CN114141023A - Fake-licensed vehicle detection method, system, storage medium and terminal - Google Patents
Fake-licensed vehicle detection method, system, storage medium and terminal Download PDFInfo
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Abstract
The invention provides a fake-licensed vehicle detection method, a system, a storage medium and a terminal, wherein the method comprises the following steps: presetting a plurality of target detection points and acquiring detection information; acquiring the speed of a target vehicle according to the detection information of the target vehicle with the same license plate information at different target detection points; the method comprises the steps of performing primary judgment on a target vehicle, and judging the target vehicle as a suspected vehicle when the speed of the target vehicle is abnormal; performing secondary judgment on the target vehicle according to the primary judgment result of the target vehicle and the characteristic information of the target vehicle, and confirming whether the target vehicle is fake plate; the method takes the snapping photos of the checkpoints distributed all over the country as the data basis, judges the fake plate behavior by calculating the snapping vehicle speeds twice, and has the advantages of high real-time performance, complete data and high accuracy.
Description
Technical Field
The invention relates to the field of security and protection, in particular to a fake-licensed vehicle detection method, a fake-licensed vehicle detection system, a storage medium and a terminal.
Background
The fake-license vehicle is characterized in that fake-license plates with the same number and color are sleeved on other vehicles by referring to real license plates. The fake-licensed vehicle can disturb the control of public safety, make social unstable factors and also disturb the management order of the transportation market. For individual car owners, the fake-licensed cars can directly damage the legal rights and interests of real car owners, and after the legal cars are fake-licensed by other cars, unnecessary troubles and economic losses are brought to the real car owners in the aspects of vehicle traffic violation, accident handling and the like.
At present, aiming at the current situation that the fake-licensed vehicles are abused, an accurate detection means is lacked, on one hand, because the difficulty in obtaining the parking record data in private territories such as companies and communities is high, if the parking record data is used as a data base for detection, the detection purpose cannot be effectively finished; on the other hand, the existing detection mode has low precision, so that fake-licensed cars are easy to miss, or a large amount of invalid fake-licensed car data are easy to obtain, and the object relationship of fake-licensed cannot be further determined.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention provides a method, a system, a storage medium and a terminal for detecting a fake-licensed vehicle, so as to solve the above technical problems.
The fake-licensed vehicle detection method provided by the invention comprises the following steps:
presetting a plurality of target detection points, and acquiring detection information, wherein the detection information comprises position information, detection time information and target vehicle information of the target detection points, and the target vehicle information at least comprises license plate information and characteristic information;
calculating the speed of a target vehicle according to the detection information of the target vehicle with the same license plate information at different target detection points;
the target vehicle is judged once, and when the speed of the target vehicle is abnormal, the target vehicle is judged to be a suspected vehicle;
and performing secondary judgment on the target vehicle according to the primary judgment result of the target vehicle and the characteristic information of the target vehicle, and confirming whether the target vehicle is fake plate.
In an embodiment of the present invention, the determining the target vehicle once includes: when the speed of the target vehicle exceeds a preset speed threshold value, judging the target vehicle to be a suspected vehicle, and giving an initial confidence coefficient;
the secondarily determining the target vehicle includes: and acquiring registration information of the target vehicle, matching the characteristic information of the target vehicle with the registration information, updating the initial confidence level according to a matching result, and confirming whether the target vehicle is fake plate or not according to the updated confidence level.
In an embodiment of the present invention, the registration information is classified in advance, and different confidence scores are set for each type of registration information, where the types of the registration information include a vehicle brand, a vehicle model, and a vehicle color;
and comparing the characteristic information with each type of registration information in sequence, increasing or decreasing the corresponding confidence score for the initial confidence according to the comparison result of each type of registration information, and stopping continuous comparison when the confidence reaches 100 percent.
In an embodiment of the present invention, after performing the second determination on the target vehicle, the method further includes:
classifying feature information in advance, and setting different confidence scores for each type of feature information, wherein the feature information comprises static identification information for representing static features of a vehicle, dynamic identification information for representing a vehicle state, and personnel identification information for representing personnel features in the vehicle;
and comparing the feature information acquired this time with the previous time in sequence, and increasing or decreasing the corresponding confidence score of the previous time according to the comparison result to acquire the updated confidence.
In an embodiment of the present invention, the target detection point is a bayonet, the detection information includes bayonet snapshot data, and the static identification information includes a vehicle body color, a vehicle type, and a vehicle brand; the dynamic identification information comprises a driving direction, a lane number, an annual inspection mark, a sunshade plate state and whether a placed object exists or not; the personnel identification information comprises the face characteristics of the driver and the state of the safety belt.
In an embodiment of the present invention, the obtaining the vehicle speed of the target vehicle according to the detection information of the target vehicle with the same license plate information at different target detection points includes:
when a target vehicle detecting the same license plate information passes through two target detection points at different time, acquiring the distance between the two target detection points;
acquiring a theoretical average speed of the target vehicle according to the detection time difference and the distance between the two target detection points;
and when the vehicle speed of the target vehicle exceeds a preset speed threshold value, determining that the target vehicle is a suspected vehicle.
In an embodiment of the present invention, when comparing the feature information, if the comparison results are the same, the confidence is reduced; if the comparison results are different, increasing the confidence coefficient; different weights are set according to different kinds of influences of the characteristic information, and confidence scores are set according to the weights.
The invention also provides a fake-licensed vehicle detection system, which comprises:
the system comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring detection information at a plurality of preset target detection points, the detection information comprises position information, detection time information and target vehicle information of the target detection points, and the target vehicle information at least comprises license plate information and characteristic information;
the data processing module is used for acquiring the speed of a target vehicle according to the detection information of the target vehicle with the same license plate information at different target detection points;
the primary judgment module is used for performing primary judgment on the target vehicle, and when the speed of the target vehicle is abnormal, the target vehicle is judged to be a suspected vehicle;
and the secondary judgment module is used for carrying out secondary judgment on the target vehicle according to the primary judgment result of the target vehicle and the characteristic information of the target vehicle and confirming whether the target vehicle is fake plate or not.
The invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of any one of the above.
The present invention also provides an electronic terminal, comprising: a processor and a memory;
the memory is adapted to store a computer program and the processor is adapted to execute the computer program stored by the memory to cause the terminal to perform the method as defined in any one of the above.
The invention has the beneficial effects that: the fake plate vehicle detection method, the fake plate vehicle detection system, the storage medium and the terminal take the snapshot pictures of the bayonets distributed all over the country as the data basis, judge the fake plate behavior by calculating the speed of the two snapshots, and have the advantages of high real-time performance, complete data and high accuracy.
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Fig. 1 is a schematic flow chart of a fake-licensed vehicle detection method in an embodiment of the invention.
Fig. 2 is a schematic structural diagram of a fake-licensed vehicle detection system in the embodiment of the invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the drawings only show the components related to the present invention rather than the number, shape and size of the components in practical implementation, and the type, amount and ratio of the components in practical implementation may be changed arbitrarily, and the layout of the components may be complicated.
In the following description, numerous details are set forth to provide a more thorough explanation of embodiments of the present invention, however, it will be apparent to one skilled in the art that embodiments of the present invention may be practiced without these specific details, and in other embodiments, well-known structures and devices are shown in block diagram form rather than in detail in order to avoid obscuring embodiments of the present invention.
As shown in fig. 1, the fake-licensed vehicle detection method in this embodiment is characterized by including:
s101, presetting a plurality of target detection points, and acquiring detection information, wherein the detection information comprises position information, detection time information and target vehicle information of the target detection points, and the target vehicle information at least comprises license plate information and characteristic information;
s102, calculating the speed of a target vehicle according to detection information of the target vehicle with the same license plate information at different target detection points;
s103, the target vehicle is judged once, and when the speed of the target vehicle is abnormal, the target vehicle is judged to be a suspected vehicle;
s104, secondary judgment is carried out on the target vehicle according to the primary judgment result of the target vehicle and the characteristic information of the target vehicle, and whether the target vehicle is fake plate or not is confirmed.
In step S101 of this embodiment, a plurality of target detection points are preset to obtain detection information, in this embodiment, the target detection points may be checkpoints, the original data may be snapshot data of each checkpoint, and as long as a vehicle travels normally on a road, the vehicle will be certainly captured by each checkpoint, and the data already exists in a system of a regulatory department conforming to relevant legal regulations, and can be easily obtained, thereby avoiding a problem that private territory parking record data such as companies and cells are not reported on a network and are difficult to obtain. The vehicle information (license plate, characteristic value and the like) is analyzed by applying a corresponding algorithm through the picture or video stream in the snapshot data push system through each bayonet, wherein any algorithm capable of realizing the functions in the prior art can be adopted through a specific algorithm for analyzing the vehicle information through the picture or video, and the detailed description is omitted.
In step S102 of this embodiment, the vehicle speed of the target vehicle is calculated according to the detection information of the target vehicle with the same license plate information at different target detection points. In this embodiment, in each time, only the vehicle speeds of two pieces of snapshot data are calculated, if the vehicle is abnormal, the vehicle is determined to be a suspected fake-licensed vehicle, and if the vehicle is abnormal for multiple times, the confidence is increased. The problem that the fake-licensed car is missed because a plurality of slower speeds possibly lower a certain faster abnormal speed when the average speed of a plurality of positions is calculated is solved.
In step S103 of this embodiment, the target vehicle is determined once, and when the vehicle speed of the target vehicle is abnormal, the target vehicle is determined to be a suspected vehicle; the making of the one-time determination of the target vehicle includes: when the vehicle speed of the target vehicle exceeds a preset speed threshold value, the target vehicle is judged to be a suspected vehicle, and initial confidence is given. Optionally, the information can be displayed in real time through a human-computer interaction interface, for example, when information of a certain set of license plate vehicles is displayed, each analysis record and details of each analysis record can be displayed at the same time, wherein the details include two snap photos and information such as a snap name, snap time, a vehicle brand and the like which are marked, geographical positions of the two snap photos are displayed in a map mode, and distances between the snaps are displayed visually in a line connection mode. And calculating the speed of the vehicle by analyzing the time of capturing the photos twice and the longitude and latitude of the capturing device, judging the vehicle as a suspected fake-licensed vehicle if the speed of the vehicle is greater than a certain threshold value, and giving an initial confidence coefficient.
In step S104 of the present embodiment, a secondary determination is performed on the target vehicle based on the primary determination result of the target vehicle and the feature information of the target vehicle, and it is confirmed whether the target vehicle is a fake plate. In the present embodiment, the feature information of the target vehicle captured twice is compared with the feature information of the registered vehicle, and the feature information of three vehicles is determined. The secondary determination in this embodiment includes: and acquiring registration information of the target vehicle, matching the characteristic information of the target vehicle with the registration information, updating the initial confidence level according to the matching result, and confirming whether the target vehicle is fake plate or not according to the updated confidence level. For example, the time of two snapshot pictures and the longitude and latitude of the snapshot device are analyzed to calculate the vehicle speed, if the vehicle speed is greater than a certain threshold value, the vehicle is judged to be a suspected fake-licensed vehicle, the initial confidence coefficient is given to be 50%, and when the vehicle speed is calculated to be abnormal subsequently, the confidence coefficient is increased by 10%. And then, by inquiring the registration information of the original real vehicle, comparing the vehicle characteristics (the color of the vehicle body, the brand of the vehicle, the model of the vehicle and the like) one by one, and properly increasing or decreasing the confidence level according to the comparison result.
In this embodiment, the registration information is classified in advance, different confidence scores are set for each type of registration information, the types of the registration information include a vehicle brand, a vehicle model and a vehicle color, the feature information and each type of registration information are sequentially compared, the initial confidence score is increased or decreased by a corresponding confidence score according to a comparison result of each type of registration information, the confidence is highest by 100%, and analysis is not continued after the initial confidence score is reached, so that consumption of large amount of calculation, storage and the like caused by abnormal data (such as large latitude and longitude deviation of equipment, inaccurate snapshot time and the like) is reduced.
In this embodiment, when comparing the feature information, the confidence may be reduced for the same feature information, and the confidence may be increased for different feature information, and different weights may be set according to the types of different feature information, for example, the weight is larger if the color and the brand of the vehicle are difficult to change, and the weight is smaller if the vehicle is not on the phone or is on the decoration.
In this embodiment, the feature information is classified in advance, and different confidence scores are set for each type of feature information, where the types of feature information include static identification information for representing static features of a vehicle, dynamic identification information for representing a vehicle state, and person identification information for representing features of persons in the vehicle; and comparing the feature information acquired this time with the previous time in sequence, and increasing or decreasing the corresponding confidence score for the confidence of the previous time according to the comparison result to acquire the updated confidence. The static identification information comprises the color of the vehicle body, the type of the vehicle, the brand of the vehicle and the like; the dynamic identification information comprises a driving direction, a lane number, an annual inspection mark, a sunshade plate state, whether a placed object exists or not and the like; the personnel identification information includes the face characteristics of the driver, the state of the safety belt and the like.
In this embodiment, according to the detection information of the target vehicle with the same license plate information at different target detection points, when the target vehicle with the same license plate information passes through two target detection points at different time, the distance between the two target detection points is acquired; acquiring a theoretical average speed of the target vehicle according to the detection time difference and the distance between the two target detection points; when the vehicle speed of the target vehicle exceeds a preset speed threshold value, the target vehicle is determined to be a suspected vehicle. For example, the longitude and latitude of the bayonets in the two data are taken out, the distance between the two points is calculated, then the theoretical average vehicle speed is calculated according to the time difference between the two snapshot times, a vehicle speed threshold (such as 250Km/h) of the suspected fake-licensed vehicle is set, the suspected fake-licensed vehicle is judged when the calculated vehicle speed is larger than the threshold, and an initial confidence coefficient (such as 50%) is given and stored in the database. If the same license plate snapshot data is pushed subsequently, the theoretical vehicle speed is continuously analyzed, and when the theoretical vehicle speed is larger than the threshold value, the confidence coefficient is increased, for example, increased by 10% because the license plate is once identified as a suspected fake-licensed vehicle. And comparing the characteristic information extracted from the two pieces of snapshot information with the registration information of the vehicle one by one. The feature information in this embodiment may include a body color, a vehicle type, a vehicle brand, a driving direction, a lane number, an annual inspection mark, a driver's face feature, whether the main driver calls, a main driver seat belt, a visor state, whether there is a furnishing, whether there is a hanging decoration, whether there is a tissue box, whether there is a vehicle inspection mark, a passenger seat belt, and the like. When the characteristic information is compared, the confidence coefficient is reduced for the same characteristic value, the confidence coefficient is increased if the characteristic information is different, different weights can be set according to different characteristic values, for example, the weight is larger if the color and the brand of the vehicle are difficult to change, and the weight is smaller if the color and the brand of the vehicle are easy to change, and after comparison, which vehicle is a fake-licensed vehicle can be further confirmed.
Correspondingly, as shown in fig. 2, the present embodiment further provides a fake-licensed vehicle detection system, including:
the system comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring detection information at a plurality of preset target detection points, the detection information comprises position information, detection time information and target vehicle information of the target detection points, and the target vehicle information at least comprises license plate information and characteristic information;
the data processing module is used for acquiring the speed of a target vehicle according to the detection information of the target vehicle with the same license plate information at different target detection points;
the primary judgment module is used for performing primary judgment on the target vehicle, and when the speed of the target vehicle is abnormal, the target vehicle is judged to be a suspected vehicle;
and the secondary judgment module is used for carrying out secondary judgment on the target vehicle according to the primary judgment result of the target vehicle and the characteristic information of the target vehicle and confirming whether the target vehicle is fake plate or not.
In this embodiment, still include interactive platform, can get into a certain set of license plate information details through interactive platform, show each time analysis record to and the details of each time analysis record, including two snap shots and the information such as the bayonet name of having identified the snap shot, the snap shot time, the vehicle brand, can also show the geographical position of two snap shots through the mode of map, show distance between the bayonet directly perceived through the mode of connecting, the user can carry out further affirmation to the analysis result on interactive platform, if the analysis result has the wrong judgement can the sign, collect user's operation result and can further optimize the logic of this system.
The fake-licensed vehicle detection system in the embodiment can execute corresponding operation through the fake-licensed vehicle detection method, on the basis of judging the fake-licensed vehicle based on the vehicle speed, calculate the vehicle speed of the twice snapshot data according to the license plate information by using the real-time snapshot data, and compare the vehicle speed with the vehicle registration information, so that a suspected fake-licensed vehicle is analyzed, the fake-licensed vehicle can be confirmed more effectively, more timely and more accurately, and the detection of the fake-licensed vehicle is completed. The system in this embodiment further includes an inquiry module that supports retrieval according to the license plate number and the time range, and may determine whether the suspected fake-licensed vehicle is a real fake-licensed vehicle based on a retrieval result.
The present embodiments also provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements any of the methods in the present embodiments.
The present embodiment further provides an electronic terminal, including: a processor and a memory;
the memory is used for storing computer programs, and the processor is used for executing the computer programs stored by the memory so as to enable the terminal to execute the method in the embodiment.
The computer-readable storage medium in the present embodiment can be understood by those skilled in the art as follows: all or part of the steps for implementing the above method embodiments may be performed by hardware associated with a computer program. The aforementioned computer program may be stored in a computer readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
The electronic terminal provided by the embodiment comprises a processor, a memory, a transceiver and a communication interface, wherein the memory and the communication interface are connected with the processor and the transceiver and are used for completing mutual communication, the memory is used for storing a computer program, the communication interface is used for carrying out communication, and the processor and the transceiver are used for operating the computer program so that the electronic terminal can execute the steps of the method.
In this embodiment, the Memory may include a Random Access Memory (RAM), and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In the above embodiments, unless otherwise specified, common objects are described by using "first", "second", etc. ordinal numbers to indicate that they refer to different instances of the same object, rather than by indicating that the objects being described must be in a given sequence, whether temporally, spatially, in ranking, or in any other manner. In the above-described embodiments, reference in the specification to "the embodiment," "an embodiment," "another embodiment," or "other embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least some embodiments, but not necessarily all embodiments. The various appearances of the phrase "the present embodiment," "one embodiment," or "another embodiment" are not necessarily all referring to the same embodiment.
In the embodiments described above, although the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art in light of the foregoing description. For example, other memory structures (e.g., dynamic ram (dram)) may use the discussed embodiments. The embodiments of the invention are intended to embrace all such alternatives, modifications and variances that fall within the broad scope of the appended claims.
The invention is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The foregoing embodiments are merely illustrative of the principles of the present invention and its efficacy, and are not to be construed as limiting the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. A fake-licensed vehicle detection method is characterized by comprising the following steps:
presetting a plurality of target detection points, and acquiring detection information, wherein the detection information comprises position information, detection time information and target vehicle information of the target detection points, and the target vehicle information at least comprises license plate information and characteristic information;
calculating the speed of a target vehicle according to the detection information of the target vehicle with the same license plate information at different target detection points;
the target vehicle is judged once, and when the speed of the target vehicle is abnormal, the target vehicle is judged to be a suspected vehicle;
and performing secondary judgment on the target vehicle according to the primary judgment result of the target vehicle and the characteristic information of the target vehicle, and confirming whether the target vehicle is fake plate.
2. The fake-licensed vehicle detecting method according to claim 1, characterized in that:
the making of the one-time determination of the target vehicle includes: when the speed of the target vehicle exceeds a preset speed threshold, judging the target vehicle to be a suspected vehicle, and giving an initial confidence coefficient;
the secondarily determining the target vehicle includes: and acquiring registration information of the target vehicle, matching the characteristic information of the target vehicle with the registration information, updating the initial confidence level according to a matching result, and confirming whether the target vehicle is fake plate or not according to the updated confidence level.
3. The fake-licensed vehicle detecting method according to claim 2, characterized in that:
classifying registration information in advance, and setting different confidence scores for each type of registration information, wherein the types of the registration information comprise vehicle brands, vehicle models and vehicle colors;
and comparing the characteristic information with each type of registration information in sequence, increasing or decreasing the corresponding confidence score for the initial confidence according to the comparison result of each type of registration information, and stopping continuous comparison when the confidence reaches 100 percent.
4. The fake-licensed vehicle detecting method according to claim 3, further comprising, after performing the secondary determination on the target vehicle:
classifying feature information in advance, and setting different confidence scores for each type of feature information, wherein the types of the feature information comprise static identification information used for representing static features of a vehicle, dynamic identification information used for representing a vehicle state, and personnel identification information used for representing personnel features in the vehicle;
and comparing the feature information acquired this time with the previous time in sequence, and increasing or decreasing the corresponding confidence score of the previous time according to the comparison result to acquire the updated confidence.
5. The fake-licensed vehicle detecting method according to claim 4, characterized in that: the target detection point is a bayonet, the detection information comprises bayonet snapshot data, and the static identification information comprises a vehicle body color, a vehicle type and a vehicle brand; the dynamic identification information comprises a driving direction, a lane number, an annual inspection mark, a sunshade plate state and whether a placed object exists or not; the personnel identification information comprises the face characteristics of the driver and the safety belt state.
6. The fake-licensed vehicle detecting method according to claim 1, characterized in that: the acquiring the speed of the target vehicle according to the detection information of the target vehicle with the same license plate information at different target detection points comprises the following steps:
when a target vehicle detecting the same license plate information passes through two target detection points at different time, acquiring the distance between the two target detection points;
acquiring a theoretical average speed of the target vehicle according to the detection time difference and the distance between the two target detection points;
and when the vehicle speed of the target vehicle exceeds a preset speed threshold value, determining that the target vehicle is a suspected vehicle.
7. The fake-licensed vehicle detecting method according to claim 5, characterized in that: when the characteristic information is compared, if the comparison results are the same, the confidence coefficient is reduced; if the comparison results are different, increasing the confidence coefficient; different weights are set according to different kinds of influences of the characteristic information, and confidence scores are set according to the weights.
8. A fake-licensed vehicle detection system, comprising:
the system comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring detection information at a plurality of preset target detection points, the detection information comprises position information, detection time information and target vehicle information of the target detection points, and the target vehicle information at least comprises license plate information and characteristic information;
the data processing module is used for acquiring the speed of a target vehicle according to the detection information of the target vehicle with the same license plate information at different target detection points;
the primary judgment module is used for carrying out primary judgment on the target vehicle and judging the target vehicle as a suspected vehicle when the speed of the target vehicle is abnormal;
and the secondary judgment module is used for carrying out secondary judgment on the target vehicle according to the primary judgment result of the target vehicle and the characteristic information of the target vehicle and confirming whether the target vehicle is fake plate or not.
9. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program, when executed by a processor, implements the method of any one of claims 1 to 7.
10. An electronic terminal, comprising: a processor and a memory;
the memory is for storing a computer program and the processor is for executing the computer program stored by the memory to cause the terminal to perform the method of any of claims 1 to 7.
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