more than six digits. It can be seen that how to improve the recognition accuracy of vehicles with fake license plates is an important task in the field of traffic safety.

[0096] To solve the above problems, the inventive concept of the present application is as follows: by obtaining the driving route of the target vehicle within a preset time period, the temporal accessibility of the target vehicle traveling between any two camera points in the driving route is determined according to the acquisition time and the position of the two camera points in the road network map. In addition, for the road network path between any two camera points in the road network map, the spatial accessibility of the target vehicle traveling between the two camera points is determined according to the second camera located in the path. Finally, a spatiotemporal analysis is performed based on the temporal accessibility and spatial accessibility of the target vehicle between each camera point to determine whether the vehicle is a fake license plate vehicle.

[0097] The above process analyzes the accessibility of the target vehicle's driving trajectory between camera points in the driving route in time and space dimensions, and determines whether the vehicle is a fake license plate vehicle based on the analysis results, thereby improving the recognition accuracy of fake license plate vehicles.

[0098] Specific as Figure 1 As shown, Figure 1 The overall process of a method for identifying a fake license plate vehicle provided in an embodiment of the present application is shown, which specifically includes:

[0099] Step 101: In response to a vehicle identification indication, a driving route of a target vehicle within a preset time period is obtained; wherein the driving route is composed of a plurality of camera points, each camera point corresponds to a unique first camera; any first camera is a bayonet camera that captures the target vehicle within the preset time period;

[0100] In the embodiment of the present application, a designated area (e.g., a city, a district, etc.) can be selected in the traffic network, and the video images captured by each bayonet camera in the designated area within a preset time period can be obtained. Each vehicle in the video image of any bayonet camera is then used as a target vehicle. A specific feature (such as vehicle style, vehicle color) or a designated vehicle can also be used as a target vehicle according to the scheduling needs of relevant personnel. The present application does not limit the source of the target vehicle.

[0101] Next, Figure 2 As shown, after the target vehicle is selected through the above process, the video images of each bayonet camera can be feature recognized through a traditional recognition algorithm, and the video frame image containing the target vehicle is selected, and the acquisition time of the video frame image is recorded. In this way, which bayonet cameras captured the target vehicle within the preset time period and the corresponding shooting time are obtained. The bayonet camera that captured the target vehicle within the preset time period is the first camera in step 101.

[0102] The camera points corresponding to the first cameras are constructed based on the latitude and longitude information of each first camera in the road network map. Each camera point is used to indicate the geographical location of the corresponding first camera and the acquisition time of the video frame image of the target vehicle acquired by the corresponding first camera. By analyzing the driving direction of the target vehicle in the video image and the acquisition time of each camera point within the preset time period, the Figure 3 The driving route of the target vehicle is shown.

[0103] Step 102: Determine the time accessibility of the target vehicle traveling between any two camera points in the driving route according to the acquisition time of the two camera points and the positions in the road network map; wherein the acquisition time of any camera point is the time when the first camera corresponding to the camera point acquires the target vehicle;

[0104] It should be noted that the time accessibility appearing in step 102 and the space accessibility appearing in the subsequent step 103 are both technical terms in the time-space discrimination task. Time accessibility and space accessibility are used to characterize the problem of time-space jumps when a vehicle travels between two points, which means that the vehicle cannot reach the other point from any one of the two points within the actual driving time.

[0105] After the target vehicle's driving route is obtained through the aforementioned step 101, for any two camera points in the driving route, the average speed of the target vehicle traveling between the two camera points is determined according to the acquisition time and the positions of the two camera points in the road map.

[0106] If the average vehicle speed is greater than the speed threshold, the time reachability of the target vehicle between the two camera points is determined to be time inaccessible; if the average vehicle speed is not greater than the speed threshold, the time reachability of the target vehicle between the two camera points is determined to be time reachable.

[0107] Specific as Figure 4 As shown, Figure 4 The driving route shown includes X1~X 10 , a total of 10 camera points. The smaller the serial number of each camera point, the earlier the collection time. Take camera points X1 and X5 as any two of the above camera points for example to perform time accessibility analysis. The collection time of camera point X1 is 12:05, and the collection time of camera point X5 is 13:05, that is, the time difference between camera point X1 and camera point X5 is 1 hour. Through the road network map, it is determined that the road network distance between camera point X1 and camera point X5 corresponding to the first camera is 160 kilometers, which means that the average speed of the target vehicle from camera point X1 to X5 is 160 kilometers per hour. It is greater than the speed threshold of 80, so it means that the time accessibility of the target vehicle between the two camera points is time inaccessible, that is, the vehicle theoretically cannot travel from camera point X1 to camera point X5 within one hour, and there may be suspicion of license plate duplication.

[0108] Correspondingly, if the average vehicle speed is not greater than the speed threshold, it means that the time accessibility of the target vehicle between the two camera points is time-accessible, which means that from the time dimension, the target vehicle can travel from camera point X1 to camera point X5 within one hour. Through the above process, the time accessibility between any two camera points in the driving route can be obtained.

[0109] Step 103: for a road network path between any two camera points in the road network map, determine the spatial accessibility of the target vehicle traveling between the two camera points according to a second camera in the road network path; wherein the second camera is a bayonet camera that has not captured the target vehicle within the preset time period;

[0110] During implementation, a road network path between any two camera points is selected in advance from the road network map. For any road network path, all traffic intersections included in the road network path are determined.

[0111] If there are at least a specified number of consecutive problem checkpoints in each traffic intersection included in each road network path, the spatial accessibility of the target vehicle traveling between the two camera points is determined to be spatially inaccessible; if there are no specified number of consecutive problem checkpoints, the spatial accessibility of the target vehicle traveling between the two camera points is determined to be spatially reachable; wherein, the checkpoint camera at the problem checkpoint is the second camera.

[0112] To facilitate understanding of the above process, Figure 4 The camera points X1 and X5 in the figure are taken as examples to illustrate. Figure 5 As shown. During implementation, all the road network paths 1 to 3 that can be driven from camera point X1 to camera point X5 are determined in advance from the road network map. The current traffic network is complex and has many intersections. There are cases where multiple paths partially overlap. For example Figure 5 The network path 1 and the network path 2 shown in the figure share the AB segment. The network path 1 and the network path 3 share the AE segment. In the embodiment of the present application, if each traffic intersection included in each network path has at least a specified number of problem checkpoints, the spatial accessibility between the two camera points is determined to be spatially inaccessible.

[0113] Next, Figure 5 Take the road network path 1 shown in the figure as an example. Since the road network path 1 includes a total of 5 traffic intersections A to E, if the checkpoint cameras at 3 consecutive intersections among the 5 intersections A to E are the second cameras that have not captured the target vehicle within the preset time period, it means that the target vehicle theoretically cannot travel from camera point X1 to camera point X5 through the road network path 1.

[0114] However, considering that the target vehicle may not travel along the road network path 1 during the actual driving process, the spatial accessibility between camera points X1 and X5 can only be explained as spatially unreachable when there are three consecutive traffic intersections where the target vehicle is not photographed in each road network path 1 to 3 from camera point X1 to camera point X5. On the contrary, if there are no three consecutive traffic intersections where the target vehicle is not photographed in any road network path, it means that the spatial accessibility between camera point X1 and camera point X5 is spatially reachable. The above process can determine the spatial accessibility between any two camera points in the driving route of the target vehicle.

[0115] Step 104: Determine whether the target vehicle is a fake license plate vehicle based on the temporal accessibility and spatial accessibility of the target vehicle between the camera points.

[0116] During implementation, the camera points are grouped in advance according to the spatial accessibility between the camera points to obtain camera subsets; wherein any camera subset includes at least one camera point; and the camera points in different camera subsets are different. Figure 6 As shown, when the camera groups are grouped according to the spatial accessibility between the camera points in the embodiment of the present application, the following process is performed on each camera point in order from early to late according to the corresponding acquisition time of each camera point:

[0117] Step 601: Determine whether a camera subset currently exists;

[0118] Step 602: If no camera subset exists, generate a camera subset including the current camera point;

[0119] Step 603: If a camera subset exists, determine whether there is a first target point that is spatially reachable from the current camera point; wherein the camera point with the latest sampling time in any camera subset is the first target point;

[0120] Step 604: If it exists, add the camera point to the camera subset where the second target point is located; wherein the second target point is the first target point that is spatially reachable from the camera point and has the latest sampling time; otherwise, return to the above step 602 to generate a camera subset containing the camera point.

[0121] To facilitate understanding of the above process, Figure 4 The camera points X1 to X 10 Take this as an example to illustrate. Figure 7 When implemented, it is determined in advance in step 601 whether there is a camera subset currently. Since the camera point X1 is the first camera point, there must be no camera subset currently. Next, step 602 is executed to generate a camera subset {X1} including the camera point X1.

[0122] Thus, the processing of camera point X1 is completed, and camera point X2 is substituted into step 601. Since there is currently a camera subset {X1}, step 603 is executed to determine whether there is spatial reachability between camera point X2 and the first target point with the latest acquisition time in camera subset {X1} (since there is only one camera point in camera subset {X1}, the camera point with the latest acquisition time is camera point X1).

[0123] Assuming that the spatial accessibility of camera point X1 and camera point X2 is spatially reachable, execute step 604 to add camera point X2 to the camera subset where the second target point is located. The second target point is the first target point with the latest sampling time. Since there is only one camera subset {X1} at present, the first target point and the second target point are both camera point X1, thereby obtaining the camera subset {X1, X2}. Assuming that the spatial accessibility of camera point X1 and camera point X2 is spatially unreachable, return to step 602 to generate a camera subset {X2} containing camera point X2. At this time, the camera subsets include {X1} and {X2}.

[0124] Next, Figure 8 As shown, it is assumed that after the camera points X1 to X9 are grouped through the above steps 601 to 604, the camera subsets {X1, X2, X3}, {X4, X5, X6}, {X7, X8}, {X9} are obtained. 10 When processing, first jump to step 603 through the determination of step 601 to determine the camera point X 10 Whether there is spatial reachability between the first target point (i.e., X3, X6, X8, and X9) with the latest acquisition time in each camera subset.

[0125] Assume the camera point X 10 The first target points (i.e., X3, X6, X8, and X9) are all spatially unreachable, and the process returns to step 602 to generate a region containing the camera point X. 10 The camera subset {X 10}, thereby determining the five camera subsets {X1, X2, X3}, {X4, X5, X6}, {X7, X8}, {X9} and {X10} obtained after the camera points X1 to X10 are grouped.

[0126] Another example Fig. 9 As shown, assuming that the camera point X 10 Part of the space in each first target point is reachable, and part of the space is not reachable. For example, if it is reachable with X3 and X8, then execute step 604 and move the camera point X 10 Add to the camera subset where the second target point is located. Since the camera point with the latest acquisition time among X3 and X8 is X8, the camera point X 10Add to the camera subset {X7, X8} where X8 is located, thereby determining the camera points X1 to X 10 The four camera subsets obtained after grouping are {X1, X2, X3}, {X4, X5, X6}, {X7, X8, X 10} and {X9}.

[0127] Through the above process, after grouping the camera points based on their spatial accessibility to obtain corresponding camera subsets, the camera subsets whose number of camera points is less than the second threshold 3 are eliminated. Fig.10 As shown, the aforementioned camera subset {X1, X2, X3}, {X4, X5, X6}, {X7, X8, X 10} and {X9} as examples, that is, the camera subset {X9} whose number of camera points is less than 3 is eliminated.

[0128] Then, it is determined whether the number of camera subsets is not less than a first threshold value 2. Specifically, if the number of camera subsets after elimination is less than 2 groups, it is confirmed that the target vehicle is not a fake license plate vehicle.

[0129] If there are not less than 2 groups, the camera subsets are combined in pairs to obtain the camera point set. 10} and {X9} as examples, after removing the camera subset {X9} with less than 3 camera points, the remaining camera subsets {X1, X2, X3}, {X4, X5, X6}, {X7, X8, X9} 10} is greater than the first threshold 2. Fig.11 As shown, the camera subsets are combined in pairs to obtain camera point set 1: [{X1, X2, X3}, {X4, X5, X6}], camera point set 2: [{X1, X2, X3}, {X7, X8, X9}] 10}] and camera point set 3: [{X4, X5, X6}, {X7, X8, X 10}].

[0130] Next, whether the target vehicle is a fake-license vehicle is determined based on the spatial reachability and temporal reachability between the first camera point and the second camera point in the camera point set; wherein, the first camera point of any camera point set is the camera point with the latest acquisition time in the first subset of the camera point set, and the second camera point is the camera point with the earliest acquisition time in the second subset of the camera point set; the camera subset where the camera point with the earliest acquisition time in any camera point set is located is the first subset of the camera point set, and the camera subset in the camera point set that is not the first subset is the second subset.

[0131] During implementation, for any camera point set, if the spatial reachability between the first camera point and the second camera point in the camera point set is spatially unreachable, the camera point set is used as the first problem point set. If the temporal reachability between the first camera point and the second camera point in the camera point set is temporally unreachable, the camera point set is used as the second problem point set.

[0132] By summing the numbers of the first problem point set and the second problem point set in each camera point set, if the sum result is greater than a preset threshold, it is determined that the target vehicle is a fake license plate vehicle.

[0133] Next, we take the camera point set 1 [{X1, X2, X3}, {X4, X5, X6}] obtained above as an example. Fig.12 As shown. From the camera point set 1 included in each (X1, X2, X3, X4, X5, X6), determine the camera point X1 with the earliest acquisition time, and use the camera subset {X1, X2, X3} where X1 is located as the first subset of the camera point set 1, and use {X4, X5, X6} as the second subset. Then, the camera point X3 with the latest acquisition time in the first subset {X1, X2, X3} is used as the first camera point in the camera point set 1, and the camera point X4 with the earliest acquisition time in the second subset {X4, X5, X6} is used as the second camera point in the camera point set 1.

[0134] Furthermore, for each camera point set, the temporal reachability and spatial reachability between the first camera point and the second camera point in the camera point set are determined. Fig.13 As shown, taking the aforementioned camera point sets 1 to 3 as an example, it is assumed that the first camera point and the second camera point in camera point set 1 are reachable in time but not in space. The first camera point and the second camera point in camera point set 2 are not reachable in time but are reachable in space. The first camera point and the second camera point in camera point set 3 are not reachable in time and space. This means that camera point set 1 is the first problem point set that is not reachable in space, camera point set 2 is the first problem point set that is not reachable in time, and camera point set 3 is not reachable in both time and space, that is, camera point set 3 is both the first problem point set and the second problem point set.

[0135] Finally, after the numbers of the first and second problem point sets in camera point sets 1 to 3 are both 2 through the above process, the number of problem point sets is summed up to obtain the total number of problem point sets in camera point sets 1 to 3 is 4. Since it is not greater than the preset threshold value 5, it means that the target vehicle is not a fake license plate vehicle. On the contrary, if it is greater than the preset threshold value 5, it means that the target vehicle is a fake license plate vehicle.

[0136] The above process analyzes the accessibility of the target vehicle's driving trajectory between camera points in the driving route in time and space dimensions, and determines whether the vehicle is a fake license plate vehicle based on the analysis results, thereby improving the recognition accuracy of fake license plate vehicles.

[0137] Based on the same inventive concept, the present application embodiment also provides a fake license plate vehicle identification device 140, specifically, Fig.14 As shown, specifically including:

[0138] The route acquisition unit 141 is configured to execute, in response to the vehicle identification indication, acquiring the driving route of the target vehicle within a preset time period; wherein the driving route is composed of a plurality of camera points, each camera point corresponds to a unique first camera; any first camera is a bayonet camera that captures the target vehicle within the preset time period;

[0139] The time analysis unit 142 is configured to determine the time accessibility of the target vehicle traveling between any two camera points in the driving route according to the acquisition time of the two camera points and the positions in the road network map; wherein the acquisition time of any camera point is the time when the first camera corresponding to the camera point acquires the target vehicle;

[0140] The spatial analysis unit 143 is configured to perform, for a road network path between any two camera points in the road network map, determining the spatial accessibility of the target vehicle traveling between the two camera points according to a second camera in the road network path; wherein the second camera is a bayonet camera that has not captured the target vehicle within the preset time period;

[0141] The fake license plate identification unit 144 is configured to determine whether the target vehicle is a fake license plate vehicle based on the temporal accessibility and spatial accessibility of the target vehicle between various camera points.

[0142] In some possible embodiments, the step of determining the time accessibility of the target vehicle traveling between any two camera points in the driving route according to the acquisition time and the position in the road network map of any two camera points in the driving route is performed, and the time analysis unit is configured as follows:

[0143] For any two camera points, determine the average speed of the target vehicle traveling between the two camera points according to the acquisition time of the two camera points and the positions in the road map;

[0144] If the average vehicle speed is greater than the vehicle speed threshold, determining the temporal reachability of the target vehicle between the two camera points as temporally unreachable;

[0145] If the average vehicle speed is not greater than the vehicle speed threshold, the temporal reachability of the target vehicle between the two camera points is determined to be temporally reachable.

[0146] In some possible embodiments, the determining of the spatial accessibility of the target vehicle traveling between the two camera points according to the second camera in the road network path is performed, and the spatial analysis unit is configured as follows:

[0147] For any road network path, determining the traffic intersections included in the road network path;

[0148] If there are at least a specified number of consecutive problem checkpoints in each traffic intersection included in each road network path, the spatial accessibility of the target vehicle traveling between the two camera points is determined to be spatially inaccessible;

[0149] If the specified number of consecutive problem checkpoints do not exist, the spatial accessibility of the target vehicle traveling between the two camera points is determined to be spatially accessible; wherein the checkpoint camera at the problem checkpoint is the second camera.

[0150] In some possible embodiments, to determine whether the target vehicle is a fake license plate vehicle based on the temporal accessibility and spatial accessibility of the target vehicle between the camera points, the fake license plate recognition unit is configured as follows:

[0151] The camera points are grouped according to the spatial accessibility between the camera points to obtain camera subsets; wherein any camera subset includes at least one camera point; and the camera points in different camera subsets are different;

[0152] Combining the camera subsets in pairs to obtain a camera point set;

[0153] Whether the target vehicle is a fake-license vehicle is determined based on the spatial accessibility and temporal accessibility between the first camera point and the second camera point in the camera point set; wherein, the first camera point of any camera point set is the camera point with the latest acquisition time in the first subset in the camera point set, and the second camera point is the camera point with the earliest acquisition time in the second subset in the camera point set; the camera subset in which the camera point with the earliest acquisition time in any camera point set is located is the first subset of the camera point set, and the camera subset in the camera point set that is not the first subset is the second subset.

[0154] In some possible embodiments, the grouping of camera points according to the spatial accessibility between the camera points is performed to obtain a camera subset, and the card identification unit is configured as follows:

[0155] The following process is performed for each camera point in order of acquisition time from earliest to latest:

[0156] Determine whether a camera subset currently exists; if no camera subset exists, generate a camera subset containing the camera point;

[0157] If a camera subset exists, determining whether there is spatial reachability between the camera point and the first target point in each camera subset; wherein the first target point is the camera point with the latest sampling time in the camera subset;

[0158] If there is spatial reachability, the camera point is added to the camera subset where the second target point is located; wherein the second target point is the first target point that is spatially reachable to the camera point and has the latest sampling time; if there is no spatial inaccessibility, a camera subset containing the camera point is generated.

[0159] In some possible embodiments, the determining whether the target vehicle is a fake license plate vehicle based on the spatial accessibility and temporal accessibility between the first camera point and the second camera point in the camera point set is performed, and the fake license plate recognition unit is configured as follows:

[0160] For any camera point set, if the spatial reachability between the first camera point and the second camera point in the camera point set is spatially unreachable, the camera point set is used as the first problem point set; and,

[0161] For any camera point set, if the time reachability between the first camera point and the second camera point in the camera point set is time unreachable, the camera point set is used as the second problem point set;

[0162] The number of the first problem point set and the number of the second problem point set in each camera point set are summed, and if the sum result is greater than a preset threshold, it is determined that the target vehicle is a fake license plate vehicle.

[0163] In some possible embodiments, before performing the step of combining the camera subsets in pairs, the counterfeit identification unit is further configured to:

[0164] Determining that the number of the camera subset is not less than a first threshold;

[0165] After grouping the camera points according to the spatial accessibility between the camera points to obtain the camera subset, the method further includes:

[0166] If the number of the camera subset is not greater than the first threshold, it is determined that the target vehicle is not a fake-license vehicle.

[0167] In some possible embodiments, before performing the step of determining whether the number of the camera subset is not less than a first threshold, the counterfeit identification unit is further configured to:

[0168] The camera subset whose number of camera points is less than a second threshold is eliminated.

[0169] Refer to the following Fig.15 The electronic device 130 according to this embodiment of the present application is described. Fig.15 The electronic device 130 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0170] like Fig.15As shown, the electronic device 130 is in the form of a general electronic device. The components of the electronic device 130 may include but are not limited to: at least one processor 131, at least one memory 132, and a bus 133 connecting different system components (including the memory 132 and the processor 131).

[0171] Bus 133 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a processor, or a local bus using any of a variety of bus architectures.

[0172] The memory 132 may include a readable medium in the form of a volatile memory, such as a random access memory (RAM) 1321 and / or a cache memory 1322 , and may further include a read-only memory (ROM) 1323 .

[0173] The memory 132 may also include a program / utility 1325 having a set (at least one) of program modules 1324, such program modules 1324 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0174] The electronic device 130 may also communicate with one or more external devices 134 (e.g., keyboards, pointing devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 130, and / or communicate with any device that enables the electronic device 130 to communicate with one or more other electronic devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 135. Furthermore, the electronic device 130 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 136. As shown, the network adapter 136 communicates with other modules for the electronic device 130 via a bus 133. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 130, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0175] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 132 including instructions, and the instructions can be executed by the processor 131 of the above device to complete the above method. Alternatively, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0176] In an exemplary embodiment, a computer program product is also provided, including a computer program / instruction, which, when executed by the processor 131, implements any method in the method for identifying a fake license plate vehicle provided in the present application.

[0177] In an exemplary embodiment, various aspects of a method for identifying a cloned vehicle provided by the present application may also be implemented in the form of a program product, which includes a program code. When the program product is run on a computer device, the program code is used to enable the computer device to execute the steps of a method for identifying a cloned vehicle according to various exemplary embodiments of the present application described above in this specification.

[0178] The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0179] The program product for counterfeit vehicle identification of the embodiment of the present application may adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on an electronic device. However, the program product of the present application is not limited thereto, and in this document, a readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, apparatus, or device.

[0180] A readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, wherein readable program code is carried. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium other than a readable storage medium, which may transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0181] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0182] The program code for performing the operation of the present application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and also conventional procedural programming languages ​​such as language or similar programming languages. The program code can be executed entirely on the user electronic device, partially on the user device, as an independent software package, partially on the user electronic device and partially on the remote electronic device, or completely on the remote electronic device or server. In the case of a remote electronic device, the remote electronic device can be connected to the user electronic device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external electronic device (for example, using an Internet service provider to connect through the Internet).

[0183] It should be noted that, although several units or subunits of the device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided into multiple units to be embodied.

[0184] In addition, although the operations of the method of the present application are described in a specific order in the drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0185] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0186] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable image scaling device to produce a machine, so that the instructions executed by the processor of the computer or other programmable image scaling device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0187] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable image scaling device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, the instruction device being implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0188] These computer program instructions may also be loaded onto a computer or other programmable image scaling device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0189] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0190] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for identifying fake license plate vehicles, characterized in that: The method comprises: In response to the vehicle identification indication, a driving route of the target vehicle within a preset time period is obtained; wherein the driving route is composed of a plurality of camera points, each camera point corresponds to a unique first camera; any first camera is a bayonet camera that captures the target vehicle within the preset time period; Determine the time accessibility of the target vehicle traveling between any two camera points in the driving route according to the acquisition time and the position in the road network map of any two camera points in the driving route; wherein the acquisition time of any camera point is the time when the first camera corresponding to the camera point acquires the target vehicle; For a road network path between any two camera points in a road network map, determine the spatial accessibility of a target vehicle traveling between the two camera points according to a second camera in the road network path; wherein the second camera is a bayonet camera that has not captured the target vehicle within the preset time period; Whether the target vehicle is a fake license plate vehicle is determined based on the temporal accessibility and spatial accessibility of the target vehicle between the camera points.

2. The method according to claim 1, characterized in that The method of determining the time accessibility of the target vehicle traveling between any two camera points in the driving route according to the acquisition time and the position in the road network map of the two camera points comprises: For any two camera points, determine the average speed of the target vehicle traveling between the two camera points according to the acquisition time of the two camera points and the positions in the road map; If the average vehicle speed is greater than the vehicle speed threshold, determining the temporal reachability of the target vehicle between the two camera points as temporally unreachable; If the average vehicle speed is not greater than the vehicle speed threshold, the temporal reachability of the target vehicle between the two camera points is determined to be temporally reachable.

3. The method according to claim 1, characterized in that The determining, based on the second camera in the road network path, the spatial accessibility of the target vehicle traveling between the two camera points comprises: For any road network path, determining the traffic intersections included in the road network path; If there are at least a specified number of consecutive problem checkpoints in each traffic intersection included in each road network path, the spatial accessibility of the target vehicle traveling between the two camera points is determined to be spatially inaccessible; If the specified number of consecutive problem checkpoints do not exist, the spatial accessibility of the target vehicle traveling between the two camera points is determined to be spatially accessible; wherein the checkpoint camera at the problem checkpoint is the second camera.

4. The method according to claim 1, characterized in that: The determining whether the target vehicle is a fake license plate vehicle based on the temporal accessibility and spatial accessibility of the target vehicle between the camera points includes: The camera points are grouped according to the spatial accessibility between the camera points to obtain camera subsets; wherein any camera subset includes at least one camera point; and the camera points in different camera subsets are different; Combining the camera subsets in pairs to obtain a camera point set; Whether the target vehicle is a fake-license vehicle is determined based on the spatial accessibility and temporal accessibility between the first camera point and the second camera point in the camera point set; wherein, the first camera point of any camera point set is the camera point with the latest acquisition time in the first subset in the camera point set, and the second camera point is the camera point with the earliest acquisition time in the second subset in the camera point set; the camera subset in which the camera point with the earliest acquisition time in any camera point set is located is the first subset of the camera point set, and the camera subset in the camera point set that is not the first subset is the second subset.

5. The method according to claim 4, characterized in that The camera points are grouped according to the spatial accessibility between the camera points to obtain a camera subset, including: The following process is performed for each camera point in order of acquisition time from earliest to latest: Determine whether a camera subset currently exists; if no camera subset exists, generate a camera subset containing the camera point; If a camera subset exists, determining whether there is spatial reachability between the camera point and the first target point in each camera subset; wherein the first target point is the camera point with the latest sampling time in the camera subset; If there is spatial reachability, the camera point is added to the camera subset where the second target point is located; wherein the second target point is the first target point that is spatially reachable to the camera point and has the latest sampling time; if there is no spatial inaccessibility, a camera subset containing the camera point is generated.

6. The method according to claim 4, characterized in that The determining whether the target vehicle is a fake license plate vehicle based on the spatial accessibility and temporal accessibility between the first camera point and the second camera point in the camera point set includes: For any camera point set, if the spatial reachability between the first camera point and the second camera point in the camera point set is spatially unreachable, the camera point set is used as the first problem point set; and, For any camera point set, if the time reachability between the first camera point and the second camera point in the camera point set is time unreachable, the camera point set is used as the second problem point set; The number of the first problem point set and the number of the second problem point set in each camera point set are summed, and if the sum result is greater than a preset threshold, it is determined that the target vehicle is a fake license plate vehicle.

7. The method according to any one of claims 4 to 6, characterized in that: Before combining the camera subsets in pairs, the method further includes: Determining that the number of the camera subset is not less than a first threshold; After grouping the camera points according to the spatial accessibility between the camera points to obtain the camera subset, the method further includes: If the number of the camera subset is not greater than the first threshold, it is determined that the target vehicle is not a fake-license vehicle.

8. The method according to claim 7, characterized in that Before determining whether the number of the camera subset is not less than a first threshold, the method further includes: The camera subset whose number of camera points is less than a second threshold is eliminated.

9. A device for identifying fake license plate vehicles, characterized in that: The device comprises: A route acquisition unit is configured to execute, in response to the vehicle identification indication, to acquire a driving route of the target vehicle within a preset time period; wherein the driving route is composed of a plurality of camera points, each camera point corresponds to a unique first camera; any first camera is a bayonet camera that captures the target vehicle within the preset time period; The time analysis unit is configured to determine the time accessibility of the target vehicle traveling between any two camera points in the driving route according to the acquisition time and the position in the road network map of any two camera points in the driving route; wherein the acquisition time of any camera point is the time when the first camera corresponding to the camera point acquires the target vehicle; The spatial analysis unit is configured to determine the spatial accessibility of a target vehicle traveling between any two camera points according to a second camera in the road network path for a road network path between any two camera points in the road network map; wherein the second camera is a bayonet camera that has not captured the target vehicle within the preset time period; The fake license plate identification unit is configured to determine whether the target vehicle is a fake license plate vehicle based on the temporal accessibility and spatial accessibility of the target vehicle between various camera points.

10. An electronic device, characterized in that: include: A memory for storing program instructions; A processor is used to call the program instructions stored in the memory, and execute the steps included in any one of the methods of claims 1-8 according to the obtained program instructions.

Images