CN112614347B

CN112614347B - Fake plate detection method and device, computer equipment and storage medium

Info

Publication number: CN112614347B
Application number: CN202011531091.3A
Authority: CN
Inventors: 邱明; 黄伟
Original assignee: Hangzhou Hikvision System Technology Co Ltd
Current assignee: Hangzhou Hikvision System Technology Co Ltd
Priority date: 2020-12-22
Filing date: 2020-12-22
Publication date: 2022-03-15
Anticipated expiration: 2040-12-22
Also published as: CN112614347A

Abstract

The application provides a fake plate detection method and device, computer equipment and a storage medium, which can effectively improve the fake plate detection accuracy. The method comprises the following steps: acquiring the snapshot information of drivers and passengers in a preset time period; the driver and passenger snapshot information includes: the driver and passenger identification, the driver and passenger snapshot time and the license plate number associated with the driver and passenger identification; determining a group to which each driver and passenger identifier belongs in the driver and passenger snapshot information of the same license plate number; the people in each group have an association relationship; acquiring the distribution of the determined groups in time according to the snapshot time of the drivers and passengers; and determining the probability that the vehicles corresponding to the same license plate number are fake-licensed vehicles according to the distribution.

Description

Fake plate detection method and device, computer equipment and storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a fake plate detection method and apparatus, a computer device, and a storage medium.

Background

In recent years, with the rapid increase of the quantity of motor vehicles in China, the number of fake-licensed vehicles is increased. The fake-licensed vehicle is a vehicle which runs on the road by forging or illegally collecting and faking other people's legal vehicle license plate and running certificate, etc. to avoid violation, hit-and-run and charge responsibility related to payment. The fake-licensed vehicles disturb the normal road traffic order, bringing about great traffic safety hidden dangers. The license plate number of the fake-licensed vehicle is the fake-licensed.

At present, a fake plate detection method based on grid monitoring is mostly adopted for fake plate detection. The method has the basic principle that all monitoring points are connected into a grid, and if a vehicle with the same license plate is shot by electronic equipment at the same time at different grid points or shot at different time points, but the time difference between two times of shooting is smaller than the shortest passing time of the two grid points, one vehicle is a fake-licensed vehicle. The method depends on the accuracy of data, such as the accuracy of the shortest passing time of two grid points, but the shortest passing time of the two grid points has timeliness, the road condition changes every moment, and the shortest passing time of the two grid points is often inaccurate due to some emergency (traffic accidents, road maintenance and the like), so that the detection result is inaccurate.

Disclosure of Invention

The application provides a fake plate detection method and device, computer equipment and a storage medium, which can effectively improve the fake plate detection accuracy.

The technical scheme of the application is as follows:

in a first aspect, the present application provides a method of fake-licensed detection, the method comprising: acquiring the snapshot information of drivers and passengers in a preset time period; the driver and passenger snapshot information includes: the driver and passenger identification, the driver and passenger snapshot time and the license plate number associated with the driver and passenger identification; determining a group to which each driver and passenger identifier belongs in the driver and passenger snapshot information of the same license plate number; the people in each group have an association relationship; acquiring the distribution of the determined groups in time according to the snapshot time of the drivers and passengers; and determining the probability that the vehicle corresponding to the same license plate number is a fake-licensed vehicle according to the distribution.

In the fake plate detection method, starting from the association relationship between drivers and passengers of vehicles corresponding to the same license plate number, people with the association relationship belong to the same group, for example, all people in the same family can belong to the same group, and friends of any person in the family can also belong to the group. According to the method and the device, based on the principle that the time distribution of the group to which the drivers and passengers of the fake-licensed vehicles belong to ride or drive the fake-licensed vehicles shows a certain rule, the probability that the vehicles corresponding to the same license plate number are the fake-licensed vehicles is determined according to the determined time distribution of the group to which the drivers and passengers of the vehicles corresponding to the same license plate number belong to ride or drive the vehicles corresponding to the same license plate number, and the time distribution of the group to which the drivers and passengers using the same license plate number belong to ride or drive the vehicles corresponding to the same license plate number is determined not to be influenced by the practical effect of space-time distance, so that the accuracy of fake-licensed detection is improved.

In a possible implementation manner, in the snap shot information of the drivers and passengers who determine the same license plate number, each driver identifies a group to which the driver belongs, including: acquiring a group member relationship; the group membership comprises a plurality of group identifications, and each group identification corresponds to a plurality of personnel identifications; determining a group to which a person identifier identical to each driver identifier belongs in the snap shot information of the drivers and passengers with the same license plate number from the group membership; for any one of the driver and passenger identifiers, establishing a group under the condition that a person identifier which is the same as the any driver and passenger identifier does not exist in the group membership; the newly created group id corresponds to any of the occupant ids.

In another possible implementation manner, the obtaining the group membership includes: acquire personnel snapshot information, personnel snapshot information includes: personnel identification, snapshot position and snapshot time; determining the association times between any two persons according to the snap shot information of the persons; the association times are the sum of the co-occurrence times of any two persons at each snapshot position; if the association times between two persons are greater than a preset threshold value, determining that the two persons belong to the same group; and determining the groups with the intersection as the same group.

In another possible implementation manner, the obtaining the distribution of the determined groups over time according to the time taken by the rider includes: counting the number of groups in each unit time period according to the snapshot time of the drivers and passengers; for each unit time period, if the number of the groups is more than 1, selecting one group as the group representative of the unit time period; if the number of the groups is equal to 1, taking the group as the group representative of the unit time period; and acquiring the distribution of the determined groups in time according to the group representation of each unit time period.

In another possible implementation manner, for each unit time period, if the number of groups is greater than 1, selecting one of the groups as the group representative of the unit time period includes: for any unit time period, if the number of groups in any unit time period is greater than 1, determining a first group which does not appear in the first m unit time periods of any unit time period in the groups in any unit time period; determining a group representative of the arbitrary unit time period from the first group; m is a positive integer; if the number of the first groups is zero, determining a second group which does not appear in the first m unit time periods in the groups in any unit time period; the group representation of the arbitrary unit time period is determined from the second group.

In another possible implementation manner, the method further includes: for the target unit time period with the number of the groups being zero in each unit time period, if the target unit time period has the previous unit time period, determining the group of the previous unit time period as the group representative of the target unit time period; and if the target unit time period is the first unit time period, determining that the preset group is the group representative of the target unit time period.

In a second aspect, a fake plate detection device is provided, which comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring driver and passenger snapshot information within a preset time period; the driver and passenger snapshot information includes: the driver and passenger identification, the driver and passenger snapshot time and the license plate number associated with the driver and passenger identification; the first determining module is used for determining a group to which each driver and passenger identifier belongs in the driver and passenger snapshot information of the same license plate number; the people in each group have an association relationship; the second acquisition module is used for acquiring the distribution of the determined groups in time according to the snapshot time of the drivers and passengers; and the second determining module is used for determining the probability that the vehicles corresponding to the same license plate number are fake-licensed vehicles according to the distribution.

Optionally, the second obtaining module is further configured to: acquiring a group member relationship; the group membership comprises a plurality of group identifications, and each group identification corresponds to a plurality of personnel identifications; the first determining module is further configured to: determining a group to which a person identifier identical to each driver identifier belongs in the snap shot information of the drivers and passengers with the same license plate number from the group membership; the fake-license detection device also comprises a newly-built module, wherein the newly-built module is used for building a group for any one of the driver identifiers under the condition that the member relationship of the group does not have the person identifier which is the same as any one of the driver identifiers; the newly-established group identification corresponds to any one driver identification.

Optionally, the second obtaining module is specifically configured to obtain the snapshot information of the person, where the snapshot information of the person includes: personnel identification, snapshot position and snapshot time; the first determining module is specifically used for determining the association times between any two persons according to the person snapshot information; the association times are the sum of the co-occurrence times of any two persons at each snapshot position; if the association times between two persons are greater than a preset threshold value, determining that the two persons belong to the same group; and determining the groups with the intersection as the same group.

Optionally, the second obtaining module is specifically configured to: determining a group representative of each unit time period according to the snapshot time of the driver and the passengers; and acquiring the distribution of the determined groups in time according to the group representation of each unit time period.

Optionally, the second determining module is further configured to: for any unit time period, if the number of the groups in any unit time period is greater than 1, determining a first group which does not appear in the first m unit time periods of the unit time period in the groups in the unit time period; if the number of the first groups is not zero, determining group representatives of the unit time period from the first groups; m is a positive integer; if the number of the first groups is zero, determining a second group which does not appear in the first m unit time periods in the groups in the unit time period; determining a group representation for the unit time period from the second group; if the number of groups in the unit time period is equal to 1, the group is determined to be a group representative of the unit time period.

Optionally, the second determining module is further configured to: and for the target unit time period with the number of the groups being zero in each unit time period, if the target unit time period has the previous unit time period, determining the group of the previous unit time period as the group representative of the target unit time period.

In a third aspect, a computer device is provided, comprising: a processor; a memory for storing processor-executable instructions. Wherein the processor is configured to execute the instructions to implement the method of fake plate detection as shown in the first aspect and any one of the possible implementations of the first aspect.

In a fourth aspect, there is provided a computer-readable storage medium having instructions that, when executed by a processor of a computer device, enable the computer device to perform a method of deck detection as set forth in the first aspect and any one of the possible implementations of the first aspect.

In a fifth aspect, a computer program product is provided, which is directly loadable into an internal memory of a computer device and contains software codes, and which, when loaded and executed by the computer device, is capable of implementing the method for detecting a fake plate as shown in the first aspect and any possible implementation manner of the first aspect.

The sixth aspect provides a chip system, which is applied to a fake plate detection device; the system-on-chip includes one or more interface circuits, and one or more processors. The interface circuit and the processor are interconnected through a line; the interface circuit is configured to receive signals from the memory of the deck detection device and send signals to the processor, the signals including computer instructions stored in the memory. When the processor executes the computer instructions, the deck detection means performs a deck detection method as provided in the first aspect and any one of its possible designs.

Any one of the fake plate detection devices, the computer device, the computer readable storage medium, the computer program product, or the chip system provided above is used to execute the corresponding method provided above, and therefore, the beneficial effects that can be achieved by the fake plate detection device can refer to the beneficial effects of the corresponding scheme in the corresponding method provided above, and are not described herein again.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the application and are not to be construed as limiting the application.

Fig. 1 is a schematic structural diagram of a fake-licensed detection system to which the technical solution provided by the present application is applied;

FIG. 2 is a schematic structural diagram of a computer device to which the technical solution provided by the embodiment of the present application is applied;

FIG. 3 is a schematic flow chart illustrating a method for detecting a fake-licensed plate according to an embodiment of the present disclosure;

FIG. 4 is a schematic diagram of a group curve of a group to which a driver or passenger using a normal license plate number belongs during a predetermined period of time in the case where a vehicle transaction is generated using a vehicle of the license plate number;

FIG. 5 is a schematic diagram of a group curve of a group of occupants using rental cars for a predetermined period of time;

FIG. 6 is a graph illustrating a group curve of a group of occupants using a fake-licensed vehicle for a predetermined period of time;

fig. 7 is a schematic structural diagram of a fake-licensed detecting device according to an embodiment of the present disclosure.

Detailed Description

In order to make the technical solutions of the present application better understood by those of ordinary skill in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.

It is noted that the terms first, second and the like in the description and in the claims of the present application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

In the embodiments of the present application, "at least one" means one or more. "plurality" means two or more.

In the embodiment of the present application, "and/or" is only one kind of association relationship describing an association object, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

The fake-licensed detection method provided by the embodiment of the application can be suitable for a fake-licensed detection system. Fig. 1 is a schematic structural diagram of a system to which the technical solution provided in the embodiment of the present application is applied. The system comprises a fake plate detection device 10-1 and a collection device 10-2. In the present application, the number of each device in the system is not limited, and two acquisition devices are illustrated as an example in fig. 1. The fake plate detection device 10-1 and each acquisition device 10-2 can be connected through a network.

The acquisition device 10-2 can be used for acquiring driver and passenger snapshot information and personnel snapshot information. Alternatively, the capture device 10-2 may be used to capture raw information that is used to capture occupant snapshot information and/or person snapshot information. In one example, the capture device 10-2 is any device for capturing images. For example: cameras, snap-shots, video cameras, and the like. The collecting device 10-2 may transmit the photographed image, the capturing time of the image, the capturing position of the image, and the like to the fake plate detecting device 10-1. The capture device 10-2 may also recognize the captured image to determine whether the image includes an image feature of a person image or an image feature of a vehicle image, and in the case where it is determined that the image includes an image feature of a person image or an image feature of a vehicle image, transmit the image, a capturing time of the image, a capturing position of the image, and the like to the fake plate detection device 10-1. In another example, the capture device 10-2 is any sensing device for capturing occupant and/or person snapshot information. For example: the acquisition device 10-2 may be a Media Access Control (MAC) code acquisition device, an International Mobile Subscriber Identity (IMSI) code acquisition device, or the like. The acquisition device 10-2 can acquire the snapshot information of the driver and the passenger according to the MAC code of the vehicle or the similar identification code which uniquely identifies the vehicle. The acquisition device 10-2 may acquire the person snapshot information of the person according to the MAC code of the mobile terminal carried by the person or an identification code similar thereto that can uniquely identify the person. The acquisition device 10-2 sends acquired driver and passenger snapshot information and/or personnel snapshot information to the fake-license detection device 10-1.

The fake plate detection device 10-1 may be used to acquire driver and/or passenger snapshot information. Wherein, the information of taking a candid photograph by the driver and the crew comprises: the time taken by the driver, the license plate number and the identification of the driver and the passenger. The personnel snapshot information includes: personnel identification, a snapshot position and personnel snapshot time of the captured person. Optionally, the fake plate detection device 10-1 may also be used to identify the image captured by the capture device 10-2.

The fake plate detection device 10-1 may be a terminal device or a server. The terminal device may be a palm computer, a notebook computer, a smart phone, a vehicle-mounted terminal, a tablet computer or a desktop computer. The server may be one server, a server cluster composed of a plurality of servers, or a cloud computing service center.

The collecting device 10-2 in the embodiment of the present application may be a collecting device in a fixed position, or may be a collecting device that moves, which is not limited in the embodiment of the present application.

The functions of the collecting device 10-2 and the fake plate detecting device 10-1 can be realized by a computer device shown in fig. 2, and as shown in fig. 2, the collecting device is a schematic structural diagram of a computer device to which the technical scheme provided by the embodiment of the present application is applied. The computer device 10 in fig. 2 includes, but is not limited to: a processor 101, a memory 102, an input unit 104, an interface unit 105, a power supply 106, and the like. Optionally, the computer device 10 further includes a camera 100, a display 104, and a positioning device 107.

The camera 100 is configured to capture an image and send the image to the processor 101. The processor 101 is a control center of the computer device, connects various parts of the entire computer device using various interfaces and lines, and performs various functions of the computer device and processes data by running or executing software programs and/or modules stored in the memory 102 and calling data stored in the memory 102, thereby monitoring the computer device as a whole. Processor 101 may include one or more processing units; optionally, the processor 101 may integrate an application processor and a modem processor, wherein the application processor mainly handles operating systems, user interfaces, application programs, and the like, and the modem processor mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 101. If the computer device 10 is the acquisition apparatus 10-2, the computer device 10 may further include a camera 100.

The memory 102 may be used to store software programs as well as various data. The memory 102 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one functional unit, and the like. Further, the memory 102 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Alternatively, the memory 102 may be a non-transitory computer readable storage medium, for example, a read-only memory (ROM), a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

The display 103 is used to display information input by the user or information provided to the user. The display 103 may include a display panel, which may be configured in the form of a Liquid Crystal Display (LCD), an organic light-emitting diode (OLED), or the like. If the computer device 10 is a deck detection apparatus 10-1, then the computer device 10 may also include a display 103.

The input unit 104 may include a Graphics Processing Unit (GPU) that processes image data of still images or videos obtained by an image capturing device (such as a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display 103. The image frames processed by the graphics processor may be stored in the memory 102 (or other storage medium).

The interface unit 105 is an interface for connecting an external device to the computer apparatus 10. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 105 may be used to receive input (e.g., data information, etc.) from an external device and transmit the received input to one or more elements within the computer apparatus 10 or may be used to transmit data between the computer apparatus 10 and an external device.

A power supply 106 (e.g., a battery) may be used to supply power to the various components, and optionally, the power supply 106 may be logically connected to the processor 101 through a power management system, so that functions such as managing charging, discharging, and power consumption are implemented through the power management system.

The positioning device 107 may be used to record the location of the captured image of the acquisition device 10-2. The positioning device may include: a Global Positioning System (GPS) device, and the like. Assuming that the computer device 10 is the acquisition apparatus 10-2, the computer device 10 may further comprise a positioning apparatus 107.

Optionally, the computer instructions in the embodiments of the present application may also be referred to as application program code or system, which is not specifically limited in the embodiments of the present application.

It should be noted that the computer device shown in fig. 2 is only an example, and does not limit the computer device to which the embodiments of the present application are applicable. In actual implementation, the computer device may include more or fewer devices or components than those shown in FIG. 2.

The embodiment of the application can be applied to traffic management scenes: the manager needs to perform fake plate detection on the vehicles running on the traffic road to maintain normal road traffic order.

The technical solutions in 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 obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

As shown in fig. 3, fig. 3 is a schematic flow chart of a method for detecting a fake-licensed card according to an embodiment of the present disclosure. The method shown in fig. 3 may be applied to the deck detection apparatus 10-1 in fig. 1, and includes the following S100 to S103:

s100: the fake plate detection device 10-1 acquires the snapshot information of the driver and the passengers within a preset time period; the driver and passenger snapshot information includes: the driver identification, the driver snapshot time, and the license plate number associated with the driver identification. The license plate number associated with the driver identifier is used for indicating that the driver represented by the driver identifier drives or takes the vehicle with the license plate number.

In one possible implementation, the fake plate detection device 10-1 receives the driver and passenger snapshot information within a preset time period sent by another device (such as the collection device 10-2 in fig. 1).

In another possible implementation manner, the fake-license detection device 10-1 may acquire a piece of driver-captured information by the following steps:

the method comprises the following steps: the fake plate detection device 10-1 receives the image sent by the acquisition device 10-2 and the snapshot time of the image.

It should be noted that the image acquired by the same vehicle at the same time may be a plurality of images or one image, and the present application is not limited thereto, and in one case, the fake plate detection device 10-1 receives different images of the same vehicle at the same time and the snapshot time of each image, which are sent by the acquisition device 10-2, where the different images respectively include the license plate number of the vehicle and the characteristics of the driver and passengers in the vehicle. In another case, the fake-license detecting device 10-1 receives the image of the vehicle sent by the collecting device 10-2, wherein the image of the vehicle comprises the license plate number of the vehicle and the characteristics of the personnel.

Step two: the fake-license detecting device 10-1 identifies the license plate number and the character characteristics in the image through a preset identification algorithm.

In one example, the fake-licensed detecting device 10-1 extracts the facial features in the image through a preset first recognition algorithm. The fake plate detection device 10-1 identifies the license plate number in the image through a preset second identification algorithm.

Step three: the fake-licensed detection device 10-1 generates a person identification for the characteristics of the identified person according to a preset identification algorithm. One person identification is used to uniquely identify one person.

Step four: the fake plate detection device 10-1 determines the license plate number recognized from the image acquired by the same vehicle at the same time, the personnel identification of the driver and the passenger at the time of the vehicle and the snapshot time of the image as a piece of driver and passenger snapshot information.

In one example, the fake plate detection device 10-1 tags the identified license plate number of the vehicle and the snapshot time of the image, and the tag is the acquired personnel identification of the driver and the passenger at the moment of the vehicle, so as to obtain a piece of driver and passenger snapshot information. Subsequently, the fake plate detection device 10-1 stores the obtained driver and passenger snapshot information into a database.

It is understood that the fake plate detection device 10-1 may acquire pieces of driver and passenger snapshot information within a preset time period through the above-described steps one to four.

In one example, the driver snapshot information obtained by the fake plate detection device 10-1 includes the driver snapshot information shown in the following table 1:

TABLE 1

The data for the row in Table 1 for information 1 is used to characterize two occupants identified as person 1 and person 2, respectively, riding or driving a vehicle having license plate number A at 12:00 am on month 11 and 25 of 2020. The explanation of the data of other rows is similar and will not be described in detail.

Alternatively, the fake plate detection device 10-1 may acquire the plurality of pieces of driver and passenger snapshot information within the preset time period through the above steps one to three, and use the plurality of pieces of driver and passenger snapshot information as the initial driver and passenger snapshot information. And acquiring the snapshot information of the driver and the passengers within a preset time period according to the initial snapshot information of the driver and the passengers.

In one possible implementation, the fake plate detection device 10-1 determines target rider snapshot information from the initial rider snapshot information; the target driver and passenger snapshot information is information that the initial driver and passenger snapshot information comprises the same license plate number and the same driver and passenger identification, and the number of the information is smaller than a preset threshold value; and deleting the target driver and passenger snapshot information from the initial driver and passenger snapshot information to obtain the driver and passenger snapshot information in a preset time period.

In another possible implementation manner, first, the fake-license detecting device 10-1 may group and aggregate the acquired initial capturing information of the drivers and passengers within a preset time period according to the license plate number of the vehicle, and then group and aggregate the capturing information of the drivers and passengers after the group aggregation according to the identifiers of the drivers and passengers, so as to obtain at least one capturing information group of the drivers and passengers. The same identification of the drivers and passengers who snapshot the information of the drivers and passengers in the same driver and passenger snapshot information group is the same, and the license plate numbers included in the driver and passenger snapshot information in the same driver and passenger snapshot information group are the same. The marks of the drivers and passengers who snapshot the information of the drivers and passengers in different driver and passenger snapshot information groups are different, or the license plate numbers included in the driver and passenger snapshot information in different driver and passenger snapshot information groups are different. Then, the fake plate detection device 10-1 acquires the driver snapshot information included in the driver snapshot information group in which the number of records of the driver snapshot information in the driver snapshot information group is greater than or equal to a preset threshold, and the acquired driver snapshot information is the driver snapshot information in a preset time period.

The two possible implementation manners of obtaining the snap shot information of the driver and the passenger within the preset time period according to the initial snap shot information of the driver and the passenger can remove noise data in the initial snap shot information of the driver and the passenger, so that the snap shot information of the driver and the passenger within the preset time period is obtained.

Based on the example of table 1, the fake-license detecting device 10-1 performs grouping and aggregation on the acquired snapshot information of the driver and the passenger according to the license plate number of the vehicle, and performs grouping and aggregation on the snapshot information of the driver and the passenger after grouping and aggregation according to the identification of the driver and the passenger to obtain a driver and passenger snapshot information group of the passenger 1, which contains information 1, information 6, information 7 and information 8; obtaining a driver and passenger snapshot information group of a person 2 containing information 1, information 3, information 4 and information 5; a driver-passenger snapshot information set containing the person 3 of the information 2 is obtained. Assuming that the preset threshold is 3, the fake plate detection device 10-1 filters the driver and passenger snapshot information set of the person 3, and obtains the driver and passenger snapshot information set of the person 1 and the driver and passenger snapshot information set of the person 2 as the driver and passenger snapshot information in the preset time period.

S101: the fake plate detection device 10-1 determines the group to which each driver and passenger belongs in the driver and passenger snapshot information of the same license plate number; the people in each group have an associative relationship.

The association relationship may be a parent-child relationship, a sibling relationship, a friendship relationship, or the like.

Specifically, the fake plate detection device 10-1 acquires a group membership relationship, and acquires a group to which a person identifier identical to the identifier of each driver and passenger belongs from the group membership relationship; and determining the acquired group as the group to which the corresponding driver and passenger identification belongs. The group membership comprises a plurality of group identifications, and each group identification corresponds to the identifications of a plurality of members; for any one of the driver identifiers, when the group membership does not have the same person identifier as the any one driver identifier, the fake plate detection device 10-1 creates a new group, and the created group identifier corresponds to the any one driver identifier.

The fake-license detection device 10-1 may acquire the group membership relationship through the following possible implementation manners:

in one possible implementation, the fake-licensed detection device 10-1 may obtain group membership imported from another device or system.

Illustratively, the fake plate detection device 10-1 acquires the group membership introduced by the staff.

In another possible implementation manner, first, the fake-licensed detecting device 10-1 obtains the person association relationship according to the data in the public database, where the person association relationship includes the correspondence between the person identifiers. Then, the fake plate detection device 10-1 obtains the group membership relationship according to the person association relationship.

In one example, the fake-licensed detecting device 10-1 obtains a photo of a family member, and recognizes the characteristics of a person corresponding to the photo through a preset recognition algorithm, and the fake-licensed detecting device 10-1 generates a person identifier for the recognized characteristics of the person according to the preset identification algorithm, and generates the same group identifier for the person identifiers of all family members in the same family, so as to obtain the group membership relationship.

In another possible implementation manner, the fake-licensed detecting device 10-1 obtains the group membership relationship by the following steps:

the method comprises the following steps: the fake plate detection device 10-1 obtains the snapshot information of the person. The personnel snapshot information comprises personnel identification, a snapshot position and personnel snapshot time.

Specifically, the fake plate detection device 10-1 receives the person snapshot information sent by the acquisition device 10-2, or the fake plate detection device 10-1 receives the image of the person sent by the acquisition device 10-2, the snapshot time of the image, and the snapshot position of the image. The fake-licensed detecting device 10-1 recognizes the characteristics of the person in the image of the person through a preset recognition algorithm, and generates a person identifier for the recognized characteristics of the person according to the preset identification algorithm. The image of the person may be an image of a person in a vehicle or an image of a pedestrian, which is not limited in the present application.

In one example, the personnel snapshot information obtained by the deck detection device 10-1 includes the data in table 2 below:

TABLE 2

In table 2, the person identifier in the person snapshot information with the person snapshot information number of 1 is person 1, the snapshot position is position a, the snapshot time of the picture of the person represented by person 1 at position a is 2020.11.3012: 00:30, and explanations of the snapshot information of the other persons are similar and will not be repeated.

Step two: the fake plate detection device 10-1 determines the association times between every two persons in the acquired person snapshot information according to the person snapshot information; the association times are the sum of the co-occurrence times of every two persons at each snapshot position, and the co-occurrence of every two persons at one snapshot position is that every two persons are snapshot at the same snapshot position within a preset time length.

Based on the example in table 2, assuming that the preset time period is 10 seconds, person 1 is used for representing person 1, and person 2 is used for representing person 2, then, in the snap shot information of the person obtained by the fake-licensed detection apparatus 10-1, the snap shot time of the picture of person 1 at position a is 2020.11.3012: 00:30, the snap shot time of the picture of person 2 at position a is 2020.11.3012: 00:35, the difference between the two snap shot times is less than 10 seconds, and the person identifiers of the two pieces of snap shot information are different, so that the fake-licensed detection apparatus 10-1 obtains one co-occurrence of person 1 and person 2. When the picture of the person 1 is captured at the position a at a capturing time of 2020.11.2518: 00:30 and the picture of the person 2 is captured at the position a at a capturing time of 2020.11.2518: 00:35, the fake-license detecting apparatus 10-1 acquires one co-occurrence of the person 1 and the person 2. The time for capturing the picture of the person 1 at the position B is 2020.11.2417: 00:35, the time for capturing the picture of the person 2 at the position B is 2020.11.2417: 00:33, and the fake-license detecting device 10-1 acquires one co-occurrence of the person 1 and the person 2. Based on the example in table 2, the number of times of association between the person 1 and the person 2 acquired by the fake-licensed detection device 10-1 is 3.

And step three, the fake plate detection device 10-1 generates group member relations according to the association times. Optionally, if the association frequency between two persons is greater than a preset threshold, the fake plate detection device 10-1 determines that the two persons belong to the same group.

For example, the deck detection device 10-1 determines the target association number, which is the association number having a value greater than or equal to a preset threshold value. The fake plate detection device 10-1 determines that two persons corresponding to the target association times belong to the same group, and generates a group membership.

Under the condition that any one of the personnel identifications of the two personnel corresponding to the target association times does not have the corresponding group identification, the fake plate detection device 10-1 classifies the two personnel into the same group, generates the group identification for the group, establishes the corresponding relationship between the personnel identifications of the two personnel and the group identification respectively, and the corresponding relationship forms the group membership relationship of the group. Under the condition that any one of the staff identifiers of the two staff corresponding to the target association times has a corresponding group identifier, the fake plate detection device 10-1 marks the corresponding group identifier as the group identifier corresponding to the other one of the two staff identifiers, and obtains the group membership of the group corresponding to the group identifier.

Based on the example in step 2, assuming that the association frequency of the person 1 and the person 2 is 10, the preset threshold is 5, and the person 1 and the person 2 do not have corresponding group identifiers, then the association frequency of the person 1 and the person 2 belongs to the target association frequency, and the fake plate detection device 10-1 may generate the group identifier 1 for both the person 1 and the person 2, so as to obtain the corresponding relationship between the person identifier and the group identifier shown in the following table 3:

TABLE 3

Personnel identification	Group identification
		Person
1	Group identifier 1
		Person 2	Group identifier 1

Optionally, the fake plate detection device 10-1 determines that a group with an intersection is the same group, and in one example, if both the first association frequency and the second association frequency belong to the target association frequency, the first person and the second person correspond to the first association frequency, and the second person and the third person correspond to the second association frequency, it is determined that the first person, the second person and the third person belong to the same group, so as to obtain a group membership relationship of the group; the group members of the group include a first person, a second person, and a third person.

It should be noted that the above various possible manners of acquiring the group membership may be used in combination or individually, and this is not limited in this application.

S102: the fake plate detection device 10-1 obtains the distribution of the determined groups in time according to the snapshot time of the drivers and passengers.

In one example, first, the deck detection device 10-1 divides a preset time period into M unit time periods, which may be one day or one hour. M is a positive integer greater than M. Then, the fake-license detecting device 10-1 determines the group representative for each unit time period based on the unit time period to which the driver and passenger snap-shot time belongs. Optionally, the fake-license detecting device 10-1 counts the number of groups in each unit time period according to the time taken by the driver and the passenger, determines a group representative in each unit time period, and obtains the time distribution of the determined group for riding or driving the vehicle corresponding to the same license plate number according to the group representative in each unit time period.

The deck detection means 10-1 determines that the group representation per unit time period includes the following cases:

in one case, for each unit time period, if the number of groups in the unit time period is greater than 1, the deck detection device 10-1 selects one group in the unit time period as the group representative of the unit time period.

Optionally, for any unit time period in which the number of groups in the unit time period is greater than 1, if the group in the unit time period includes a first group that does not appear in the first m unit time periods of the unit time period, the fake plate detection device 10-1 determines the group representation of the unit time period from the first group. m is a positive integer. It should be noted that the first group may include a plurality of groups, and in the case where the first group includes a plurality of groups, the fake-card detecting device 10-1 may arbitrarily determine one first group from the first groups as the group representative of the unit time period.

For example, assuming that the group in the unit time period includes group 1 and group 2, and the groups in the first m unit time periods of the unit time period include only group 1, the fake plate detection apparatus 10-1 determines that group 2 is the group representative of the unit time period. Therefore, on one hand, the group of the vehicles corresponding to the license plate number which is taken or driven in the preset time period can be determined as much as possible, so that the accuracy of the probability that the determined vehicles corresponding to the same license plate number are fake-licensed vehicles is improved. On the other hand, because the group distribution of the fake-licensed vehicles is likely to present the alternate characteristics, the group which does not appear in the groups in the first m unit time periods is selected as the group representative, and the alternate characteristics which represent the group distribution of the fake-licensed vehicles can be found as soon as possible.

If the number of the first groups is zero, the fake plate detection device 10-1 determines a second group which does not appear in the first m unit time periods in the group in the unit time period, and determines the group representation of the unit time period from the second group. It should be noted that the second group may include a plurality of groups, and in the case where the second group includes a plurality of groups, the fake plate detection apparatus 10-1 may arbitrarily determine one second group from the second groups as the group representative of the unit time period.

For example, assuming that m is 3, the groups in the unit time period include group 1 and group 2, the group in the first unit time period of the unit time period is group 1, the group in the second unit time period of the unit time period is group 2, and the group in the third unit time period of the unit time period is group 2, then the fake plate detection apparatus 10-1 determines that group 2 is the group representative of the unit time period. Therefore, the group distribution of the fake-licensed vehicles is likely to present the alternating characteristics, and the group which does not appear in the groups within the first m unit time periods is selected as the group representative, so that the alternating characteristics for representing the group distribution of the fake-licensed vehicles can be presented as soon as possible.

In another case, for each unit time period, if the number of groups in the unit time period is equal to 1, the fake plate detection device 10-1 takes the group as the group representative of the unit time period;

for example, assuming that the group in the unit time period includes only the group 1, the deck detection device 10-1 represents the group 1 as the group in the unit time period.

In another case, for each unit time period, if the number of groups in the unit time period is zero, if the unit time period has a previous unit time period, the fake plate detection device 10-1 determines that the group in the previous unit time period is the group representative of the unit time period. In this way, it is explained that there is no vehicle snap-shot information about the vehicle of the license plate number in the unit time period, and therefore, the group of the previous unit time period is used as the group representative of the unit time period. If the unit time period is the first unit time period (i.e. there is no previous unit time period in the unit time period), the fake plate detection device 10-1 determines the preset group as the group representative of the unit time period.

In one example, the deck detection device 10-1 determines the group representative for the first unit time period in time: and when any one of the snapshot times of the drivers and passengers in the snapshot information of the drivers and passengers is not within the first unit time period, taking the preset group as the group corresponding to the first unit time period. In the process of determining the group representative of the third unit time period, when any one of the driver snapshot times in the driver snapshot information is not within the third unit time period, the fake-licensed detecting device 10-1 takes the group representative of the second unit time period as the group representative of the third unit time period.

Based on the example of table 1, assuming that the person 1 belongs to the group α and the person 2 belongs to the group β, the unit time period into which the fake-license detecting device 10-1 is divided is one day for the license plate a. Then, 2020.11.20 is the first unit period, 2020.11.21 is the second unit period, 2020.11.22 is the third unit period, 2020.11.23 is the fourth unit period, 2020.11.24 is the fifth unit period, 2020.11.25 is the sixth unit period.

Only the person 1 rides or drives the vehicle of the license plate a in the first unit time period, the fake-license detecting device 10-1 acquires the group of the person 1 as a group α, and determines that the group representative of the first unit time period is the group α.

In the second unit time period, people 1 ride or drive the vehicle with the license plate A, and people 2 ride or drive the vehicle with the license plate A. The group of the unit period preceding the second unit period is the group α, the group in the second unit period includes the group α and the group β, and since the group β does not appear in the unit period preceding the second unit period, the fake-plate detecting device 10-1 determines that the group in the second unit period represents the group β.

Only the person 2 drives or takes the vehicle with the license plate a in the third unit time period, and the fake-license detecting device 10-1 determines that the group in the third unit time period represents the group β.

Only the person 2 rides or drives the vehicle of the license plate a in the fourth unit time period, and the fake-license detecting device 10-1 determines that the group of the fourth unit time period represents the group β.

Only the person 1 rides or drives the vehicle of the license plate a in the fifth unit time period, and the fake-license detecting device 10-1 determines that the group of the fifth unit time period represents the group α.

In the sixth unit time period, people 1 ride or drive the vehicle of the license plate A, and people 2 ride or drive the vehicle of the license plate A. Since the group representation of the unit period preceding the sixth unit period includes the group α and the group β, and the group representation of the unit period preceding the sixth unit period (i.e., the fifth unit period) is the group α, the deck detection device 10-1 determines that the group representation of the sixth unit period is the group β.

S103: the fake-licensed detection device 10-1 determines the probability that the vehicle corresponding to the same license plate number is a fake-licensed vehicle according to the distribution of the determined groups in time.

For a license plate number, in one possible implementation, the fake-license detecting device 10-1 may represent the time distribution of the group of the driver and the passenger who use the license plate number to ride or drive the vehicle corresponding to the license plate number by using a group graph. The fake-licensed detection device 10-1 inputs the group curve graph into a preset classifier model and outputs the probability that the vehicle corresponding to the license plate number is a fake-licensed vehicle.

In one example, for the driver snapshot information using the normal license plate number in the preset time period, it is assumed that the driver using the vehicle corresponding to the normal license plate number includes members of the same family and friends of any one member of the same family, and the members of the same family and the friends of any one member of the same family belong to the same group. Then, the group curve of the group to which the driver and the passenger of the vehicle corresponding to the normal license plate number belong is used as a horizontal straight line in the preset time period.

In another example, in the case where a license plate number is traded within a preset time period, the drivers who use the license plate number within the preset time period take a snapshot of information, the drivers before and after the license plate number is traded belong to different groups, and the group to which the driver who uses the license plate number for a time period after the trading time belongs to a vehicle will become another group, and in the preset time period, the group curve of the group to which the driver who uses the license plate number belongs will be a horizontal straight line before the trading and a horizontal straight line after the trading. Fig. 4 is a schematic diagram showing a group curve of a group to which a driver or passenger using a license plate number belongs during a preset time period under the condition that the license plate number generates a transaction during the preset time period. In fig. 4, the horizontal axis represents a time axis, and the vertical axis represents a numerical value for characterizing a group. In fig. 4, the group to which the driver of the vehicle corresponding to the license plate number belongs before the transaction time is 1, and the group to which the driver of the vehicle corresponding to the license plate number belongs after the transaction time is 2.

In another example, for a rider snapshot of a rental car license plate number during a predetermined period of time, the group to which the rider using the license plate number belongs is constantly changed. Therefore, the group curve of the group to which the driver using the license plate belongs fluctuates in different magnitudes. Fig. 5 is a schematic diagram illustrating a group curve of a group of occupants using the rental car for a predetermined period of time. In fig. 5, the horizontal axis represents a time axis, and the vertical axis represents a numerical value for characterizing a group. The group curve diagram of fig. 5 includes four unit time periods, and the group representative identifier of the first unit time period is 5 in the order from left to right; the group representative mark of the second unit time period is 3; the group representative flag of the third unit period is 1; the group identification of the fourth unit period is 4.

In another example, for the information snapshot of the driver using the fake-licensed vehicle, the group to which the driver using the license plate number of the fake-licensed vehicle belongs in the preset time period includes at least two groups, and the at least two groups are always changed, as shown in fig. 6, which is a graph of the group curve of the group to which the driver using the fake-licensed vehicle belongs in the preset time period. In fig. 6, the horizontal axis represents a time axis, and the vertical axis represents a numerical value for characterizing a group. In the group curve shown in fig. 6: according to the sequence from left to right, the group representation identifier of the first unit time period is 1, the group representation identifier of the second unit time period is 2, the group representation identifier of the third unit time period is 2, and the group representation identifier of the fourth unit time period is 1, and oscillations with the same amplitude are presented.

Therefore, it can be understood that, in the case where different groups are represented by different values, the group curve of the group to which the driver identifier belongs should be relatively gentle for the driver snapshot information using the normal license plate number within the preset time period, the group curve of the group to which the driver identifier belongs should oscillate with different amplitudes for the driver snapshot information using the rental vehicle within the preset time period, and the group curve of the group to which the driver identifier belongs should easily oscillate with the same amplitude for the driver snapshot information using the fake-licensed vehicle within the preset time period, so that the fake-licensed detecting apparatus 10-1 can input the group curve map into the preset classifier model to determine the probability that the vehicle corresponding to the license plate number is the fake-licensed vehicle.

The fake-licensed detection method provided by the embodiment of the application starts from the association relation between the drivers and the passengers of the vehicles corresponding to the same license plate number, determines the probability that the vehicle corresponding to one license plate number is the fake-licensed vehicle based on the principle that the time distribution of the group to which the drivers and the passengers of the fake-licensed vehicle belong take or drive the fake-licensed vehicle presents a certain rule, and determines that the time distribution of the group to which the drivers and the passengers using the same license plate number take or drive the vehicle corresponding to the same license plate number is not influenced by the actual effect of the space-time distance, so that the accuracy of fake-licensed detection is improved.

Subsequently, the fake-licensed vehicle detecting device 10-1 may send out the warning message when the probability that the vehicle corresponding to the license plate number is the fake-licensed vehicle is greater than the third threshold value. The warning information includes warning information displayed on the screen of the fake plate detection device 10-1, and prompt information (such as text message or voice message) sent to the legal owner of the license plate number or prompt information sent to the manager, so as to notify the corresponding personnel of the warning information and remind the corresponding personnel to react to maintain normal traffic order.

The scheme provided by the embodiment of the application is mainly introduced from the perspective of a method. To implement the above functions, it includes hardware structures and/or software modules for performing the respective functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the exemplary method steps described in connection with the embodiments disclosed herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiment of the present application, the fake plate detection apparatus may be divided into the functional modules according to the method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. It should be noted that, in the embodiment of the present application, the division of the module is schematic, and is only one logic function division, and there may be another division manner in actual implementation.

Fig. 7 is a schematic structural diagram of a fake-licensed detecting device according to an embodiment of the present disclosure. Referring to fig. 7, the deck detection apparatus 70 includes a first obtaining module 701, a first determining module 702, a second obtaining module 703, and a second determining module 704. Wherein: the first acquisition module 701 is used for acquiring the snapshot information of the driver and the passengers within a preset time period; the driver and passenger snapshot information includes: the driver identification, the driver snapshot time, and the license plate number associated with the driver identification. For example, in conjunction with fig. 3, the first obtaining module 701 may be configured to perform S100. The first determining module 702 is configured to determine a group to which each driver and passenger identifier belongs in the captured information of the drivers and passengers with the same license plate number; the people in each group have an associative relationship. For example, in conjunction with fig. 3, the first determining module 702 may be configured to perform S101. The second obtaining module 703 is configured to obtain, according to the snapshot time of the driver and the crew, the distribution of the determined group over time; for example, in conjunction with fig. 3, the second obtaining module 703 may be configured to execute S102. The second determining module 704 is configured to determine, according to the distribution of the determined groups over time, a probability that the vehicle corresponding to the same license plate number is a fake-licensed vehicle. For example, in conjunction with fig. 3, the second determining module 704 may be configured to perform S103.

Optionally, the second obtaining module 703 is further configured to: acquiring a group member relationship; the group membership comprises a plurality of group identifications, and each group identification corresponds to a plurality of personnel identifications; the first determining module 702 is specifically configured to: determining a group to which a person identifier identical to each driver identifier belongs in the snap shot information of the drivers and passengers with the same license plate number from the group membership; the fake-license detection device 70 further includes a newly-built module 705, configured to build a group for any one of the driver identifiers under the condition that no person identifier identical to any one of the driver identifiers exists in the group membership; the newly-established group identification corresponds to any one driver identification.

Optionally, the second obtaining module 703 is specifically configured to: acquire personnel snapshot information, personnel snapshot information includes: personnel identification, snapshot position and snapshot time; the first determining module 702 is specifically configured to: determining the association times between any two persons according to the person snapshot information; the association times are the sum of the co-occurrence times of any two persons at each snapshot position; if the association times between two persons are larger than a preset threshold value, determining that the two persons belong to the same group; and determining the groups with the intersection as the same group.

Optionally, the second obtaining module 703 is specifically configured to: determining a group representative of each unit time period according to the snapshot time of the driver and the passengers; and acquiring the distribution of the determined groups in time according to the group representation of each unit time period.

Optionally, the second determining module 704 is further configured to: for any unit time period, if the number of the groups in any unit time period is greater than 1, determining a first group which does not appear in the first m unit time periods of the unit time period in the groups in the unit time period; if the number of the first groups is not zero, determining group representatives of the unit time period from the first groups; m is a positive integer; if the number of the first groups is zero, determining a second group which does not appear in the first m unit time periods in the groups in the unit time period; determining a group representation for the unit time period from the second group; if the number of groups in the unit time period is equal to 1, the group is determined to be a group representative of the unit time period.

Optionally, the second determining module 704 is further configured to: and for the target unit time period with the number of the groups being zero in each unit time period, if the target unit time period has the previous unit time period, determining the group of the previous unit time period as the group representative of the target unit time period.

In an example, referring to fig. 2, the receiving function of the first obtaining module 701 and the receiving function of the second obtaining module 703 may be implemented by the communication interface 104 in fig. 2. The processing function of the first acquiring module 701, the processing function of the second acquiring module 703, the first determining module 702, the second determining module 704 and the new creating module 705 can all be implemented by the processor 101 in fig. 2 calling a computer program stored in the memory 103.

For the detailed description of the above alternative modes, reference is made to the foregoing method embodiments, which are not described herein again. In addition, for the explanation and the description of the beneficial effects of any one of the fake plate detection devices 70 provided above, reference may be made to the corresponding method embodiments described above, and details are not repeated.

It should be noted that the actions performed by the modules are only specific examples, and the actions actually performed by the units refer to the actions or steps mentioned in the description of the embodiment based on fig. 3.

An embodiment of the present application further provides a computer device, including: a memory and a processor; the memory is for storing a computer program, and the processor is for invoking the computer program to perform the actions or steps mentioned in any of the embodiments provided above.

Embodiments of the present application also provide a computer-readable storage medium, which stores a computer program, and when the computer program runs on a computer, the computer program causes the computer to execute the actions or steps mentioned in any of the embodiments provided above.

The embodiment of the application also provides a chip system, and the chip system is applied to computer equipment. The system-on-chip includes one or more interface circuits, and one or more processors. The interface circuit and the processor are interconnected by a line. The interface circuit is used to receive signals from the memory of the computer device and to send signals to the processor, the signals including computer instructions stored in the memory. When the processor executes the computer instructions, the computer apparatus performs the steps performed by the deck detection means in the method flow illustrated in the above-described method embodiments.

Optionally, the functions supported by the system on chip may include processing actions in the embodiment described based on fig. 3, which is not described herein again. Those skilled in the art will appreciate that all or part of the steps for implementing the above embodiments may be implemented by a program instructing the associated hardware to perform the steps. The program may be stored in a computer-readable storage medium. The above-mentioned storage medium may be a read-only memory, a random access memory, or the like. The processing unit or processor may be a central processing unit, a general purpose processor, an Application Specific Integrated Circuit (ASIC), a microprocessor (DSP), a Field Programmable Gate Array (FPGA) or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof.

The embodiments of the present application also provide a computer program product containing instructions, which when executed on a computer, cause the computer to execute any one of the methods in the above embodiments. The computer program product includes one or more computer instructions. The procedures or functions described in accordance with the embodiments of the present application are all or partially generated upon loading and execution of computer program instructions on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). Computer-readable storage media can be any available media that can be accessed by a computer or can comprise one or more data storage devices, such as servers, data centers, and the like, that can be integrated with the media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

It should be noted that the above devices for storing computer instructions or computer programs provided in the embodiments of the present application, such as, but not limited to, the above memories, computer readable storage media, communication chips, and the like, are all nonvolatile (non-volatile).

Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims

1. A method of deck detection, the method comprising:

acquiring the snapshot information of drivers and passengers in a preset time period; the occupant snapshot information includes: the license plate number is associated with the driver identifier, the driver snapshot time and the driver identifier;

determining a group to which each driver and passenger identifier belongs in the driver and passenger snapshot information of the same license plate number; the people in each group have an association relationship;

acquiring the distribution of the determined groups in time according to the snapshot time of the drivers and passengers;

determining the probability that the vehicles corresponding to the same license plate number are fake-licensed vehicles according to the distribution;

the acquiring the distribution of the determined groups in time according to the snapshot time of the driver and the passengers comprises the following steps: determining a group representative of each unit time period according to the snapshot time of the driver and passengers; acquiring the time distribution of the determined group riding or driving the vehicle corresponding to the same license plate number according to the group representation of each unit time period;

determining the probability that the vehicle corresponding to the same license plate number is a fake-licensed vehicle according to the distribution, wherein the probability comprises the following steps: and inputting a group curve graph into a preset classifier model, and outputting the probability that the vehicle corresponding to the same license plate number is a fake-licensed vehicle, wherein the group curve graph represents the time distribution of the group of the drivers and passengers using the same license plate number to ride or drive the vehicle corresponding to the same license plate number.

2. The method of claim 1, wherein determining the snap shots of occupants of the same license plate number includes identifying a group to which each occupant belongs:

acquiring a group member relationship; the group membership comprises a plurality of group identifications, and each group identification corresponds to a plurality of personnel identifications;

determining that the group to which the personnel identifier same as each driver identifier belongs in the snap shot information of the drivers with the same license plate number is the group to which each driver identifier belongs from the group membership;

for any one of the driver identifiers, under the condition that a person identifier which is the same as any one of the driver identifiers does not exist in the group membership, a group is newly established; and the group identification of the newly-built group corresponds to any one driver identification.

3. The method of claim 2, wherein the obtaining group membership comprises:

acquiring personnel snapshot information, wherein the personnel snapshot information comprises: personnel identification, snapshot position and snapshot time;

determining the association times between any two persons according to the person snapshot information; the association times are the sum of the co-occurrence times of any two persons at each snapshot position;

if the association times between two persons are larger than a preset threshold value, determining that the two persons belong to the same group;

and determining the groups with the intersection as the same group.

4. The method according to any one of claims 1-3, wherein said determining a group representation per unit time period comprises:

for any unit time period, if the number of the groups in any unit time period is greater than 1, determining a first group which does not appear in the first m unit time periods of the groups in any unit time period; if the number of the first groups is not zero, determining group representatives of any unit time period from the first groups; m is a positive integer; if the number of the first groups is zero, determining a second group which does not appear in the first m unit time periods in the groups in any unit time period; determining a group representation of said any unit time period from said second group;

if the number of the groups in any unit time period is equal to 1, the group is determined to be the group representative of the unit time period.

5. The method of claim 4, wherein determining the group representation per unit time period further comprises:

for the target unit time period in which the number of the groups in each unit time period is zero, if the target unit time period has a previous unit time period, determining that the group in the previous unit time period is a group representative of the target unit time period.

6. A fake-licensed detection device, characterized by comprising:

the first acquisition module is used for acquiring the snapshot information of the driver and the passengers within a preset time period; the occupant snapshot information includes: the license plate number is associated with the driver identifier, the driver snapshot time and the driver identifier;

the first determining module is used for determining a group to which each driver and passenger identifier belongs in the driver and passenger snapshot information of the same license plate number; the people in each group have an association relationship;

the second acquisition module is used for acquiring the distribution of the determined groups in time according to the snapshot time of the drivers and passengers;

the second determining module is used for determining the probability that the vehicles corresponding to the same license plate number are fake-licensed vehicles according to the distribution;

the second obtaining module is specifically further configured to: determining a group representative of each unit time period according to the snapshot time of the driver and passengers;

the second obtaining module is specifically further configured to: acquiring the time distribution of the determined group riding or driving the vehicle corresponding to the same license plate number according to the group representation of each unit time period;

7. The apparatus of claim 6,

the second obtaining module is further configured to: acquiring a group member relationship; the group membership comprises a plurality of group identifications, and each group identification corresponds to a plurality of personnel identifications;

the first determination module is further to: determining that the group to which the personnel identifier same as each driver identifier belongs in the snap shot information of the drivers with the same license plate number is the group to which each driver identifier belongs from the group membership;

the fake plate detection device also comprises a newly-built module, wherein the newly-built module is used for building a group for any one of the driver identifiers under the condition that the member identifier which is the same as the member identifier of any one of the drivers does not exist in the group membership; the newly established group identification corresponds to any one driver and passenger identification;

the second obtaining module is specifically configured to: acquiring personnel snapshot information, wherein the personnel snapshot information comprises: personnel identification, snapshot position and snapshot time;

the first determining module is specifically configured to: determining the association times between any two persons according to the person snapshot information; the association times are the sum of the co-occurrence times of any two persons at each snapshot position; if the association times between two persons are larger than a preset threshold value, determining that the two persons belong to the same group; determining groups with intersection as the same group;

the second determining module is specifically further configured to: for any unit time period, if the number of the groups in any unit time period is greater than 1, determining a first group which does not appear in the first m unit time periods of the groups in any unit time period; if the number of the first groups is not zero, determining group representatives of any unit time period from the first groups; m is a positive integer; if the number of the first groups is zero, determining a second group which does not appear in the first m unit time periods in the groups in any unit time period; determining a group representation of said any unit time period from said second group; if the number of the groups in any unit time period is equal to 1, determining that the group is a group representative of the unit time period;

the second determining module is specifically further configured to: for the target unit time period in which the number of the groups in each unit time period is zero, if the target unit time period has a previous unit time period, determining that the group in the previous unit time period is a group representative of the target unit time period.

8. A computer device, comprising:

a processor and a memory for storing processor-executable instructions; wherein the processor is configured to execute the executable instructions to implement the deck detection method of any of claims 1-5.

9. A computer-readable storage medium having instructions thereon which, when executed by a processor of a computer device, enable the computer device to perform the deck detection method of any one of claims 1-5.