CN112330967A - Identification method, device and system of fake-licensed vehicle and computer equipment - Google Patents
Identification method, device and system of fake-licensed vehicle and computer equipment Download PDFInfo
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- CN112330967A CN112330967A CN202011252379.7A CN202011252379A CN112330967A CN 112330967 A CN112330967 A CN 112330967A CN 202011252379 A CN202011252379 A CN 202011252379A CN 112330967 A CN112330967 A CN 112330967A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
Abstract
The application relates to a method, a device, a system and computer equipment for identifying a fake-licensed vehicle, wherein the method for identifying the fake-licensed vehicle comprises the following steps: the method comprises the steps that a vehicle characteristic information base and vehicle characteristics of a license plate are obtained, wherein the vehicle characteristic information base stores reference vehicle characteristics of the license plate, and the reference vehicle characteristics are generated through secondary analysis after feature recognition is carried out on collected vehicle pictures; respectively comparing the vehicle characteristics of the license plate with corresponding reference vehicle characteristics, and determining different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics, wherein the vehicle characteristics of the license plate at least comprise two items; whether the vehicle corresponding to the vehicle characteristics is the fake-licensed vehicle or not is judged according to the proportion, the problem that the fake-licensed vehicle identification precision is low in a mode of carrying out speed calculation based on the space-time information of the vehicle to identify the fake-licensed vehicle through the speed in the related technology is solved, and the identification precision of the fake-licensed vehicle is improved.
Description
Technical Field
The application relates to the technical field of image processing, in particular to a fake-licensed vehicle identification method, device, system and computer equipment.
Background
The fake-licensed vehicle is used for mounting fake license plates on vehicles or applying license plates of other vehicles. The fake-license behavior of the vehicle has negative effects on the aspects of public traffic management, public safety maintenance and the like. The detection of the fake-licensed vehicle can find the fake-licensed vehicle so as to maintain the order of public transportation.
In the related technology, the commonly used fake-licensed vehicle detection is to calculate the speed according to the time-space information of the vehicle, so as to identify the fake-licensed vehicle through the speed, for example, calculate the speed of the vehicle with the same license plate passing through two front and rear bayonet capturing devices, if the speed is greater than a preset threshold, it is proved that the license plate may appear in different areas at the same time, and the possibility of fake-licensed exists.
At present, aiming at the problem that in the related technology, the fake-licensed car identification precision is low in a mode of carrying out speed calculation based on the space-time information of the vehicle and identifying the fake-licensed car through the speed, and an effective solution is not provided.
Disclosure of Invention
The embodiment of the application provides a fake-licensed vehicle identification method, a fake-licensed vehicle identification device, a fake-licensed vehicle identification system and computer equipment, and aims to at least solve the problem that in the related technology, the fake-licensed vehicle identification precision is low in a mode of carrying out speed calculation based on space-time information of vehicles so as to identify fake-licensed vehicles through speed.
In a first aspect, an embodiment of the present application provides a method for identifying a fake-licensed vehicle, where the method includes:
acquiring a vehicle characteristic information base and vehicle characteristics of a license plate, wherein the vehicle characteristic information base stores reference vehicle characteristics of the license plate, and the reference vehicle characteristics are generated by secondary analysis after feature recognition is carried out on a collected vehicle picture;
respectively comparing the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics, and determining different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics, wherein the vehicle characteristics of the license plate at least comprise two items;
and judging whether the vehicle corresponding to the vehicle characteristics is a fake plate vehicle or not according to the proportion.
In some of these embodiments, obtaining vehicle characteristics of a license plate comprises:
acquiring a captured vehicle picture;
carrying out feature recognition on the vehicle picture, and determining a vehicle feature table based on the vehicle picture;
and determining the vehicle characteristics of the license plate according to the vehicle characteristic table of the vehicle picture.
In some embodiments, before performing feature recognition on the vehicle picture and determining the vehicle feature table based on the vehicle picture, the method further includes:
and according to the preset screening condition, deleting the vehicle pictures which do not accord with the screening condition from the captured vehicle pictures.
In some of these embodiments, the screening conditions include at least one of:
whether the time period of the vehicle picture snapshot accords with a preset time period, whether the vehicle picture accords with a picture of a preset vehicle part, whether the annual inspection standard quantity of the vehicle in the vehicle picture is greater than a preset annual inspection standard threshold value and whether the safety belt quantity in the vehicle picture is greater than a preset safety belt threshold value.
In some embodiments, determining the vehicle characteristics of the license plate according to the vehicle characteristic table of the vehicle picture includes:
deleting the vehicle features with the recognition confidence coefficient smaller than a preset threshold value from the vehicle feature table based on the vehicle picture;
deleting the vehicle features of which the number of times of occurrence of the license plate is less than a preset value in unit time from the vehicle feature table for deleting the vehicle features of which the recognition confidence coefficient is less than a preset threshold value;
and determining the vehicle characteristics of the license plate from the vehicle characteristic table for deleting the vehicle characteristics of which the number of times of occurrence of the license plate in unit time is less than a preset value.
In some of these embodiments, the vehicle characteristics include at least a vehicle type and a vehicle brand, and the reference vehicle characteristics include at least a reference vehicle type and a reference vehicle brand;
if the vehicle characteristics at least comprise a vehicle type and a vehicle brand, and the reference vehicle characteristics at least comprise a reference vehicle type and a reference vehicle brand, respectively comparing the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics, and determining the different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics comprises:
comparing the vehicle type of the license plate with the reference vehicle type, determining a first proportion of the vehicle characteristic different from the reference vehicle characteristic, and comparing the vehicle brand of the license plate with the reference vehicle brand, determining a second proportion of the vehicle characteristic different from the reference vehicle characteristic;
and taking the sum of the first proportion and the second proportion as the proportion of the vehicle characteristic of the license plate different from the reference vehicle characteristic.
In a second aspect, an embodiment of the present application provides an identification device for a fake-licensed vehicle, the identification device including: the device comprises an acquisition module, a comparison module and a generation module;
the acquisition module is used for acquiring a vehicle characteristic information base and vehicle characteristics of a license plate, wherein the vehicle characteristic information base stores reference vehicle characteristics of the license plate, and the reference vehicle characteristics are generated by secondary analysis after feature recognition is carried out on an acquired vehicle picture;
the comparison module is used for respectively comparing the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics and determining the different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics, wherein the vehicle characteristics of the license plate at least comprise two items;
and the generating module is used for judging whether the vehicle corresponding to the vehicle characteristics is a fake-licensed vehicle or not according to the proportion.
In a third aspect, an embodiment of the present application provides an identification system for a fake-licensed vehicle, where the identification system includes: a camera and a processor;
the camera is used for acquiring captured vehicle pictures and sending the vehicle pictures to the processor;
the camera is used for capturing a vehicle picture and sending the vehicle picture to the processor;
the processor is used for acquiring a vehicle characteristic information base and determining the vehicle characteristics of a license plate according to the vehicle picture, wherein the vehicle characteristic information base stores the reference vehicle characteristics of the license plate, and the reference vehicle characteristics are generated by performing secondary analysis after the characteristic recognition on the vehicle picture acquired in advance;
the processor is further configured to compare the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics, determine a different ratio between the vehicle characteristics of the license plate and the reference vehicle characteristics, and determine whether the vehicle corresponding to the vehicle characteristics is a fake-licensed vehicle according to the ratio, where the vehicle characteristics of the license plate include at least two items.
In a fourth aspect, the present application provides a computer device, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the method for identifying a fake-licensed vehicle according to the first aspect.
In a fifth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the method for identifying a fake-licensed vehicle as described in the first aspect above.
Compared with the related art, the identification method, the identification device, the identification system and the computer equipment of the fake-licensed vehicle provided by the embodiment of the application acquire a vehicle characteristic information base and vehicle characteristics of a license plate, wherein the vehicle characteristic information base stores reference vehicle characteristics of the license plate, and the reference vehicle characteristics are generated by secondary analysis after the characteristic identification is carried out on the acquired vehicle picture; respectively comparing the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics, and determining different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics, wherein the vehicle characteristics of the license plate at least comprise two items; and judging whether the vehicle corresponding to the vehicle characteristics is a fake-licensed vehicle or not according to the proportion, solving the problem of low fake-licensed vehicle identification precision in a mode of carrying out speed calculation based on the space-time information of the vehicle to identify the fake-licensed vehicle through speed in the related technology, and improving the identification precision of the fake-licensed vehicle.
The details of one or more embodiments of the application are set forth in the accompanying drawings and the description below to provide a more thorough understanding of the application.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flow chart of a method of identifying a fake-licensed vehicle according to an embodiment of the present application;
FIG. 2 is a first flowchart of a method for obtaining vehicle characteristics of a license plate according to an embodiment of the present disclosure;
FIG. 3 is a flowchart of a second method for obtaining vehicle characteristics of a license plate according to an embodiment of the present disclosure;
FIG. 4 is a flowchart of a third method for obtaining vehicle characteristics of a license plate according to an embodiment of the present application;
FIG. 5 is a second flowchart of a method of identifying a fake-licensed vehicle according to an embodiment of the present application;
FIG. 6 is a block diagram of an identification device of a fake-licensed vehicle according to an embodiment of the present application;
FIG. 7 is a block diagram of an identification system for a fake-licensed vehicle according to an embodiment of the present application;
fig. 8 is a schematic diagram of an internal structure of a computer device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of ordinary skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms referred to herein shall have the ordinary meaning as understood by those of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar words throughout this application are not to be construed as limiting in number, and may refer to the singular or the plural. The present application is directed to the use of the terms "including," "comprising," "having," and any variations thereof, which are intended to cover non-exclusive inclusions; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Reference to "connected," "coupled," and the like in this application is not intended to be limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. Reference herein to "a plurality" means greater than or equal to two. "and/or" describes an association relationship of associated objects, meaning that three relationships may exist, for example, "A and/or B" may mean: a exists alone, A and B exist simultaneously, and B exists alone. Reference herein to the terms "first," "second," "third," and the like, are merely to distinguish similar objects and do not denote a particular ordering for the objects.
The identification method of the fake-licensed vehicle can be applied to a camera for managing traffic order. With the restrictive growth of high security of motor vehicles, especially the stricter index control and prohibition measures for passenger cars, the more prominent illegal behaviors such as counterfeiting, changing and moving motor vehicle license plates, and the like, the fake license plate behaviors seriously affect the normal traffic order and the normal vehicle owner interests, and the fake license plate detection is needed to identify and capture the fake license plates.
In the related technology, the commonly used fake-licensed vehicle detection is to calculate the speed according to the time-space information of the vehicle, so as to identify the fake-licensed vehicle through the speed, for example, calculate the speed of the vehicle with the same license plate passing through two front and rear bayonet capturing devices, if the speed is greater than a preset threshold, it is proved that the license plate may appear in different areas at the same time, and the possibility of fake-licensed exists. According to the fake-licensed vehicle identification method, the vehicle characteristic information base and the vehicle characteristics of the license plate are obtained, the vehicle characteristics of the license plate are compared with the corresponding reference vehicle characteristics respectively, the different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics are determined, whether the vehicle corresponding to the vehicle characteristics is the fake-licensed vehicle or not is judged according to the proportions, the problem that the identification precision of the fake-licensed vehicle is low due to the fact that speed calculation is carried out based on the space-time information of the vehicle in the related technology so that the fake-licensed vehicle can be identified through the speed is solved, and the identification precision of the fake-licensed vehicle is improved.
The embodiment provides a method for identifying a fake-licensed vehicle, and fig. 1 is a flowchart of a method for identifying a fake-licensed vehicle according to an embodiment of the application, and as shown in fig. 1, the flowchart includes the following steps:
step S101, a vehicle characteristic information base and vehicle characteristics of a license plate are obtained, wherein the vehicle characteristic information base stores reference vehicle characteristics of the license plate, and the reference vehicle characteristics are generated by secondary analysis after feature recognition is carried out on a collected vehicle picture;
it should be noted that the reference vehicle feature of the license plate stored in the vehicle feature information base may be a preset period of time, the vehicle feature of the captured vehicle is counted during the period of time, and finally, secondary analysis is performed according to the counted vehicle feature, the vehicle feature of the same license plate is counted based on the license plate, and the vehicle feature is used as the reference vehicle feature of the license plate, for example, based on a deep learning vehicle secondary analysis algorithm, intelligent analysis of real-time/historical passing images is achieved, vehicle attributes such as a vehicle brand, a license plate, a vehicle body color and the like, and driver attributes such as whether to fasten a seat belt, whether to make a call or not are analyzed, and the vehicle attribute is used as the vehicle feature.
Step S102, comparing the vehicle characteristics of the license plate with corresponding reference vehicle characteristics respectively, and determining different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics, wherein the vehicle characteristics of the license plate at least comprise two items;
for example, recording the vehicle characteristics of a certain license plate in a week when the license plate appears each time, comparing the recorded vehicle characteristics in the week with the reference vehicle characteristics in the vehicle characteristic information base, and counting the different proportions of the vehicle characteristics of the license plate in the week and the reference vehicle characteristics; specifically, a certain license plate a appears 6 times in a week, and then the vehicle type of the license plate a in the week records 6 times, if the reference vehicle type of the license plate a recorded in the vehicle characteristic information base is a normal-class vehicle type, and the vehicle types of the license plate a in the week record 6 times which are all high-class cars, the number of times that the vehicle characteristic of the license plate a in the week is different from the reference vehicle characteristic is 6, and the proportion that the vehicle characteristic is different from the reference vehicle characteristic is 100%; it should be further noted that the vehicle characteristics of the license plate can be any two of the type of vehicle, the brand of vehicle, the number of annual labels, and the like.
Step S103, judging whether the vehicle corresponding to the vehicle characteristics is a fake plate vehicle or not according to the proportion;
for example, the ratio of the vehicle characteristics of the license plate to the reference vehicle characteristics may be a preset threshold, and once the ratio is greater than the preset threshold, the vehicle carrying the license plate is the fake-licensed vehicle.
Through the steps S101 to S103, a vehicle characteristic information base storing the reference vehicle characteristics of the license plate and the vehicle characteristics of the license plate are obtained, the reference vehicle characteristics in the vehicle characteristic information base are generated through secondary analysis after feature recognition is carried out on the collected vehicle pictures, the vehicle characteristics of the license plate are compared with the reference vehicle characteristics, the different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics are determined, the vehicle corresponding to the vehicle characteristics is determined to be a fake-licensed vehicle according to the proportions, the problem that the fake-licensed vehicle recognition accuracy is low due to the fact that speed calculation is carried out based on the space-time information of the vehicle in the related art so that the fake-licensed vehicle is recognized through the speed is solved, and the recognition accuracy of the fake-licensed vehicle is improved.
In some embodiments, fig. 2 is a flowchart of a first method for acquiring vehicle characteristics of a license plate according to an embodiment of the present application, and as shown in fig. 2, acquiring the vehicle characteristics of the license plate includes the following steps:
step S201, obtaining a captured vehicle picture;
step S202, carrying out feature recognition on the vehicle picture, and determining a vehicle feature list based on the vehicle picture;
for example, a captured vehicle picture within a week is obtained, vehicle features in the captured vehicle picture are preliminarily identified based on an identification algorithm or a feature analysis algorithm, secondary analysis is performed after the primary identification is performed to further identify the vehicle features in the vehicle picture, such as a license plate, a vehicle type, a vehicle brand, an annual inspection standard number, whether to carry a seat belt, an identification confidence coefficient and the like, and a vehicle feature table is established.
Step S203, determining the vehicle characteristics of the license plate according to the vehicle characteristic table of the vehicle picture;
for example, based on a vehicle feature table of captured vehicle pictures, the vehicle features corresponding to each license plate in a week are counted with the identified license plate as a reference.
Through the steps S201 to S203, the captured vehicle picture is subjected to feature recognition to determine a vehicle feature list based on the vehicle picture, the vehicle features of each license plate are determined based on the vehicle feature list of the vehicle picture, and the recognition accuracy of the vehicle license plate number and the vehicle features can be improved through analyzing and counting the captured picture of the vehicle.
In some embodiments, fig. 3 is a flowchart of a second method for obtaining vehicle features of a license plate according to an embodiment of the present application, and as shown in fig. 3, before performing feature recognition on a vehicle picture and determining a vehicle feature table based on the vehicle picture, the method further includes the following steps:
step S301, according to preset screening conditions, vehicle pictures which do not accord with the screening conditions are deleted from the captured vehicle pictures;
the vehicle pictures can be screened according to the captured time periods, for example, the vehicle pictures captured in the time periods from eight am to eighteen pm every day are only taken in consideration of the condition of insufficient light, so that the captured vehicle pictures are prevented from being influenced by insufficient light, and the quality of the captured vehicle pictures is improved.
In some of these embodiments, the screening conditions include at least one of:
whether the time period of the vehicle picture snap-shot accords with a preset time period, whether the vehicle picture accords with a picture of a preset vehicle part, whether the annual inspection standard quantity of the vehicle in the vehicle picture is greater than a preset annual inspection standard threshold value and whether the safety belt quantity in the vehicle picture is greater than a preset safety belt threshold value; and the screening condition may be set to include the above four items in consideration of the quality of the vehicle picture.
For example, the preset time period may be eight am to eighteen pm every day, and only the pictures of the vehicle captured in the eight am to eighteen pm every day are taken; the preset picture of the vehicle part can be a picture of a vehicle head, namely, the picture of the vehicle head is taken and the picture of the vehicle tail is discarded, considering that the picture of the vehicle tail is not accurately identified, the vehicle type and the vehicle brand are wrongly identified; only pictures with the annual inspection standard number larger than a preset annual inspection standard threshold value 0 in the vehicle pictures are taken; and only pictures with the number of the safety belts being larger than a preset safety belt threshold value 0 in the pictures of the vehicles are taken.
In some embodiments, fig. 4 is a flowchart of a third method for obtaining vehicle characteristics of a license plate according to an embodiment of the present application, and as shown in fig. 4, determining the vehicle characteristics of the license plate according to a vehicle characteristic table based on a vehicle picture includes the following steps:
step S401, deleting the vehicle features of which the recognition confidence degrees are smaller than a preset threshold value from a vehicle feature table based on the vehicle picture;
step S402, deleting the vehicle features of which the number of times of occurrence of the license plate in unit time is less than a preset value from the vehicle feature table of which the recognition confidence coefficient is less than a preset threshold value is deleted;
for example, considering that the recognition algorithm or the feature analysis algorithm of the picture is influenced by the picture snapshot quality and has the risk of feature extraction errors, the vehicle features which appear three times or more in one day of each license plate are only taken, and the reliability of the vehicle features in the vehicle feature list is further improved.
Step S403, determining the vehicle characteristics of the license plate from the vehicle characteristic table for deleting the vehicle characteristics of which the number of times of occurrence of the license plate in unit time is less than a preset value.
Through the steps S401 to S403, based on the vehicle feature table of the vehicle picture, the vehicle features with the recognition confidence smaller than the preset threshold and the vehicle features with the license plate occurrence frequency smaller than the preset value are deleted, so that the reliability of the vehicle features in the vehicle feature table is improved.
In some of these embodiments, the vehicle features include at least a vehicle type and a vehicle brand, and the reference vehicle features include at least a reference vehicle type and a reference vehicle brand; fig. 5 is a second flowchart of a method for identifying a fake-licensed vehicle according to an embodiment of the present application, where as shown in fig. 5, if the vehicle characteristics at least include a vehicle type and a vehicle brand, and the reference vehicle characteristics at least include a reference vehicle type and a reference vehicle brand, the comparing the vehicle characteristics of the license plate with the reference vehicle characteristics of the license plate in the vehicle characteristic information base, and determining a ratio of the vehicle characteristics of the license plate to the reference vehicle characteristics includes the following steps:
step S501, comparing the vehicle type of the license plate with a reference vehicle type, determining a first proportion of different vehicle characteristics from the reference vehicle characteristics, and comparing the vehicle brand of the license plate with the reference vehicle brand, determining a second proportion of different vehicle characteristics from the reference vehicle characteristics;
step S502, taking the sum of the first proportion and the second proportion as the proportion of the vehicle characteristics of the license plate different from the reference vehicle characteristics;
for example, if a certain license plate a appears 6 times in a week, and the vehicle type of the license plate a in the week records 6 times, and the vehicle brand records 6 times, the reference vehicle type of the license plate a recorded in the vehicle feature information base is a normal-class vehicle type, and 6 times of recording the vehicle types of the license plate A in a week are all high-class cars, the times of the difference between the vehicle characteristics of the license plate A in a week and the reference vehicle characteristics is 6, the proportion of the difference between the vehicle types and the reference vehicle types is 100%, if the reference vehicle brand of the license plate A recorded in the vehicle characteristic information base is a domestic brand, and 6 times of record of the vehicle brand of the license plate A in one week are joint-fund brands, the number of times that the vehicle brand of the license plate A in one week is different from the reference vehicle brand is 6, the ratio of the vehicle brand to the reference vehicle brand is 100 percent, the different proportion of the vehicle characteristics of the license plate in one week to the reference vehicle characteristics is 200 percent;
it should be noted that the vehicle type of the license plate may be compared with the reference vehicle type, the number of times that the vehicle type is different from the reference vehicle type is determined, and integral conversion is performed according to the number of times, wherein the larger the different number of times, the larger the integral is; similarly, the vehicle brand of the license plate is compared with the reference vehicle brand, the times that the vehicle brand is different from the reference vehicle brand are determined, integration conversion is carried out according to the times, the total integral that the vehicle characteristic is different from the reference vehicle characteristic is the sum of two integrals, further, the total integral is compared with the threshold integral, and if the total integral is larger than the threshold integral, the vehicle is a fake-licensed vehicle.
Through the steps S501 to S502, different vehicle characteristics of the license plate are compared with corresponding reference vehicle characteristics to determine a first proportion and a second proportion corresponding to the different vehicle characteristics, and the sum of the first proportion and the second proportion is used as the different proportion of the vehicle characteristics of the license plate and the reference vehicle characteristics, so that the accuracy of the counted times is improved.
In some embodiments, after determining that the vehicle corresponding to the vehicle characteristic is the fake-licensed vehicle according to the number of times, considering that a vehicle owner changes the vehicle within a short time in reality, the fake-licensed vehicle is also recognized in this case, so the generated fake-licensed vehicle result is compared with the vehicle archive table, a license plate which commonly appears in the archive table and the fake-licensed vehicle result is found out, and if no vehicle change record exists in the archive table, the vehicle corresponding to the vehicle characteristic is determined to be the fake-licensed vehicle according to the proportion.
It should be noted that the steps illustrated in the above-described flow diagrams or in the flow diagrams of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flow diagrams, in some cases, the steps illustrated or described may be performed in an order different than here.
The present embodiment further provides an identification apparatus for a fake-licensed vehicle, which is used to implement the foregoing embodiments and preferred embodiments, and the description of the devices is omitted. As used hereinafter, the terms "module," "unit," "subunit," and the like may implement a combination of software and/or hardware for a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
In some embodiments, fig. 6 is a block diagram of an identification apparatus of a fake-licensed vehicle according to an embodiment of the present application, and as shown in fig. 6, the identification apparatus of the fake-licensed vehicle includes: an acquisition module 61, a comparison module 62 and a generation module 63;
the acquiring module 61 is configured to acquire a vehicle characteristic information base and vehicle characteristics of a license plate, where the vehicle characteristic information base stores reference vehicle characteristics of the license plate, and the reference vehicle characteristics are generated by performing secondary analysis after feature recognition on an acquired vehicle picture;
the comparison module 62 is configured to compare the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics, and determine different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics, where the vehicle characteristics of the license plate include at least two items;
and the generating module 63 is configured to determine whether the vehicle corresponding to the vehicle characteristic is a fake-licensed vehicle according to the ratio.
In some embodiments, the obtaining module 61, the comparing module 62, and the generating module 63 are further configured to implement steps in the identification method for the fake-licensed vehicle provided in each of the embodiments, and details are not repeated here.
The above modules may be functional modules or program modules, and may be implemented by software or hardware. For a module implemented by hardware, the modules may be located in the same processor; or the modules can be respectively positioned in different processors in any combination.
In some embodiments, fig. 7 is a block diagram of an identification system of a fake-licensed vehicle according to an embodiment of the present application, and as shown in fig. 7, the identification system of the fake-licensed vehicle includes: a camera 71 and a processor 72;
the camera 71 is used for capturing a vehicle picture and sending the vehicle picture to the processor 72;
the processor 72 is configured to obtain a vehicle feature information base, and is further configured to determine a vehicle feature of a license plate according to a vehicle picture, where the vehicle feature information base stores a reference vehicle feature of the license plate, and the reference vehicle feature is generated by performing secondary analysis after performing feature recognition on a vehicle picture acquired in advance;
the processor 72 is further configured to compare the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics, determine a different ratio between the vehicle characteristics of the license plate and the reference vehicle characteristics, and determine whether the vehicle corresponding to the vehicle characteristics is a fake-licensed vehicle according to the ratio, where the vehicle characteristics of the license plate include at least two items.
In some embodiments, the processor 72 is further configured to implement the steps in the method for identifying a fake-licensed vehicle provided in each of the above embodiments, which are not described herein again.
In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of identifying a fake-licensed vehicle. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
In an embodiment, fig. 8 is a schematic diagram of an internal structure of a computer device according to an embodiment of the present application, and as shown in fig. 8, there is provided a computer device, which may be a server, and its internal structure diagram may be as shown in fig. 8. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of identifying a fake-licensed vehicle.
Those skilled in the art will appreciate that the architecture shown in fig. 8 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the steps of the identification method for a fake-licensed vehicle provided in the above embodiments are realized.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the steps in the method for identifying a fake-licensed vehicle provided by the above embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of identifying a fake-licensed vehicle, the method comprising:
acquiring a vehicle characteristic information base and vehicle characteristics of a license plate, wherein the vehicle characteristic information base stores reference vehicle characteristics of the license plate, and the reference vehicle characteristics are generated by secondary analysis after feature recognition is carried out on a collected vehicle picture;
respectively comparing the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics, and determining different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics, wherein the vehicle characteristics of the license plate at least comprise two items;
and judging whether the vehicle corresponding to the vehicle characteristics is a fake plate vehicle or not according to the proportion.
2. The method of claim 1, wherein obtaining the vehicle characteristics of the license plate comprises:
acquiring a captured vehicle picture;
carrying out feature recognition on the vehicle picture, and determining a vehicle feature table based on the vehicle picture;
and determining the vehicle characteristics of the license plate according to the vehicle characteristic table of the vehicle picture.
3. The method of identifying a fake-licensed vehicle of claim 2, wherein before the vehicle picture is subjected to feature recognition and a vehicle feature table based on the vehicle picture is determined, the method further comprises:
and according to the preset screening condition, deleting the vehicle pictures which do not accord with the screening condition from the captured vehicle pictures.
4. A method of identifying a fake-licensed vehicle according to claim 3, wherein the screening condition includes at least one of:
whether the time period of the vehicle picture snapshot accords with a preset time period, whether the vehicle picture accords with a picture of a preset vehicle part, whether the annual inspection standard quantity of the vehicle in the vehicle picture is greater than a preset annual inspection standard threshold value and whether the safety belt quantity in the vehicle picture is greater than a preset safety belt threshold value.
5. The method of claim 2, wherein determining the vehicle characteristics of the license plate from the vehicle characteristics table of the vehicle picture comprises:
deleting the vehicle features with the recognition confidence coefficient smaller than a preset threshold value from the vehicle feature table based on the vehicle picture;
deleting the vehicle features of which the number of times of occurrence of the license plate is less than a preset value in unit time from the vehicle feature table for deleting the vehicle features of which the recognition confidence coefficient is less than a preset threshold value;
and determining the vehicle characteristics of the license plate from the vehicle characteristic table for deleting the vehicle characteristics of which the number of times of occurrence of the license plate in unit time is less than a preset value.
6. The method of identifying a fake-licensed vehicle of claim 1, wherein the vehicle characteristics include at least a vehicle type and a vehicle brand, and the reference vehicle characteristics include at least a reference vehicle type and a reference vehicle brand;
if the vehicle characteristics at least comprise a vehicle type and a vehicle brand, and the reference vehicle characteristics at least comprise a reference vehicle type and a reference vehicle brand, respectively comparing the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics, and determining the different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics comprises:
comparing the vehicle type of the license plate with the reference vehicle type, determining a first proportion of the vehicle characteristic different from the reference vehicle characteristic, and comparing the vehicle brand of the license plate with the reference vehicle brand, determining a second proportion of the vehicle characteristic different from the reference vehicle characteristic;
and taking the sum of the first proportion and the second proportion as the proportion of the vehicle characteristic of the license plate different from the reference vehicle characteristic.
7. An identification device for a fake-licensed vehicle, the identification device comprising: the device comprises an acquisition module, a comparison module and a generation module;
the acquisition module is used for acquiring a vehicle characteristic information base and vehicle characteristics of a license plate, wherein the vehicle characteristic information base stores reference vehicle characteristics of the license plate, and the reference vehicle characteristics are generated by secondary analysis after feature recognition is carried out on an acquired vehicle picture;
the comparison module is used for respectively comparing the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics and determining the different proportions of the vehicle characteristics of the license plate and the reference vehicle characteristics, wherein the vehicle characteristics of the license plate at least comprise two items;
and the generating module is used for judging whether the vehicle corresponding to the vehicle characteristics is a fake-licensed vehicle or not according to the proportion.
8. An identification system for a fake-licensed vehicle, the identification system comprising: a camera and a processor;
the camera is used for capturing a vehicle picture and sending the vehicle picture to the processor;
the processor is used for acquiring a vehicle characteristic information base and determining the vehicle characteristics of a license plate according to the vehicle picture, wherein the vehicle characteristic information base stores the reference vehicle characteristics of the license plate, and the reference vehicle characteristics are generated by performing secondary analysis after the characteristic recognition on the vehicle picture acquired in advance;
the processor is further configured to compare the vehicle characteristics of the license plate with the corresponding reference vehicle characteristics, determine a different ratio between the vehicle characteristics of the license plate and the reference vehicle characteristics, and determine whether the vehicle corresponding to the vehicle characteristics is a fake-licensed vehicle according to the ratio, where the vehicle characteristics of the license plate include at least two items.
9. A computer device comprising a memory and a processor, wherein the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the method of identifying a fake-licensed vehicle of any one of claims 1 to 6.
10. A computer-readable storage medium, in which a computer program is stored, wherein the computer program is arranged to carry out the method of identifying a fake-licensed vehicle of any one of claims 1 to 6 when executed.
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