CN111368868B - Method, device and equipment for determining vehicle fake license plate - Google Patents
Method, device and equipment for determining vehicle fake license plate Download PDFInfo
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Abstract
The application provides a method, a device and equipment for determining vehicle fake license plates. The method comprises the following steps: the license plate set corresponding to any two adjacent track information in the first track set is obtained by obtaining the first track set corresponding to the first vehicle license plate number, the license plate sets corresponding to any two adjacent track information are obtained respectively, similarity comparison is carried out on the license plate sets corresponding to any two adjacent track information respectively, whether the first vehicle has a fake-licensed action is determined according to the similarity comparison result, the result of the similarity of the vehicle sets is obtained by comparing the vehicle sets of bayonets where the first vehicle license plate passes through in the first track set, whether the first vehicle has the fake-licensed action is determined, and efficient identification on whether the first vehicle license plate has the fake-licensed in big data is realized.
Description
Technical Field
The application relates to the technical field of traffic big data, in particular to a method, a device and equipment for determining vehicle fake-licensed.
Background
Along with the continuous rising of the vehicle storage quantity, the illegal behavior of vehicle fake license plates is gradually increased, the vehicle fake license plates are license plates of other people, namely clone vehicles, fake license plates with the same number are sleeved on vehicles with the same model and color by referring to the model and color of real license plates, and the vehicle fake license plates bring great economic loss and safety hazard to real license plate vehicle owners and society.
In the prior art, whether a fake license plate exists in a vehicle is determined based on a vehicle management library, license plates of all motor vehicles and corresponding vehicle information, such as vehicle colors, vehicle types, vehicle brands and the like, are stored in the vehicle management library, the vehicle license plate numbers are acquired and identified through monitoring equipment, the vehicle license plate numbers are compared with the vehicle information of the vehicle license plate numbers stored in the vehicle management library, and if the vehicle license plate numbers are the same but the vehicle information does not accord with the information stored in the vehicle management library, the vehicle is determined to be a fake license plate vehicle.
However, in practical application, because the probability of false recognition is unavoidable in the process of recognizing the vehicles by the monitoring equipment, the large data amount required to be recognized by the monitoring equipment leads to the fact that most fake-licensed vehicles recognized by the method are false recognition vehicles, and the recognized vehicle license numbers are compared with huge data stored in a vehicle management library, so that the time consumption is long, the accuracy of the recognition technology for the fake-licensed vehicles in the prior art is poor, and the efficiency is low.
Disclosure of Invention
The application provides a method, a device and equipment for determining fake-licensed vehicles, which are based on acquired passing data of a plurality of bayonets, and realize efficient and accurate confirmation of whether fake-licensed behaviors exist.
In a first aspect, the present application provides a method of determining a vehicle fake-licensed comprising:
acquiring a first track set corresponding to a first vehicle number, wherein the first track set comprises a plurality of track information which are ordered in time sequence, the track information comprises bayonet information when a first vehicle passes through a bayonet and time, and the first vehicle is a vehicle for installing the first vehicle number;
for any two adjacent track information in the first track set, obtaining license plate sets respectively corresponding to the any two adjacent track information, wherein the license plate sets comprise at least one vehicle license plate number which follows the first vehicle to pass through the same bayonet, and comparing the similarity of the license plate sets respectively corresponding to the any two adjacent track information;
and determining whether the fake-licensed behavior exists in the first vehicle according to the similarity comparison result.
In a specific implementation manner, the determining whether the first vehicle has a fake-licensed behavior according to the similarity comparison result includes:
if the number of times that the vehicle license number intersection between any two license plate sets corresponding to adjacent track information is zero in the first track set is larger than a preset threshold value, determining that a fake-licensed behavior exists in the first vehicle;
Otherwise, determining that the first vehicle does not have fake-licensed behaviors.
Further, the method further comprises:
obtaining a passing set according to passing data acquired by a plurality of bayonets arranged in a preset area, wherein the passing data comprises a vehicle number and time of passing through each bayonet, and the passing set comprises bayonet information of the plurality of bayonets and passing data corresponding to each bayonet;
the obtaining the first track set corresponding to the first vehicle license number includes:
obtaining a plurality of track information corresponding to the first vehicle license number according to the passing set and the first vehicle license number;
and sequencing the plurality of track information in time sequence to obtain the first track set.
Further, the method further comprises:
according to the passing set, a plurality of license plate sets are obtained, each license plate set comprises a regular time, a piece of bayonet information and a vehicle license plate number of at least one vehicle, the regular time passes through a bayonet corresponding to the bayonet information, and the regular time is used for indicating a time period of the vehicle, the time of which passes through the bayonet, belongs to.
Optionally, before obtaining license plate sets corresponding to the arbitrary two adjacent track information respectively, the method further includes:
Comparing the time difference of any two adjacent track information with a preset interval threshold value;
if the time difference between two adjacent track information is smaller than the interval threshold value, acquiring license plate sets corresponding to any two adjacent track information respectively.
In a second aspect, the present application provides an apparatus for determining a vehicle fake-licensed, the apparatus comprising:
the system comprises an acquisition module, a first license plate number acquisition module and a second license plate number acquisition module, wherein the acquisition module is used for acquiring a first track set corresponding to the first license plate number, the first track set comprises a plurality of track information which are ordered in time sequence, the track information comprises the bayonet information when a first vehicle passes through each bayonet, and the first vehicle is a vehicle for installing the first license plate number;
the processing module is used for acquiring license plate sets corresponding to any two adjacent track information in the first track set respectively, wherein the license plate sets comprise at least one vehicle license plate number which follows the first vehicle to pass through the same bayonet, and similarity comparison is carried out on the license plate sets corresponding to the any two adjacent track information respectively;
the processing module is further used for determining whether the fake-licensed behaviors exist in the first vehicle according to the similarity comparison result.
In a specific implementation, the processing module is specifically configured to:
if the number of times that the vehicle license number intersection between any two license plate sets corresponding to adjacent track information is zero in the first track set is larger than a preset threshold value, determining that a fake-licensed behavior exists in the first vehicle;
otherwise, determining that the fake-licensed action does not exist.
Further, the processing module is further configured to: obtaining a passing set according to passing data acquired by a plurality of bayonets arranged in a preset area, wherein the passing data comprises a vehicle number and time of passing through each bayonet, and the passing set comprises bayonet information of the plurality of bayonets and passing data corresponding to each bayonet;
the acquisition module is specifically configured to: obtaining a plurality of track information corresponding to the first vehicle license number according to the passing set and the first vehicle license number; and sequencing the plurality of track information in time sequence to obtain the first track set.
Further, the acquisition module is further configured to:
according to the passing set, a plurality of license plate sets are obtained, each license plate set comprises a regular time, a piece of bayonet information and a vehicle license plate number of at least one vehicle, the regular time passes through a bayonet corresponding to the bayonet information, and the regular time is used for indicating a time period of the vehicle, the time of which passes through the bayonet, belongs to.
Optionally, the processing module is further configured to:
comparing the time difference of any two adjacent track information with a preset interval threshold value;
if the time difference between two adjacent track information is smaller than the interval threshold value, acquiring license plate sets corresponding to any two adjacent track information respectively.
In a third aspect, the present application provides an electronic device, comprising: a memory and a processor;
the memory stores computer-executable instructions;
the processor executes computer-executable instructions stored by the memory, causing the processor to perform the method of determining vehicle trowels as described in the first aspect.
In a fourth aspect, the present application provides a storage medium comprising: a readable storage medium and a computer program for implementing the method of determining a vehicle fake-licensed of the first aspect.
According to the method, the device and the equipment for determining the vehicle license plate, the first track set corresponding to the first vehicle license plate number is obtained, the first track set comprises a plurality of track information which are sequenced in time sequence, the track information comprises the bayonet information when the first vehicle passes through each bayonet, the first vehicle is a vehicle provided with the first vehicle license plate number, any two adjacent track information in the first track set is aimed at, license plate sets corresponding to the any two adjacent track information respectively are obtained, the license plate sets comprise the first vehicle license plate number and at least one vehicle license plate number which follows the first vehicle and passes through the same bayonet, similarity comparison is carried out on the any two adjacent track information respectively, whether the first vehicle license plate is in a fake license plate behavior is determined according to the result of similarity comparison, and whether the first vehicle license plate is in a fake license plate behavior is determined by comparing the vehicle sets of the bayonets of the first vehicle license plate number passing through the first track set in adjacent time, so that whether the first vehicle license plate is in the first track set is in a large data is identified.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief description will be given below of the drawings that are needed in the embodiments or the prior art descriptions, it being obvious that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic flow chart of a first embodiment of a method for determining a vehicle fake-licensed according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a second embodiment of a method for determining a vehicle fake-licensed according to an embodiment of the present application;
fig. 3 is a schematic flow chart of a third embodiment of a method for determining a vehicle fake-licensed according to an embodiment of the present application;
FIG. 4 is a schematic diagram of an embodiment of a process resulting in a regular time provided in the embodiments of the present application;
fig. 5 is a schematic flow chart of a fourth embodiment of a method for determining a vehicle fake-licensed according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an embodiment one of a device for determining a fake-licensed vehicle according to an embodiment of the present application;
fig. 7 is a schematic hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The terms "comprises," "comprising," and any variations thereof, as used herein, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
Reference throughout this specification to "one embodiment" or "another embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in one embodiment" or "in this embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
The execution subject of the present application is an electronic device, which may be any terminal device having data processing capabilities, such as a computer, or a server.
The method for determining the vehicle fake-licensed does not need to process a large number of path relations, does not depend on a large number of historical data, has better real-time performance, and is described in the following through a few specific embodiments.
In this scheme, can set for a province, a city, a merchant district, or several streets and predetermine the region, in predetermineeing the region, be provided with a plurality of bayonet sockets, set up respectively in a plurality of highway sections in urban road, for example, can set up in the crossing, or set up in the highway section, every highway section can have one to a plurality of bayonet sockets, and image acquisition device is installed to every bayonet socket, carries out image acquisition to the vehicle through the bayonet socket, rejects the unclear image of vehicle number, carries out the record to the data of driving that gathers, the data of driving includes vehicle number and the time of passing through this bayonet socket.
Fig. 1 is a schematic flow chart of a first embodiment of a method for determining a vehicle fake-licensed, where, as shown in fig. 1, the method for determining a vehicle fake-licensed includes:
S101: a first track set corresponding to the first vehicle card number is obtained.
The first track set comprises a plurality of track information which are ordered in time sequence, wherein the track information comprises the information of the bayonets when a first vehicle passes through each bay and the time, and the first vehicle is a vehicle provided with the first vehicle number.
Acquiring a first track set corresponding to the first vehicle number, namely inquiring in the passing data of each bayonet according to the first vehicle number to find out the information and time of each bayonet passed by the first vehicle, optionally, corresponding the information and time of each bayonet to form track information of the bayonet, for example, the bayonet information is denoted as c i The time elapsed through the bayonet is denoted t i The bayonet information and the time are correspondingly formed into track information c of the first vehicle i -t i And arranging each track information of the first vehicles according to time sequence to form a first track set corresponding to the first vehicles, for example, the track L1 set of the first vehicles is [ c ] 1 -t 1 ，c 2 -t 2 ，……，c i -t i ]Each piece of bayonet information and the track information formed by time are one element in the track L1 set, wherein the time sequence can be in an ascending time sequence or in a descending time sequence.
S102: and aiming at any two adjacent track information in the first track set, acquiring license plate sets corresponding to the any two adjacent track information respectively, and comparing the similarity of the license plate sets corresponding to the any two adjacent track information respectively.
The license plate set comprises at least one vehicle license plate number which follows the first vehicle to pass through the same gate, and optionally, the license plate set corresponding to each track information is obtained, namely, the license plate set is queried in the passing data according to the gate information and the time of each track information, and the set of the vehicle license plate numbers of the vehicles which pass through the same gate in the same time or the same time period and except the first vehicle is found.
And comparing the license plate sets corresponding to the two track information in similarity, namely comparing whether the license plate sets passing through the two bayonets have intersections or not under the condition of comparing two adjacent time, wherein the license plate sets comprise all vehicle license plate numbers passing through the same bayonets by following the first vehicle, in some embodiments, the license plate sets comprise the vehicle license plate numbers passing through the bayonets by the first vehicle and at least one vehicle license plate number passing through the same bayonets by following the first vehicle, and when comparing whether the license plate sets respectively corresponding to the adjacent track information have intersections or not, the vehicle license plate numbers of the first vehicle need to be removed, and only the following vehicle license plate numbers of the first vehicle in the vehicle license plate number sets passing through the two bayonets are judged.
In some embodiments, in order to avoid that the first vehicle stays between the bayonets of the two track information for a long time, so that the first vehicle is obviously changed with the vehicle in the two bayonets, and the accuracy of the final similarity comparison result is affected, the time interval of the two adjacent track information needs to be confirmed, if the time interval is greater than or equal to a preset interval threshold, the similarity comparison of license plate sets corresponding to the two track information is stopped, and if the time interval is less than the preset interval threshold, the similarity comparison of license plate sets corresponding to the two track information is performed.
In a specific implementation, the time of two adjacent track information is t 1 And t 2 For example, in the set of traces L1, t 1 And t 2 The corresponding two track information is c 1 -t 1 ，c 2 -t 2 Let t be 1 And t 2 The interval time between the two is smaller than the interval threshold value, the time t is 1 And t 2 Respectively and correspondingly, the bayonet information is combined into a Key (Key), or pairTime t 1 And t 2 Processing to obtain regular time, combining the regular time and corresponding bayonet information into Key, for example Key1 is 0900-cross 1, key2 is 0900-cross 2, corresponding values (Value) V1 and V2 are searched in a MAP set according to K1 and K2, wherein V1 and V2 are respectively a group of license plate sets, the license plate sets comprise at least one vehicle license plate number which follows a first vehicle to pass through the same bayonet at the same regular time, the vehicle license plate number is also called a following vehicle, the vehicle license plate numbers of the following vehicles in the two sets of V1 and V2 are compared, and whether the intersection of the vehicle license plate numbers in the two license plate sets of V1 and V2 is zero is determined.
S103: and determining whether the first vehicle has fake-licensed behaviors according to the similarity comparison result.
After the process described in step S102 is performed on each two adjacent track information in the first track set, a similarity result between one or more adjacent track information is obtained, and whether a fake-licensed vehicle exists is determined according to the one or more similarity results.
In a specific implementation manner, in the process described in step S102, for each two adjacent track information in the first track set, the number of times that the intersection of the vehicle sets corresponding to each two adjacent track information is zero is accumulated, and if the number of times is greater than a preset threshold, it is determined that the first vehicle has a fake-licensed action, otherwise, it is determined that the first vehicle does not have a fake-licensed action.
According to the method, the device and the equipment for determining the vehicle license plate, the first track set corresponding to the first vehicle license plate number is obtained, the first track set comprises a plurality of track information which are sequenced in time sequence, the track information comprises the bayonet information when the first vehicle passes through each bayonet, the first vehicle is a vehicle provided with the first vehicle license plate number, any two adjacent track information in the first track set is aimed at, license plate sets corresponding to the any two adjacent track information respectively are obtained, the license plate sets comprise the first vehicle license plate number and at least one vehicle license plate number which follows the first vehicle and passes through the same bayonet, similarity comparison is carried out on the any two adjacent track information respectively, whether the first vehicle license plate is in a fake license plate behavior is determined according to the result of similarity comparison, and whether the first vehicle license plate is in a fake license plate behavior is determined by comparing the vehicle sets of the bayonets of the first vehicle license plate number passing through the first track set in adjacent time, so that whether the first vehicle license plate is in the first track set is in a large data is identified.
On the basis of the embodiment shown in fig. 1, fig. 2 is a schematic flow chart of a second embodiment of a method for determining a vehicle fake-licensed according to the embodiment of the present application, and as shown in fig. 2, the method for determining a vehicle fake-licensed further includes:
s201: and obtaining a passing set according to the passing data acquired by the plurality of bayonets arranged in the preset area.
The vehicle passing data comprise vehicle license numbers and passing time of each bayonet, and the vehicle passing set comprises bayonet information of a plurality of bayonets and vehicle passing data corresponding to each bayonet.
The preset area is a preset or defined area, the size of the area can be set according to the needs of practical application scenes, for example, a province, a city, a business area or a plurality of streets are set as the preset area, a plurality of bayonets are arranged in the preset area, a plurality of road sections respectively arranged in urban roads, for example, the road sections can be arranged at intersections or the road sections, each road section can be provided with one to a plurality of bayonets, and each bay is provided with an image acquisition device.
In this step, the image acquisition device provided at the bayonet may acquire the vehicle image passing through the bayonet and record the time of image acquisition, and process the vehicle image passing through the bayonet acquired by each bayonet to obtain the vehicle passing data acquired by each bayonet, where the vehicle passing data includes the number of the vehicle passing through each bayonet and the time of the vehicle passing through the bayonet, it should be understood that each bayonet has corresponding bayonet information, also referred to as a bayonet identifier, and the bayonet information and the corresponding vehicle passing data are used as one element of the vehicle passing set, for example, the image acquisition device installed on the bayonet with the bayonet information being crosid 1 acquires that the vehicle plateNo1 is in 9:00 passes through the bayonet, and vehicle platel No. 2 passes through the bayonet at 9 points 04, and the passing set comprises [ crosssild 1-platel No. 1-0900, crosssild 1-platel No. 2-0904], and it is understood that the bayonet information, the vehicle number and the passing time of each element in the passing set have no sequence requirement.
In a specific implementation, the image capturing device captures images at preset time intervals or according to preset triggering conditions, and before information is extracted according to the captured vehicle images, the captured vehicle images need to be filtered, for example, images with blurred numbers of the vehicle license plates or vehicle images of the host vehicle are filtered. Further, in the process of identifying the vehicle image, in order to avoid repeatedly identifying the same vehicle license number from the plurality of vehicle images, only the vehicle license number of the host vehicle in the vehicle image is identified, the host vehicle may be a vehicle appearing in the middle position in the vehicle image, or a vehicle appearing in the forefront of the vehicle image, it may be understood that the vehicle running to the nearest image acquisition device is the host vehicle, the vehicle passing through the bayonet in the preset time period before or after the host vehicle acquired by the image acquisition device is the following vehicle, and the vehicle license numbers identified in the preset time period may be the following vehicles.
S202: and obtaining a plurality of track information corresponding to the first vehicle license number according to the passing set and the first vehicle license number.
The passing set comprises the corresponding relation among the bayonet information, the vehicle number, the passing time and the three of each bayonet. Searching or traversing the first vehicle number in the passing vehicle set to obtain the information of each bayonet passed by the first vehicle and the time of passing each bayonet, and correspondingly forming track information by the information of each bayonet and the time of passing the bayonet, wherein in the actual application scene, the number of the bayonets passed by the first vehicle can be one to a plurality, so that the number of the track information is one to a plurality.
Optionally, in order to ensure accuracy of similarity comparison, necessary screening needs to be performed on the track information, and if the number of bayonets passed by the first vehicle is very small, for example, only two bayonets are passed, then the number of track information corresponding to the first vehicle number is only two, and accuracy of a similarity result is affected when the similarity of the host vehicle to the vehicle is judged, so that when the number of track information corresponding to the first vehicle number is smaller than a preset track length threshold, one or more track information corresponding to the first vehicle number is deleted; and when the number of the track information corresponding to the first vehicle card number is greater than or equal to a preset track length threshold value, reserving a plurality of track information corresponding to the first vehicle card number.
Alternatively, the preset track length threshold may be 5.
S203: and ordering the plurality of track information in time sequence to obtain a first track set.
And (3) sequencing the track information corresponding to the first vehicle number obtained in the step S202 in time sequence to obtain a first track set.
It should be appreciated that in a practical application scenario, each vehicle number, including the first vehicle number, corresponds to a track set.
In a specific implementation manner, assuming that the first vehicle is PlateNo1 in table 1, arranging the track information ci-ti in time ascending order to obtain ordered track information, splicing the bayonet information ci and the time ti of the ordered track information into a character string, and putting the character string and the character string into a track L list corresponding to Key PlateNo1, wherein the data format in the list is [ c1-t1, c2-t2, …, ci-ti ], so as to obtain a first track set, and according to the method, a track set corresponding to each vehicle license number can be obtained, as shown in table 1.
| Key | Track L |
| PlateNo1 | [c1-t1,c2-t2,…,ci-ti] |
| PlateNo2 | [c1-t1,c2-t2,…,ci-ti] |
| …… | …… |
| PlateNon | [c1-t1,c2-t2,…,ci-ti] |
TABLE 1
In this embodiment, according to the passing set and the first vehicle number, a plurality of track information corresponding to the first vehicle number is obtained, and the track information is sequenced in time sequence, so as to obtain the first track set, so that similarity comparison is performed according to any two adjacent track information in the first track set, and accuracy of the similarity comparison is ensured.
On the basis of the embodiment shown in fig. 1, fig. 3 is a schematic flow chart of a third embodiment of a method for determining a vehicle fake-licensed according to the embodiment of the present application, and as shown in fig. 3, the method for determining a vehicle fake-licensed further includes:
s301: and obtaining a passing set according to the passing data acquired by the plurality of bayonets arranged in the preset area.
The vehicle passing data comprise vehicle license numbers and passing time of each bayonet, and the vehicle passing set comprises bayonet information of a plurality of bayonets and vehicle passing data corresponding to each bayonet.
The specific implementation process of this step is similar to step S201, and will not be repeated here.
S302: and acquiring a plurality of license plate sets according to the passing set.
Each license plate set comprises a regular time, a piece of bayonet information and a vehicle license number of at least one vehicle, wherein the regular time passes through a bayonet corresponding to the bayonet information, and the regular time is used for indicating a time period to which the time of the vehicle passing through the bayonet belongs.
The passing set comprises bayonet information of a plurality of bayonets and passing data corresponding to each bayonet, and the passing data of each bayonet comprises bayonet information, vehicle number, passing time and corresponding relations among the bayonets.
In this step, first, the elapsed time is normalized to obtain a normalized time, and a plurality of data sets are obtained, where each data set includes a normalized time, a bayonet information, and a vehicle number, for example, all the passing data is traversed, the passing time (passTime) is taken out, the passTime is normalized according to the position of the passTime within a 1 hour time segment, the segment size is configurable, the segment size is related to a set following time δt, where δt may be generally 3-5 minutes, and the following time is used to represent how long the vehicle appears before and after the host vehicle is determined to be a following vehicle, and for simplicity of description, in conjunction with fig. 4, fig. 4 is a schematic diagram of an embodiment of the normalized time obtained by a process provided in this embodiment of the present application, and in a 30 minute segment example, that 1 hour is divided into 2 segments, 9:22 is located in the corresponding section within 1 hour, the corresponding time is normalized to 9:00, and 0900 is taken as an identification. Next, the regular time and the gate information are combined into a character string, for example 0900-cross 1, as a Key, and a Value (Value) corresponding to the Key is determined from the correspondence among the gate information, the vehicle number, and the elapsed time, the content of the Value being the vehicle number (plateNox is a specific number), as shown in table 2, table 2 is only one example.
| Key | Value |
| 0900-crossid1 | plateNo1 |
| 0900-crossid1 | plateNo2 |
| 0900-crossid2 | plateNo1 |
| 0900-crossid2 | plateNo2 |
TABLE 2
And secondly, taking all vehicle license plate numbers corresponding to the same regular time and the same bayonet information as a license plate set. It should be understood that each vehicle license number in the license plate set may be the host vehicle, and when comparing the similarity between any two license plate sets corresponding to the adjacent track information of the first vehicle license number, the first vehicle license number in the two license plate sets should be removed first, and only the similarity between the two license plate sets and the vehicle is compared.
In the embodiment, huge passing data are subjected to rapid data processing to obtain license plate sets corresponding to each track information, so that the scheme can be applied to the obtained license plate sets to rapidly and accurately judge whether fake license plate behaviors exist or not, and the data processing efficiency is improved.
On the basis of the foregoing embodiments, fig. 5 is a schematic flow chart of a fourth embodiment of a method for determining a vehicle license plate according to the embodiment of the present application, where, as shown in fig. 5, before obtaining license plate sets corresponding to any two adjacent track information respectively, the method further includes:
s401: and comparing the time difference between any two adjacent track information with a preset interval threshold value.
In the first track set, any two adjacent track information is traversed, the time interval between the two adjacent track information is determined, namely the time difference between the two track information is determined, if the interval time is too long, the first vehicle stays between two bayonets corresponding to the two adjacent track information for a long time, so that obvious change of the first vehicle in the two bayonets along with the vehicle is easily caused, the accuracy of a final similarity comparison result is affected, and therefore whether the license plate set corresponding to the two adjacent track information is subjected to similarity comparison is determined by comparing the time difference between any two adjacent track information with a preset interval threshold value.
S402: if the time difference between two adjacent track information is smaller than the interval threshold value, acquiring license plate sets corresponding to any two adjacent track information respectively.
Comparing the time difference of two adjacent track information with a preset interval threshold, and when the time difference is larger than the preset interval threshold, not comparing the similarity of the gate information, wherein the time difference of the two adjacent track information is smaller, if the time difference is smaller than the interval threshold, acquiring license plate sets corresponding to any two adjacent track information respectively, and optionally, if the license plate sets comprise first vehicle license plate numbers, deleting the first vehicle license plate numbers.
In a specific implementation manner, as can be seen from table 1, assuming that the first vehicle number is PlateNo1, performing a traversal operation on the first track set corresponding to PlateNo1, filtering out data that the time difference in the adjacent track information does not meet the interval threshold value readn, where readn is a configurable parameter, and optionally, readn=5. Specifically, traversing the first track set (track set corresponding to PlateNo1 in Table 1), and obtaining adjacent two track information to obtain bayonet information ci, c i+1 Time ti, t i+1 When t i+1 –ti>the wiredT does not acquire license plate sets corresponding to the two adjacent track information respectively, skips the similarity step of comparing the license plate information corresponding to the two adjacent track information, and if t is satisfied i+1 –ti<And acquiring license plate sets corresponding to the two adjacent track information respectively by using the wiredT.
Fig. 6 is a schematic structural diagram of an embodiment one of a device for determining a vehicle fake-licensed, and as shown in fig. 6, the device 10 for determining a vehicle fake-licensed includes:
an obtaining module 11, configured to obtain a first track set corresponding to a first vehicle number, where the first track set includes a plurality of track information ordered in time sequence, where the track information includes information of a first vehicle passing through each of the bayonets and time, and the first vehicle is a vehicle on which the first vehicle number is installed;
The processing module 12 is configured to obtain license plate sets corresponding to any two adjacent track information in the first track set respectively, where the license plate sets include at least one vehicle license plate number that follows the first vehicle to pass through the same bayonet, and perform similarity comparison on the license plate sets corresponding to the any two adjacent track information respectively;
the processing module 12 is further configured to determine whether the first vehicle has a fake-licensed action according to the similarity comparison result.
The apparatus 10 for determining a vehicle fake-licensed provided in the embodiment of the present application includes: the acquiring module 11 and the processing module 12 acquire a first track set corresponding to a first vehicle license number, wherein the first track set comprises a plurality of track information which are sequenced in time sequence, the track information comprises bayonet information when a first vehicle passes through each bayonet, the first vehicle is a vehicle provided with the first vehicle license number, any two adjacent track information in the first track set is used for acquiring license plate sets corresponding to any two adjacent track information respectively, the license plate sets comprise the first vehicle license number and at least one vehicle license number which follows the first vehicle and passes through the same bayonet, similarity comparison is carried out on license plate sets corresponding to any two adjacent track information respectively, whether the first vehicle has a fake license plate behavior is determined according to a similarity comparison result, and whether the first vehicle has a fake license plate behavior is determined by comparing the vehicle sets of the bayonets of the first vehicle passing through the first track set at adjacent time, so that whether the first vehicle has the fake license plate behavior is determined, and high-efficient identification of whether the first vehicle has the fake license plate in big data is realized.
In one possible design, the processing module 12 is specifically configured to:
if the number of times that the vehicle license number intersection between any two license plate sets corresponding to adjacent track information is zero in the first track set is larger than a preset threshold value, determining that a fake-licensed behavior exists in the first vehicle;
otherwise, determining that the fake-licensed action does not exist.
In one possible design, the processing module 12 is further configured to obtain a passing set according to the passing data collected by the plurality of bayonets set in the preset area, where the passing data includes a number of a vehicle passing through each bay and a time, and the passing set includes bay information of the plurality of bayonets and passing data corresponding to each bay;
the acquisition module 11 is specifically configured to: obtaining a plurality of track information corresponding to the first vehicle license number according to the passing set and the first vehicle license number;
and sequencing the plurality of track information in time sequence to obtain the first track set.
In one possible design, the acquisition module 11 is further configured to:
according to the passing set, a plurality of license plate sets are obtained, each license plate set comprises a regular time, a piece of bayonet information and a vehicle license plate number of at least one vehicle, the regular time passes through a bayonet corresponding to the bayonet information, and the regular time is used for indicating a time period of the vehicle, the time of which passes through the bayonet, belongs to.
In one possible design, the processing module 11 is further configured to:
comparing the time difference of any two adjacent track information with a preset interval threshold value;
if the time difference between two adjacent track information is smaller than the interval threshold value, acquiring license plate sets corresponding to any two adjacent track information respectively.
The device for determining the vehicle fake-licensed provided by the embodiment can execute the technical scheme of the method embodiment, and the implementation principle and the technical effect are similar, and the embodiment is not repeated here.
The embodiment of the present application further provides an electronic device, and referring to fig. 7, the embodiment of the present application is only illustrated by taking fig. 7 as an example, and the embodiment of the present application is not limited thereto.
Fig. 7 is a schematic hardware structure of an electronic device according to an embodiment of the present application. As shown in fig. 7, the electronic device 20 provided in this embodiment may include: a memory 201, a processor 202; optionally, a bus 203 may also be included. Wherein the bus 203 is used to implement the connections between the elements.
The memory 201 stores computer-executable instructions;
the processor 202 executes computer-executable instructions stored in the memory 201 to cause the processor to perform the method of determining a vehicle pool card provided in any of the preceding embodiments.
The memory 201 is directly or indirectly electrically connected to the processor 202, so as to realize data transmission or interaction. For example, the elements may be electrically coupled to each other via one or more communication buses or signal lines, such as via bus 203. Stored in the memory 201 are computer-executable instructions for implementing a data access control method, including at least one software functional module that may be stored in the memory 201 in the form of software or firmware, and the processor 202 executes various functional applications and data processing by running the software programs and modules stored in the memory 201.
The Memory 201 may be, but is not limited to, random access Memory (Random Access Memory, RAM), read Only Memory (ROM), programmable Read Only Memory (Programmable Read-Only Memory, PROM), erasable Read Only Memory (Erasable Programmable Read-Only Memory, EPROM), electrically erasable Read Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc. The memory 201 is used for storing a program, and the processor 202 executes the program after receiving an execution instruction. Further, the software programs and modules within the memory 201 may also include an operating system, which may include various software components and/or drivers for managing system tasks (e.g., memory management, storage device control, power management, etc.), and may communicate with various hardware or software components to provide an operating environment for other software components.
The processor 202 may be an integrated circuit chip with signal processing capabilities. The processor 202 may be a general-purpose processor, including a central processing unit (Central Processing Unit, abbreviated as CPU), a network processor (Network Processor, abbreviated as NP), and the like. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. It will be appreciated that the configuration of fig. 7 is illustrative only and may include more or fewer components than shown in fig. 7 or have a different configuration than shown in fig. 7. The components shown in fig. 7 may be implemented in hardware and/or software.
The embodiment of the application also provides a computer readable storage medium, on which computer-executable instructions are stored, which when executed by a processor, can implement the method for determining a vehicle fake-licensed provided by any one of the method embodiments.
The computer readable storage medium in this embodiment may be any available medium that can be accessed by a computer or a data storage device such as a server, a data center, etc. that contains one or more available medium(s) integrated, and the available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., an SSD), etc.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.
Claims (12)
1. A method of determining a vehicle fake plate, comprising:
acquiring a first track set corresponding to a first vehicle number, wherein the first track set comprises a plurality of track information which are ordered in time sequence, the track information comprises bayonet information when a first vehicle passes through a bayonet and time, and the first vehicle is a vehicle for installing the first vehicle number;
For any two adjacent track information in the first track set, obtaining license plate sets respectively corresponding to the any two adjacent track information, wherein the license plate sets comprise at least one vehicle license plate number which follows the first vehicle to pass through the same bayonet, and comparing the similarity of the license plate sets respectively corresponding to the any two adjacent track information;
determining whether the fake-licensed behaviors exist in the first vehicle according to the similarity comparison result;
the obtaining the license plate sets respectively corresponding to the arbitrary two adjacent track information comprises the following steps:
inquiring in the passing data according to the gate information and time of each track information in the first track set to find a set of vehicle license plate numbers of vehicles except the first vehicle passing through the same gate at the same time or in the same time period;
the step of comparing the similarity of license plate sets corresponding to any two adjacent track information respectively comprises the following steps:
and comparing whether intersection exists among license plate sets passing through the two bayonets or not under the condition of two adjacent times.
2. The method of claim 1, wherein determining whether the first vehicle has a fake-licensed action based on the similarity comparison result comprises:
If the number of times that the vehicle license number intersection between any two license plate sets corresponding to adjacent track information is zero in the first track set is larger than a preset threshold value, determining that a fake-licensed behavior exists in the first vehicle;
otherwise, determining that the first vehicle does not have fake-licensed behaviors.
3. The method according to claim 1 or 2, characterized in that the method further comprises:
obtaining a passing set according to passing data acquired by a plurality of bayonets arranged in a preset area, wherein the passing data comprises a vehicle number and time of passing through each bayonet, and the passing set comprises bayonet information of the plurality of bayonets and passing data corresponding to each bayonet;
the obtaining the first track set corresponding to the first vehicle license number includes:
obtaining a plurality of track information corresponding to the first vehicle license number according to the passing set and the first vehicle license number;
and sequencing the plurality of track information in time sequence to obtain the first track set.
4. A method according to claim 3, characterized in that the method further comprises:
according to the passing set, a plurality of license plate sets are obtained, each license plate set comprises a regular time, a piece of bayonet information and a vehicle license plate number of at least one vehicle, the regular time passes through a bayonet corresponding to the bayonet information, and the regular time is used for indicating a time period of the vehicle, the time of which passes through the bayonet, belongs to.
5. The method according to claim 1 or 2, wherein before obtaining license plate sets corresponding to the any two adjacent track information respectively, the method further comprises:
comparing the time difference of any two adjacent track information with a preset interval threshold value;
if the time difference between two adjacent track information is smaller than the interval threshold value, acquiring license plate sets corresponding to any two adjacent track information respectively.
6. An apparatus for determining a vehicle fake-licensed, the apparatus comprising:
the system comprises an acquisition module, a first license plate number acquisition module and a second license plate number acquisition module, wherein the acquisition module is used for acquiring a first track set corresponding to the first license plate number, the first track set comprises a plurality of track information which are ordered in time sequence, the track information comprises the bayonet information when a first vehicle passes through each bayonet, and the first vehicle is a vehicle for installing the first license plate number;
the processing module is used for acquiring license plate sets corresponding to any two adjacent track information in the first track set respectively, wherein the license plate sets comprise at least one vehicle license plate number which follows the first vehicle to pass through the same bayonet, and similarity comparison is carried out on the license plate sets corresponding to the any two adjacent track information respectively;
The processing module is further used for determining whether the first vehicle has fake-licensed behaviors according to the similarity comparison result;
the obtaining the license plate sets respectively corresponding to the arbitrary two adjacent track information comprises the following steps:
inquiring in the passing data according to the gate information and time of each track information in the first track set to find a set of vehicle license plate numbers of vehicles except the first vehicle passing through the same gate at the same time or in the same time period;
the step of comparing the similarity of license plate sets corresponding to any two adjacent track information respectively comprises the following steps:
and comparing whether intersection exists among license plate sets passing through the two bayonets or not under the condition of two adjacent times.
7. The apparatus of claim 6, wherein the processing module is specifically configured to:
if the number of times that the vehicle license number intersection between any two license plate sets corresponding to adjacent track information is zero in the first track set is larger than a preset threshold value, determining that a fake-licensed behavior exists in the first vehicle;
otherwise, determining that the fake-licensed action does not exist.
8. The apparatus according to claim 6 or 7, wherein,
the processing module is further configured to: obtaining a passing set according to passing data acquired by a plurality of bayonets arranged in a preset area, wherein the passing data comprises a vehicle number and time of passing through each bayonet, and the passing set comprises bayonet information of the plurality of bayonets and passing data corresponding to each bayonet;
The acquisition module is specifically configured to: obtaining a plurality of track information corresponding to the first vehicle license number according to the passing set and the first vehicle license number; and sequencing the plurality of track information in time sequence to obtain the first track set.
9. The apparatus of claim 8, wherein the acquisition module is further configured to:
according to the passing set, a plurality of license plate sets are obtained, each license plate set comprises a regular time, a piece of bayonet information and a vehicle license plate number of at least one vehicle, the regular time passes through a bayonet corresponding to the bayonet information, and the regular time is used for indicating a time period of the vehicle, the time of which passes through the bayonet, belongs to.
10. The apparatus of claim 6 or 7, wherein the processing module is further configured to:
comparing the time difference of any two adjacent track information with a preset interval threshold value;
if the time difference between two adjacent track information is smaller than the interval threshold value, acquiring license plate sets corresponding to any two adjacent track information respectively.
11. An electronic device, comprising: a memory and a processor;
The memory stores computer-executable instructions;
the processor executing computer-executable instructions stored in the memory causes the processor to perform the method of determining vehicle trowels as claimed in any one of claims 1 to 5.
12. A storage medium, comprising: a readable storage medium and a computer program for implementing the method of determining a vehicle fake-licensed of any one of claims 1 to 5.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017157119A1 (en) * | 2016-03-18 | 2017-09-21 | 中兴通讯股份有限公司 | Method and device for identifying abnormal behavior of vehicle |
| CN108091140A (en) * | 2016-11-23 | 2018-05-29 | 杭州海康威视数字技术股份有限公司 | A kind of method and apparatus of definite fake license plate vehicle |
| CN108230685A (en) * | 2016-12-22 | 2018-06-29 | 乐视汽车（北京）有限公司 | Deck recognition methods, Intelligent license-plate of vehicle, Intelligent license-plate of vehicle scanning means, deck judgment means and deck identifying system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI459332B (en) * | 2012-05-15 | 2014-11-01 | Ind Tech Res Inst | Method and system for integrating multiple camera images to track vehicle |
-
2019
- 2019-07-31 CN CN201910703054.7A patent/CN111368868B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017157119A1 (en) * | 2016-03-18 | 2017-09-21 | 中兴通讯股份有限公司 | Method and device for identifying abnormal behavior of vehicle |
| CN108091140A (en) * | 2016-11-23 | 2018-05-29 | 杭州海康威视数字技术股份有限公司 | A kind of method and apparatus of definite fake license plate vehicle |
| CN108230685A (en) * | 2016-12-22 | 2018-06-29 | 乐视汽车（北京）有限公司 | Deck recognition methods, Intelligent license-plate of vehicle, Intelligent license-plate of vehicle scanning means, deck judgment means and deck identifying system |
Non-Patent Citations (3)
| Title |
|---|
| Li Y，et al..An approach to instantly detecting fake plates based on large-scale ANPR data.《2015 12th Wb Information System and Application Conference(WISA)》.2015,第287-292页. * |
| 汤鑫.融合数据挖掘技术与车辆轨迹时空特征分析的套牌车识别方法.《万方数据》.2018,全文. * |
| 赵卓峰 ; 卢帅 ; 韩燕波 ; .基于海量车牌识别数据的相似轨迹查询方法.清华大学学报(自然科学版).2017,(第02期),全文. * |
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