WO2016113977A1 - Traffic violation management system and traffic violation management method - Google Patents

Traffic violation management system and traffic violation management method Download PDF

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Publication number
WO2016113977A1
WO2016113977A1 PCT/JP2015/080397 JP2015080397W WO2016113977A1 WO 2016113977 A1 WO2016113977 A1 WO 2016113977A1 JP 2015080397 W JP2015080397 W JP 2015080397W WO 2016113977 A1 WO2016113977 A1 WO 2016113977A1
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WO
WIPO (PCT)
Prior art keywords
traffic violation
information
traffic
person
violation
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PCT/JP2015/080397
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French (fr)
Japanese (ja)
Inventor
光司 滝沢
浩輝 上野
谷口　正宏
Original Assignee
オムロン株式会社
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Publication date
Application filed by オムロン株式会社 filed Critical オムロン株式会社
Priority to CN201580067859.7A priority Critical patent/CN107004351B/en
Publication of WO2016113977A1 publication Critical patent/WO2016113977A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • 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
    • 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
    • G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
    • G08G1/127—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams to a central station ; Indicators in a central station
    • G08G1/13—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams to a central station ; Indicators in a central station the indicator being in the form of a map

Definitions

  • the present invention relates to a traffic violation management system and a traffic violation management method for managing information related to traffic violations using an image captured by an imaging means such as a camera.
  • Patent Document 1 discloses a violation vehicle notification system that transmits vehicle situation analysis information including an image obtained by imaging a violation vehicle including a license plate with a mobile terminal and a corresponding automobile registration number to a control server. .
  • vehicle situation analysis information including an image obtained by imaging a violation vehicle including a license plate with a mobile terminal and a corresponding automobile registration number to a control server.
  • an automobile registration number is obtained by analyzing an image obtained by a portable terminal, and the automatic registration number is transmitted to a control server as vehicle state analysis information and stored. For this reason, it is not necessary to transfer large-capacity image information from the mobile terminal to the control server, and the amount of data is minimized.
  • the above conventional configuration has the following problems. That is, in the system disclosed in Patent Document 1, only a vehicle registration number, which is vehicle state analysis information, is automatically acquired based on an image taken by a general reporter with his / her mobile terminal and transmitted to a control server. is doing. For this reason, there is a possibility of being notified based on an image of a vehicle that is not actually violated or an image that cannot be sufficiently verified even if it is violated. In this case, the number of traffic violations that must be confirmed by the police becomes enormous and the processing burden on the police is large. Also, the data that the police must check may contain data that is insufficient to establish traffic violations.
  • An object of the present invention is to provide a traffic violation management system and a traffic violation management method capable of efficiently managing information necessary for traffic violation control.
  • the traffic violation management system comprises image acquisition means, person identification means, determination means, and storage means.
  • the image acquisition means acquires an image at the time of traffic violation imaged by the cross-imaging means.
  • the person specifying means specifies at least one person among a driver, an owner, and a passenger of the vehicle in which the traffic violation is detected from the acquired image.
  • the determination means determines the certainty that the traffic violation can be proved from the acquired image.
  • the storage means stores traffic violation information that associates at least the certainty, the image used for the determination of certainty, the information of the person specified by the person specifying means, and the image used for the person specifying means, Save for each violation.
  • the traffic violation management system identifies a person who has violated the person identification means based on the image in which the traffic violation is detected, and the determination means determines the certainty of the verification and stores it in association with the image used for the verification. To do. That is, in this traffic violation management system, not only the information required for verification but also the certainty of the verification is stored in association with each other. Therefore, it is possible to efficiently manage information necessary for traffic violation control. For this reason, police officers who control traffic violations can preferentially extract traffic violation information with certainty of verification, for example.
  • the traffic violation management system is the traffic violation management system according to the first invention, further comprising a display control means for displaying the traffic violation information on the screen of the display means in the order corresponding to the certainty.
  • a display control means for displaying the traffic violation information on the screen of the display means in the order corresponding to the certainty.
  • an image or information associated with the certainty of verification can be displayed on the screen of the display means. Therefore, a police officer who determines traffic violation can check the display screen of the display means and efficiently control traffic violation.
  • a traffic violation management system is the traffic violation management system according to the first or second invention, wherein the traffic violation information is determined to be reliable by the determination means, and the person specifying means When the person can be specified by the above, it is stored in the storage means.
  • the traffic violation information including the image is stored when the certainty is determined and the person can be identified, the amount of data stored in the storage unit can be suppressed, and the storage unit can be used efficiently.
  • a traffic violation management system is the traffic violation management system according to any one of the first or second aspects of the invention, wherein the determination means is surely calculated by calculating a probability that the traffic violation can be proved. Determine sex.
  • the probability that traffic violation can be proved that is, the verification probability is a numerical value of 0 to 100%, for example.
  • the probability of verification is, for example, if there are two photos of the violation for the same violation (the vehicle number and driver's face can be confirmed), and if the specified vehicle number information and driver information can be obtained, Calculated as 100%.
  • the certainty of proof of traffic violations can be determined more precisely and in detail. Furthermore, police officers who control traffic violations can confirm traffic violation information according to the probability of verification, and can efficiently handle traffic violations.
  • a traffic violation management system is the traffic violation management system according to the fourth invention, wherein the determination means organizes a plurality of traffic violation information into a storage means for each probability within a predetermined range. save.
  • the determination means organizes a plurality of traffic violation information into a storage means for each probability within a predetermined range.
  • a traffic violation management system is the traffic violation management system according to the second aspect of the present invention, wherein the determining means determines certainty by calculating the probability that the traffic violation can be proved, and the display control means Arranges and displays a plurality of traffic violation information for each probability within a predetermined range on the screen of the display means.
  • the display control means Arranges and displays a plurality of traffic violation information for each probability within a predetermined range on the screen of the display means.
  • Traffic violation information can be displayed in descending order. For this reason, police officers who control traffic violations can confirm traffic violation information according to the probability of verification, and can efficiently handle traffic violations.
  • a traffic violation management system is the traffic violation management system according to any one of the second and sixth aspects, further comprising an input unit that receives an input operation.
  • the display control means extracts traffic violation information according to the certainty selected by the input operation of the input unit, and displays the traffic violation information on the display means.
  • traffic violation information according to the probability can be extracted by the search function and displayed on the display means, so police officers who crack down on traffic violations can check the traffic violation information according to the probability of verification. And can handle traffic violations efficiently.
  • a traffic violation management system is the traffic violation management system according to any one of the first, second and sixth inventions, wherein the imaging means is a camera for imaging a road, and the traffic violation Is detected by the camera image.
  • the imaging means is a camera for imaging a road
  • the traffic violation Is detected by the camera image since the certainty of verifying the traffic violation is determined by the camera image, the certainty of the verification can be improved.
  • a traffic violation management system is the traffic violation management system according to any one of the first, second or sixth inventions, and is a violation fee for creating a claim document for a traffic violation fee.
  • a billing document creation unit is further provided, and the violation bill request document creation unit stores the created billing document for the violation fee in the storage unit in association with the traffic violation information.
  • the traffic violation information is further stored in association with the violation billing document, a police officer or the like who controls the traffic violation can process the traffic violation more efficiently.
  • a traffic violation management system includes image acquisition means, person identification means, determination means, and display control means.
  • the image acquisition means acquires an image at the time of traffic violation imaged by the imaging means.
  • the person specifying means specifies at least one person among a driver, an owner, and a passenger of the vehicle in which the traffic violation is detected from the acquired image.
  • the determination means determines the certainty that the traffic violation can be proved from the acquired image.
  • the display control means is a traffic that associates at least the certainty, the image used for the determination of certainty, the information of the person specified by the person specifying means, and the image used for the person specifying means for each traffic violation. Violation information is displayed on the screen in order according to certainty.
  • the traffic violation management method includes an image acquisition step, a person identification step, a determination step, a storage step, and an image acquisition step.
  • the image acquisition step an image at the time of traffic violation imaged by the imaging means is acquired.
  • the person specifying step at least one person among the driver, the owner, and the passenger of the vehicle in which the traffic violation is detected from the acquired image is specified.
  • the determination step the certainty that the traffic violation can be proved is determined from the acquired image.
  • traffic violation information that associates at least the certainty, the image used for the determination of certainty, the information of the person specified in the person specifying step, and the image used in the person specifying step, Save every traffic violation.
  • the traffic violation management method specifies a person who has violated in the person specifying step based on the image in which the traffic violation is detected, determines the certainty of the verification in the determining step, and stores it in association with the image used for the verification. To do. That is, in this traffic violation management method, not only the information required for verification but also the certainty of the verification is stored in association with each other. For this reason, it is possible to efficiently manage information necessary for traffic violation control. Therefore, a police officer or the like who controls traffic violations can preferentially extract traffic violation information with certainty of verification. (The invention's effect) According to the traffic violation management system and the traffic violation management method according to the present invention, it is possible to efficiently manage information necessary for traffic violation control.
  • (A) And (b) is a figure which shows the example of installation of the camera which supplies the image imaged with respect to the traffic violation management system which concerns on one Embodiment of this invention.
  • the block diagram which shows the whole structure of the traffic violation management system which concerns on this embodiment.
  • the block diagram which shows the structure of the verification probability determination means contained in the traffic violation management system of FIG.
  • the block diagram which shows the structure of the person specific means contained in the traffic violation management system of FIG. (A)-(c) is a figure which shows an example of the display switching of the display screen of the display means contained in the traffic violation management system of FIG.
  • the flowchart which shows the flow of the verification probability determination process by the traffic violation management method system of FIG.
  • the flowchart which shows the flow of the display control processing by the traffic violation management method system of FIG.
  • a traffic violation management system 100 according to an embodiment of the present invention will be described below with reference to FIGS. ⁇ 1.
  • Overview of Traffic Violation Management System 100> The traffic violation management system 100 according to the present embodiment acquires violation detection information (including traffic violation contents, location, and images) acquired by a connected traffic violation control device, and based on the violation detection information, traffic Determine the certainty of proof of violation and manage traffic violation information according to the probability of proof.
  • the traffic violation management system 100 is installed, for example, in a police station that controls traffic violations.
  • a police officer or the like determines whether or not the traffic violation is subject to control while checking an extracted image as will be described later. That is, the traffic violation management system 100 is utilized as a system for supporting police officers and the like so that they can efficiently handle traffic violations.
  • a police officer or the like uses a PC or the like connected to the system 100 to process traffic violations while checking the display screen of the PC one by one.
  • As the input means a mouse, a keyboard, a touch panel or the like is used.
  • the traffic violation management system 100 is connected to a predetermined traffic violation control device (for example, an automatic speed violation control device, an automobile number automatic reading device, an automatic signal ignore control device, etc.).
  • the traffic violation control apparatus includes a camera as an imaging unit and supplies an image to the traffic violation management system 100.
  • the camera is, for example, a camera 10 installed at a predetermined position at an intersection as shown in FIG.
  • the camera 10 captures an image including an installed road and a vehicle that travels on the road. And the camera 10 transmits the imaged image with respect to the traffic violation management system 100 so that it may mention later.
  • the camera 10 is installed at the front of a vehicle moving within an intersection and at a position where a driver can take a photograph.
  • the installation position for example, as shown in FIG. 1A and FIG. 1B, it may be installed on a column (reverse U-shaped, L-shaped) 102 or the like provided exclusively for the camera 10. It may be attached to existing equipment such as traffic lights, street lights, pedestrian bridges, signs, etc. As shown in the figure, it is not necessary to install the camera 10 for each lane.
  • One camera may be provided for a plurality of lanes, or a plurality of cameras 10 may be set for one lane.
  • the traffic violation management system 100 acquires an image (including a photograph and a video) captured when a traffic violation is detected. Further, the traffic violation management system 100 identifies the offender from the acquired image and calculates the probability of verifying the traffic violation. In other words, the traffic violation management system 100 automatically organizes, stores, and displays information according to the probability of traffic violation verification, thereby improving the efficiency of traffic violation control by a police officer or the like.
  • the violator is a person who is determined based on the laws and regulations prescribed in each country, such as the driver of the vehicle, the passenger, the owner of the vehicle, etc. Also good.
  • the detected traffic violation content is a traffic violation that can be verified using an image.
  • the traffic violation management system 100 includes a detection information acquisition unit 11 (an example of an image acquisition unit), a verification probability determination unit 12 (an example of a determination unit), and a person identification unit 13 (a person identification unit).
  • a non-compliance claim document preparation means 14 (an example of a non-compliance claim request document preparation means), a storage means 15 (an example of storage means), a display control means 16 (an example of display control means), and a display means 17 (An example of display means).
  • the traffic violation management system 100 is also connected to an input unit 150 (an example of an input unit).
  • the detection information acquisition unit 11 acquires violation information from the violation detection unit 19.
  • the violation detection means 19 is a traffic violation control apparatus such as an automatic speed violation control apparatus, an automobile number automatic reading apparatus, and an automatic signal ignore control apparatus, and includes a camera 10 (an example of an image pickup means) as an image pickup means.
  • the camera 10 captures the license plate and driver of the target vehicle and generates an image.
  • the automatic speed violation control apparatus includes, for example, a radar type and a loop coil type, and may use a known technique.
  • the traffic violation management system 100 may be connected to the violation detection means 19 belonging to another system.
  • the detection information acquisition unit 11 acquires violation detection information from the violation detection unit 19.
  • the violation detection information includes the content (type) of the traffic violation, the location where the traffic violation has occurred, and the image captured by the camera 10 (an image of a violation vehicle or a person).
  • the detection information acquisition unit 11 transmits the acquired image to the verification probability determination unit 12 and the person identification unit 13.
  • the detection information acquisition unit 11 includes a storage unit (not shown) that temporarily stores the acquired violation detection information (including image data), and performs processing by the system 100 after adjusting the reception time interval and the data amount. You may make it start.
  • the verification probability determination means 12 determines whether or not sufficient information for verifying the traffic violation is available from the content of the traffic violation and information such as one or a plurality of images including the vehicle in violation. The certainty is determined, and the verification probability is calculated. More specifically, based on the content of the traffic violation acquired and the content and clarity of the image of the traffic violation, it is determined whether there are images that can be used as evidence to prove the traffic violation. Calculate the probability of verification.
  • the content of the image is, for example, when all faces of a person are included, all license plates are included, a person's face and license plate are included in one image, or not all Whether it is included to the extent.
  • the probability of verification is also calculated from the number of photographs taken of the same violation.
  • the verification probability determining means 12 specifies the image used by the person specifying means 13 or the image used for verification and the person specifying means 13 for each traffic violation when the person can be specified by the person specifying means 13 described later.
  • the traffic violation information in which the personal information and the like to be associated with the verification probability is generated and stored in the storage unit 15. The detailed processing contents of the verification probability determination unit 12 will be described in detail later with reference to FIG.
  • Person specifying means 13 specifies a person related to a violation vehicle or a traffic violation.
  • the person related to the traffic violation includes a driver of the offending vehicle, a passenger, an owner, an employer (a company, etc.) of the driver of the offending vehicle, and the like.
  • the person specifying unit 13 inquires the vehicle number information read from the image received from the detection information acquiring unit 11 and the registered information stored in advance, specifies the owner of the vehicle, and outputs it as person information.
  • the person identification means 13 uses a known face authentication technique to collate the driver's or passenger's face detected from the image with the photo information of the license held in advance, and violates the driver or passenger. Is identified.
  • the person specifying unit 13 outputs the specified person information and vehicle information to the verification probability determining unit 12. Detailed processing contents when the person specifying means 13 specifies a person related to the traffic violation will be described in detail later with reference to FIG.
  • the infringement fee claim document preparation means 14 creates an invoice for a traffic infringement fee (foul) for each traffic violation. More specifically, the breach money billing document creation means 14 refers to information on the breach money stored in advance based on the content of the selected traffic breach, and sets the amount of the breach money. Then, the non-compliance fee billing document creating means 14 detects an address or the like to which the invoice is to be sent based on the personal information specified by the selected traffic violation, and creates a non-violating bill request document.
  • the storage unit 15 stores the traffic violation information generated by the verification probability determination unit 12.
  • the storage means 15 is, for example, a magnetic recording device, a semiconductor memory, or the like.
  • the display control means 16 controls the display means 17 so that the traffic violation information stored in the storage means 15 is displayed in the order of groups with the highest probability of verification.
  • the display unit 17 is a display device such as a liquid crystal display, for example, and displays traffic violation information stored in the storage unit 15 according to the probability of verification. The display mode on the display screen of the display unit 17 will be described in detail later with reference to FIGS.
  • the input unit 150 includes a mouse, a keyboard, a touch panel and the like connected to the traffic violation management system 100 and is operated by a user (a police officer or the like). In accordance with the operation of the input unit 150, functions by the non-compliance fee billing document creation means 14, the display control means 16, and the like are executed.
  • the verification probability determination means 12 will be described below with reference to FIG. As shown in FIG. 3, the verification probability determination unit 12 can access a database (DB) 21 that is a part of the storage unit 15.
  • the DB 21 stores the traffic violation information generated by the verification condition storage unit 211 for storing information (validation conditions) related to the conditions for verifying the traffic violation (including image conditions that can be used for verification) and the verification probability determination means 12.
  • a traffic violation information storage unit 212 for storing.
  • the verification conditions are stored in the verification condition storage unit 211 of the DB 21.
  • the verification condition includes, for example, condition items such as the number of photographs and images taken of the violating vehicle or a person, the image quality, the content, and the sharpness, and a threshold value serving as a reference for verification possibility is set for each condition item.
  • the verification probability determination means 12 refers to the verification conditions stored in the verification condition storage unit 211, and to what extent these condition items are satisfied, for example, whether or not the threshold value is exceeded or not, and whether the person can be determined. Etc. are determined. For example, if there are two photos of the same violation, one for confirming the car number at the time of the violation and another for confirming the driver's face, the probability of verification is calculated as 100%.
  • the verification probability determination unit 12 may not calculate the verification probability and may terminate the process because the verification is impossible when the verification conditions are hardly satisfied.
  • the verification probability is less than a predetermined value (for example, less than 80%)
  • the verification probability determination unit 12 may end the process without calculating the verification probability and making verification impossible.
  • the driver's face in the image is clear and can be sufficiently matched with the face photo of the license.
  • the vehicle number of the violating vehicle in the image is clear and sufficiently readable.
  • the above-mentioned verification conditions are stored in advance based on the conditions necessary for verification according to the laws, regulations, operations, etc. of national and local governments. For example, an identifiable violation vehicle and driver must be included in a single image. When multiple images are combined, the identifiable violation vehicle and person can be verified in each image. In order to prove traffic violations, there must be at least two photographs of a person.
  • a condition that specifies only the driver (whether there is a driver's image or photo) is set, and the country controls the vehicle only. For example, a condition for specifying only the vehicle number is set.
  • Such preconditions are stored in advance in the DB 21 or the like.
  • the verification probability determination unit 12 refers to the stored precondition and determines whether the acquired violation detection information satisfies the precondition. If the precondition is not satisfied before the verification probability is determined, the verification probability determination unit 12 may terminate the process as a verification impossible.
  • the verification conditions may be weighted according to the importance of the evidence. For example, if the condition item that the license plate is in the image is more important than the number of acquired images, the clarity of the license plate image has a high contribution to the verification, and the number of images is verified. The contribution to is considered low. In this case, the former weight coefficient is set large and the latter weight coefficient is set small.
  • the verification probability determination unit 12 compares the verification conditions stored in the DB 21 with the acquired image, and calculates the probability of verifying that the target vehicle included in the image has committed a traffic violation. To do.
  • the verification probability determination means 12 also uses an image used by the person identification means 13 or an image used for determination of verification for each traffic violation and the person identification means 13 when a person can be identified by the person identification means 13 described later. Traffic violation information that associates the identified personal information and the verification probability is generated.
  • the verification probability determination unit 12 stores the generated traffic violation information in the traffic violation information storage unit 212.
  • the traffic violation information is stored for each verification probability so that the traffic violation information can be managed and output (100% verification probability, 80% verification probability, less than 80% verification probability, etc.).
  • the image stored as traffic violation information may not be all the images acquired as violation detection information, or may be a part thereof. For example, only an image that matches the verification condition and / or the above preconditions, or an image that is used by the person specifying means 13 described later may be stored.
  • the verification condition storage unit 211 and the traffic violation information storage unit 212 do not need to be provided in the DB 21 and may be provided in another connectable storage device (semiconductor memory, magnetic recording medium, optical recording medium, etc.).
  • the person specifying unit 13 can access a database (DB) 23 that is a part of the storage unit 15.
  • the DB 23 includes a license information storage unit 231 and an automobile registration number storage unit 232.
  • the license information storage unit 231 stores information such as the face photograph, name, address, date of birth, etc. of the driver license holder.
  • the automobile registration number storage unit 232 stores information such as an automobile registration number (number plate), the name of a vehicle owner, and an address.
  • the person specifying means 13 refers to the license information storage unit 231 and the automobile registration number storage unit 232, and collates with the image in the acquired violation detection information, so that the person (driver) , Passengers, owners, users (businesses, etc.). Specifically, for example, the person specifying means 13 uses the face photograph of the driver's face stored in the driver's license information storage unit 231 using the face authentication technology for the face of the driver, passenger, etc. included in the image. Determine whether they match. In addition, the vehicle number detected from the image and the vehicle information stored in the automobile registration number storage unit 232 are collated, and the owner or the like of the violating vehicle specifies.
  • the person specifying unit 13 transmits the specified person information to the verification probability determining unit 12 and stores the image used for specifying the person in the storage unit 15.
  • the license information storage unit 231 and the automobile registration number storage unit 232 do not have to be provided in the DB 23, and may be provided in another connectable storage device (semiconductor memory, magnetic recording medium, optical recording medium, etc.). .
  • the verification probability determination unit 12 and the person identification unit 13 calculate the verification probability for each traffic violation, and the storage unit 15 together with the corresponding image and other accompanying information. Saved in. Then, the display control means 16 converts the traffic violation information stored in the storage means 15 (DB 21) into a predetermined format in accordance with an operation by the input unit 150 and displays it on the display means 17.
  • FIGS. 5A to 5C various types of information on traffic violations are displayed on the screen of the display unit 17 such as a liquid crystal display.
  • the screen 17a in FIG. 5A displays the traffic violation information for which the verification probability is calculated by the traffic violation management system 100 for each group of verification probabilities within a predetermined range (in the illustrated example, 100%, 99% to 80%, An example of displaying the number of cases in less than 80%) is shown.
  • the screens are displayed in order from the group having the highest probability of verification. Therefore, a user (a police officer or the like) can preferentially select a group having a high verification probability by looking at the screen 17a.
  • the selection operation is performed by the input unit 150.
  • the screen 17b transitions to the screen 17b in FIG.
  • the screen 17b in FIG. 5B shows an example in which the traffic violation information of the group having a high verification probability (100% verification probability) selected in FIG. 5A is displayed as a list.
  • main information date, violation type, violator name, location, etc.
  • the list of traffic violation information may be displayed in order of date, order of violation type, order with the same number of violators, etc.
  • the screen 17c in FIG. 5 (c) shows the detailed contents of the traffic violation information selected in FIG. 5 (b).
  • the traffic violation information includes, for example, the content of the traffic violation (type), the location of the violation, the name of the offender (at least one of the driver and the vehicle owner), the date and time of image capture, and an image that identifies the violation. (At least an image that can identify a person and a vehicle). As shown in the figure, one traffic violation information is displayed on the screen 17c.
  • information necessary to prove one traffic violation (violation content, image for specifying a person and a vehicle, violation location, image capturing date / time, etc.) ) And the calculated verification probability are stored in a state associated with each other in the storage unit 15 (DB21). For this reason, these associated information can be displayed on the display means 17 according to the verification probability. For example, the number of traffic violations is displayed for each verification probability within a predetermined range as shown in the screen 17a of FIG. 5A, or traffic violation information is displayed in ascending or descending order of the verification probability. Including doing.
  • a police officer who controls traffic violations using the system 100 first confirms the screen 17a shown in FIG. 5A, and acquires traffic violation information of a group with a high probability of verification. Then, on the screen 17b shown in FIG. 5B, the traffic violation information of further interest can be selected and the details can be confirmed in FIG. 5C. Therefore, the police officer can start from a case with a high probability of probing that can be processed quickly, and can improve the efficiency of traffic violation control.
  • step S ⁇ b> 601 the detection information acquisition unit 11 of the traffic violation management system 100 acquires one violation detection information from the violation detection unit 19.
  • the violation detection information includes the content (type) of the traffic violation, the location where the traffic violation has occurred, and the image captured by the camera 10 as described above.
  • Traffic violation details (types) are, for example, verified using images such as signal ignorance, overspeed, traffic prohibition violation, traffic classification violation, overtaking prohibition violation, designated place temporary stoppage, neglected parking violation, traffic zone violation, etc. It is a possible traffic violation.
  • the detection information acquisition unit 11 proceeds to step S602.
  • step S ⁇ b> 602 the detection information acquisition unit 11 acquires an image included in the violation detection information and transmits the image to the verification probability determination unit 12 and the person identification unit 13.
  • the verification probability determination unit 12 calculates the verification probability based on the violation detection information including the traffic violation content (type) and image acquired from the detection information acquisition unit 11. Specifically, the verification probability determination unit 12 accesses the verification condition storage unit 211 of the DB 21 to determine how much the acquired image satisfies the verification condition, whether it is equal to or greater than a threshold, and whether a person can be determined. Judge equally.
  • a threshold value is set for each condition item such as the number of photographs or images taken of a violating vehicle or a person, the image quality, the content, and the clarity. For example, if there are two photographs for the same violation, a photograph that allows confirmation of the vehicle number at the time of the violation and a photograph that allows confirmation of the driver's face, the verification probability determination means 12 is calculated as 100%. For example, for the same violation, if there is one photograph at the time of the violation and the car number is clear but the top of the driver's forehead has not been photographed, a probability of verification of 80% is calculated.
  • the verification conditions used by the verification probability determination means 12 are determined according to the laws, ordinances, operations, etc. of each country or local government, and it is determined whether the verification conditions are satisfied when determining the verification probability. .
  • the verification probability determination means 12 may terminate the process because the verification probability is impossible without calculating the verification probability when the verification conditions are hardly satisfied or when the vehicle or the person cannot be determined.
  • the person specifying unit 13 specifies a person related to the traffic violation from the acquired image.
  • the person related to the traffic violation includes a driver of the violating vehicle, a passenger, an owner, an employer (a company, etc.) of the driver of the violating vehicle, and the like.
  • the person specifying unit 13 specifies at least one of the driver and the owner of the offending vehicle among these pieces of person information.
  • the person specifying unit 13 compares the vehicle number information read from the acquired image with the registration information acquired by accessing the automobile registration number storage unit 232 of the DB 23, and specifies the vehicle information and its owner.
  • the person specifying means 13 collates the driver and passenger face information acquired from the acquired image with the face information of the person acquired by accessing the license information storage unit 231 of the DB 23, and Identify passengers. Then, the person specifying means 13 outputs the specified license number, owner, driver, passenger information, etc. to the verification probability determining means. When there are a plurality of specified persons, for example, when the owner and the driver are different, or when the passenger can be specified in addition to the driver, the respective information is output to the verification probability determining means 12.
  • the image used for the person identification is stored in the storage means 15.
  • step S605 the verification probability determining unit 12 determines the verification probability calculated in step S604, the image used by the person specifying unit 13, the image used for determining verification, the person information specified by the person specifying unit 13, and the like. To generate traffic violation information and store it in the traffic violation information storage unit 212 of the DB 21.
  • step S701 the display control means 16 of the traffic violation management system 100 displays the screen 17a (FIG. 5 (a)) in accordance with the input operation of the input unit 150 (FIG. 2) of the user (a police officer or the like who performs control). It is displayed on the display means 17. The user looks at the screen 17a and determines a group to be selected according to the verification probability.
  • step S ⁇ b> 702 the user selects, for example, a group of “1. Probability of 100%” from the screen 17 a via the input unit 150.
  • step S703 the display control unit 16 changes the screen of the display unit 17 from the screen 17a to the screen 17b (FIG. 5B) in response to the input operation of the input unit 150 in step S703.
  • the screen 17b displays a list of traffic violation information determined by the verification probability determination means 12 as a verification probability of 100%. The user determines the traffic violation information of interest by looking at the screen 17b.
  • step S704 the user selects one traffic violation information of interest from the screen 17b via the input unit 150.
  • the display control means 16 changes the screen of the display means 17 from the screen 17b to the screen 17c (FIG. 5C) according to the input operation of the input unit 150 in step S704.
  • the screen 17c displays details of the selected traffic violation information. The user looks at the screen 17c, confirms the content of the traffic violation, and finally decides whether to notify the offender (including whether to charge the offense).
  • step S706 when notifying the violator of the traffic violation displayed on the screen 17c, the user performs an input operation (selecting a button on the screen, etc.) via the input unit 150, and proceeds to step S707. . If not notified, the process proceeds to step S708.
  • step S707 the breach money claim document creation means 14 creates a breach money claim document including a notification, a billing address, etc. in response to the input operation in step S706.
  • the breach money claim document creation means 14 refers to information on the breach money stored in advance based on the content of the selected traffic breach, and calculates the amount of the breach money.
  • step S708 the display control means 16 ends the process when there is an operation to end the screen via the input unit 150, and returns to the designated screen when returning to another screen (step S709).
  • the traffic violation management system 100 and the traffic violation management method executed by the system according to the present embodiment calculate the verification probability and the verification probability for each detected traffic violation, and verify the traffic violation.
  • Necessary information (violation content, image for identification, other information, etc.) is stored in association with each other.
  • these pieces of information can be extracted and displayed according to the verification probability. This makes it possible to extract information on traffic violations with a high probability of verification among traffic violations at a police station or the like. Therefore, since police officers can confirm and claim charges for violations from violation cases with a high probability of proof, the efficiency of traffic violation control by police officers and the like can be greatly improved compared to the prior art.
  • the traffic violation management system 100 may be implemented, for example, with a configuration as shown in FIG.
  • the traffic violation management system 100 is connected to an external traffic violation control device (violation detection means 19) via a network N such as the Internet, a LAN (Local Area Network), or a WAN (Wide Area Network).
  • the traffic violation management system 100 is also connected to the storage device 160.
  • the traffic violation management system 100 includes a computer terminal, and includes a CPU (Central Processing Unit) 110, a RAM (Random Access Memory) 120, an output unit 130, a communication unit 140, an input unit 150, and the like.
  • a CPU Central Processing Unit
  • RAM Random Access Memory
  • the CPU 110 executes various arithmetic processes and the like, and executes a predetermined control program that is read into the RAM 120 and expanded.
  • a control program executes a predetermined control program that is read into the RAM 120 and expanded.
  • the RAM 120 is configured by a memory element such as SRAM (Static RAM) or DRAM (Dynamic RAM), and stores data generated during the processing of the CPU 110.
  • the output unit 130 has connection terminals for connecting cables or the like for transmitting analog signals or digital signals such as images and sounds, and is connected to the display means 17 described above via these cables.
  • the output unit 130 converts various types of information read from the storage device 160 into image signals in accordance with instructions from the display control unit 16 and outputs the image signals to the display unit 17 via a cable.
  • the communication unit 140 has a connection terminal or a wireless communication interface for connecting a communication cable, and is connected to the network N.
  • the communication unit 140 transmits / receives data to / from the traffic violation control device (violation detection unit 19) or the camera 10 connected to the network N.
  • the input unit 150 is configured by (a mouse, a keyboard, a touch panel operated on a screen, or the like).
  • the input unit 150 accepts input of information by user operation, menu selection, and the like, and notifies the CPU 110 of the accepted operation content.
  • the storage device 160 includes a semiconductor memory, a magnetic recording medium, an optical recording medium, and the like.
  • the storage means 15 described above may be included in the storage device 160, or may be a separately connected mass storage device.
  • the storage device 160 may be connected to the traffic violation management system 100 via a network.
  • the verification probability is calculated by the verification probability determination means 12 as the determination of certainty for proving the traffic violation, but it is not always necessary to calculate a specific probability.
  • a determination unit that determines whether or not verification is possible may be provided.
  • a determination unit that replaces the verification probability determination unit 12 determines whether the acquired violation detection information satisfies a verification condition stored in the verification condition storage unit 211 of the DB 21. When these conditions are satisfied, the determination unit obtains traffic violation information including an image used by the person specifying unit 13 for each traffic violation, an image used for the determination, and personal information specified by the person specifying unit 13. Generated and stored in the storage means 15.
  • the person identification unit 13 may acquire the person information, and then the verification probability determination unit 12 may determine the verification probability (steps S603 and S604 in FIG. 6 are performed). Replace).
  • the verification probability determination unit 12 determines the verification probability. If the person information cannot be acquired, the process ends.
  • the probability of proving a traffic violation becomes small and verification is impossible. Determined.
  • the vehicle owner information can be acquired as the personal information, the driver is unclear, If the personal information cannot be acquired, the probability of proving the traffic violation is reduced and it is determined that the verification is impossible.
  • the non-compliance fee claim document creating means 14 creates the non-conformity claim document according to the selection operation via the input unit 150, but is not limited thereto. If the violation detection information is acquired by the detection information acquisition unit 11 and the person information can be acquired by the person specifying unit 13, the violation bill request document generation unit 14 generates a violation fee request document and DB 21 etc. together with the traffic violation information. You may make it save to. In this case, when the display control means 16 displays the traffic violation information on the display means 17 (screens 17b and 17c in FIG. 5), the violation amount may be displayed together.
  • the configuration including the display means 17 such as a liquid crystal display has been described as an example.
  • the present invention is not limited to this.
  • the traffic violation management system of the present invention may be configured as a system that does not include display means such as a liquid crystal display.
  • the traffic violation management system 100 may be configured as a system that includes the display unit 17 and does not include the storage unit 15.
  • the traffic violation management system 100 acquires the violation detection information by the violation detection means 19 including the camera 10, but the present invention is not limited to this.
  • the report may include a mobile terminal or camera image from a general person. Even in this case, it is possible to specify a person from an image, a photograph or the like acquired by the person specifying unit 13 and calculate the verification probability by the verification probability determining unit 12.
  • the traffic violation management system 100 that calculates the probability of traffic violation at a police station or the like using information transmitted from the external violation detection means 19 is taken as an example.
  • the traffic violation management system 100 may include violation detection means.
  • the traffic violation management system 100 acquires an image from imaging means such as a camera, and identifies a traffic violation from the image.
  • the signal ignoring violation is specified based on information related to switching of traffic lights at an intersection where a camera is installed.
  • the overspeed violation is identified based on information on the speed limit on the road where the camera is installed, information on the camera imaging speed, and the like.
  • the display control unit 16 displays traffic violation information on the display unit 17 with a low probability of verification (for example, a probability of verification of less than 50%) according to a user input operation. You may let them.
  • the traffic violation information with a low verification probability selected according to the user's input operation may be deleted from the traffic violation information storage unit 212.
  • the traffic violation management system 100 may automatically delete or move traffic violation information with a low probability of verification to another storage device. Thereby, the amount of data stored in the storage unit 15 can be suppressed, and the storage capacity can be used effectively.
  • the traffic violation management system 100 can also detect and manage various types of traffic violations.
  • traffic violations include speeding, signal ignorance, traffic prohibition / U-turn prohibition violation, traffic classification violation, reverse running, overtaking prohibition violation, designated place temporary stop, neglected parking violation, traffic zone violation, route bus, etc. Includes traffic zone violations, inability to maintain distances between vehicles, no lights, use of mobile phones, etc.
  • the DBs 21 and 23 may be configured by a single database.
  • the DBs 21 and 23 may be included as part of the traffic violation management system 100, or may be included in another system so that the traffic violation management system 100 can be accessed.
  • the execution order of the processing methods executed by the traffic violation management system 100 is not necessarily limited to the description of the above embodiment, and the execution order can be changed without departing from the gist of the invention.
  • a traffic violation management method that is a processing method executed by the traffic violation management system 100, a computer program that causes a computer to execute the method, and a computer-readable recording medium that records the program are included in the scope of the present invention.
  • examples of the computer-readable recording medium include a flexible disk, a hard disk, a CD-ROM, an MO, a DVD, a DVD-ROM, a DVD-RAM, a BD (Blu-ray (registered trademark) Disc), and a semiconductor memory.
  • the computer program is not limited to the one recorded on the recording medium, but may be transmitted via an electric communication line, a wireless or wired communication line, a network represented by the Internet, or the like.
  • the traffic violation management system and method of the present invention has the effect of being able to efficiently detect and manage information related to traffic violation control. Therefore, it is expected to be widely used as a traffic violation management system adopted by the national and local governments.

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Abstract

A traffic violation management system (100) that is provided with a detection information acquisition means (11), a person specification means (13), a determination means (12), and a storage means (15). The detection information acquisition means (11) acquires images that are captured by an imaging means of the time of a traffic violation. The person specification means (13) specifies, from the acquired images, at least one person from among the driver, the owner, and a passenger of the vehicle for which the traffic violation was detected. The determination means (12) determines, from the acquired images, the certainty with which the traffic violation can be proven. For each traffic violation, the storage means (15) saves traffic violation information that associates at least the certainty, the image(s) used in the determination of the certainty, information on the person(s) specified by the person specification means (13), and the image(s) used by the person specification means (13).

Description

交通違反管理システムおよび交通違反管理方法Traffic violation management system and traffic violation management method
　本発明は、カメラ等の撮像手段で撮像された画像を用いて交通違反に関する情報の管理を行う交通違反管理システムおよび交通違反管理方法に関する。 The present invention relates to a traffic violation management system and a traffic violation management method for managing information related to traffic violations using an image captured by an imaging means such as a camera.
　従来、カメラ等の撮像装置で撮像した車両の撮像画像を用いて、その車両や運転者等を判別する車両認識装置が提案されている。このような車両認識装置は、交通違反の取締りや、事故対応、犯罪捜査（犯罪に使用された車両の発見）等への利用が有効と考えられている。
　例えば、特許文献１には、携帯端末によりナンバープレートを含む違反車両を撮像した画像と対応する自動車登録番号とを含む車両状況解析情報を、取締サーバに送信する違反車両通報システムが開示されている。同違反車両通報システムにおいては、携帯端末によって取得した画像を解析して自動車登録番号を取得し、この自動登録番号を車両状況解析情報として取締サーバに送信し保存する。このため、携帯端末から取締サーバに容量の大きい画像情報を転送する必要がなく、データ量を最小限にしている。 2. Description of the Related Art Conventionally, a vehicle recognition device that discriminates a vehicle, a driver, and the like using a captured image of a vehicle captured by an imaging device such as a camera has been proposed. Such a vehicle recognition device is considered to be effective for traffic violation control, accident response, criminal investigation (finding of a vehicle used for crime), and the like.
For example, Patent Document 1 discloses a violation vehicle notification system that transmits vehicle situation analysis information including an image obtained by imaging a violation vehicle including a license plate with a mobile terminal and a corresponding automobile registration number to a control server. . In the violating vehicle notification system, an automobile registration number is obtained by analyzing an image obtained by a portable terminal, and the automatic registration number is transmitted to a control server as vehicle state analysis information and stored. For this reason, it is not necessary to transfer large-capacity image information from the mobile terminal to the control server, and the amount of data is minimized.
　しかしながら、上記従来の構成では、以下に示すような問題点を有している。
　すなわち、上記特許文献１に開示されたシステムでは、一般の通報者が自身の携帯端末で撮像した画像に基づき、自動的に車両状況解析情報である自動車登録番号のみを取得し、取締サーバに送信している。このため、実際には違反していない車両の画像や、違反していても十分に立証できない画像に基づき通報されるおそれがある。この場合、警察が確認しなければならない交通違反件数は膨大になり、警察の処理負担が大きい。また、警察が確認しなければならないデータの中には、交通違反を立証するのに不十分なデータが含まれる可能性がある。 However, the above conventional configuration has the following problems.
That is, in the system disclosed in Patent Document 1, only a vehicle registration number, which is vehicle state analysis information, is automatically acquired based on an image taken by a general reporter with his / her mobile terminal and transmitted to a control server. is doing. For this reason, there is a possibility of being notified based on an image of a vehicle that is not actually violated or an image that cannot be sufficiently verified even if it is violated. In this case, the number of traffic violations that must be confirmed by the police becomes enormous and the processing burden on the police is large. Also, the data that the police must check may contain data that is insufficient to establish traffic violations.
特開２００６－１１９７６７号公報JP 2006-119767 A
　本発明の課題は、交通違反の取締りに必要な情報を効率的に管理することが可能な交通違反管理システムおよび交通違反管理方法を提供することにある。 An object of the present invention is to provide a traffic violation management system and a traffic violation management method capable of efficiently managing information necessary for traffic violation control.
　第１の発明に係る交通違反管理システムは、画像取得手段と、人物特定手段と、判定手段と、記憶手段と、を備える。画像取得手段は、交撮像手段により撮像された交通違反の時の画像を取得する。人物特定手段は、取得した画像から、交通違反が検出された車両の運転者および所有者および同乗者うちの少なくとも一の人物を特定する。判定手段は、取得した画像から、交通違反を証明できる確実性を判定する。記憶手段は、少なくとも上記確実性と、確実性の判定に用いた画像と、人物特定手段により特定された人物の情報と、人物特定手段に用いられた画像とを関連付けた交通違反情報を、交通違反毎に保存する。 The traffic violation management system according to the first invention comprises image acquisition means, person identification means, determination means, and storage means. The image acquisition means acquires an image at the time of traffic violation imaged by the cross-imaging means. The person specifying means specifies at least one person among a driver, an owner, and a passenger of the vehicle in which the traffic violation is detected from the acquired image. The determination means determines the certainty that the traffic violation can be proved from the acquired image. The storage means stores traffic violation information that associates at least the certainty, the image used for the determination of certainty, the information of the person specified by the person specifying means, and the image used for the person specifying means, Save for each violation.
　本交通違反管理システムは、交通違反が検出された画像に基づいて、人物特定手段が違反した人物を特定するとともに、判定手段がその立証の確実性を判定し、立証に用いる画像と関連付けて保存する。つまり、本交通違反管理システムでは、立証に要する情報だけでなくその立証の確実性も関連付けて保存される。よって、交通違反の取締りに必要な情報を効率的に管理することができる。このため、交通違反を取り締まる警察官等は、例えば、立証の確実性のある交通違反情報を優先的に抽出することができる。 The traffic violation management system identifies a person who has violated the person identification means based on the image in which the traffic violation is detected, and the determination means determines the certainty of the verification and stores it in association with the image used for the verification. To do. That is, in this traffic violation management system, not only the information required for verification but also the certainty of the verification is stored in association with each other. Therefore, it is possible to efficiently manage information necessary for traffic violation control. For this reason, police officers who control traffic violations can preferentially extract traffic violation information with certainty of verification, for example.
　第２の発明に係る交通違反管理システムは、第１の発明に係る交通違反管理システムであって、表示手段の画面に上記確実性に応じた順番に交通違反情報を表示させる表示制御手段を更に備える。
　ここでは、立証の確実性に関連付けられた画像や情報を、表示手段の画面に表示することができる。よって、交通違反の判定を行う警察官等は、表示手段の表示画面を確認して、効率よく交通違反の取締りを実施することができる。 The traffic violation management system according to the second invention is the traffic violation management system according to the first invention, further comprising a display control means for displaying the traffic violation information on the screen of the display means in the order corresponding to the certainty. Prepare.
Here, an image or information associated with the certainty of verification can be displayed on the screen of the display means. Therefore, a police officer who determines traffic violation can check the display screen of the display means and efficiently control traffic violation.
　第３の発明に係る交通違反管理システムは、第１または第２の発明に係る交通違反管理システムであって、交通違反情報は、判定手段により確実性があると判定され、かつ、人物特定手段により人物が特定できた場合に、記憶手段に保存される。
　ここでは、画像を含む交通違反情報は、確実性が判定され且つ人物が特定できた場合に保存されるため、記憶手段の記憶データ量を抑えることができ、記憶手段を効率的に使用できる。 A traffic violation management system according to a third invention is the traffic violation management system according to the first or second invention, wherein the traffic violation information is determined to be reliable by the determination means, and the person specifying means When the person can be specified by the above, it is stored in the storage means.
Here, since the traffic violation information including the image is stored when the certainty is determined and the person can be identified, the amount of data stored in the storage unit can be suppressed, and the storage unit can be used efficiently.
　第４の発明に係る交通違反管理システムは、第１または第２の発明のいずれか１つに係る交通違反管理システムであって、判定手段は、交通違反を証明できる確率を算出することにより確実性を判定する。
　ここで、交通違反を証明できる確率、つまり立証確率とは、例えば、０～１００％までの数値である。立証確率は、例えば、同一違反について、違反時の写真が２枚（車番と運転者の顔が確認できるもの）あり、特定した車番情報と運転者情報が取得できた場合は、立証確率１００％と算定される。また、例えば、同一違反について、違反時の写真が１枚あり、車番は明確であるものの運転者のおでこから上が撮影できていない場合であって、特定した車番情報と運転者情報が取得できた場合は、立証確率８０％が算定される。 A traffic violation management system according to a fourth aspect of the present invention is the traffic violation management system according to any one of the first or second aspects of the invention, wherein the determination means is surely calculated by calculating a probability that the traffic violation can be proved. Determine sex.
Here, the probability that traffic violation can be proved, that is, the verification probability is a numerical value of 0 to 100%, for example. The probability of verification is, for example, if there are two photos of the violation for the same violation (the vehicle number and driver's face can be confirmed), and if the specified vehicle number information and driver information can be obtained, Calculated as 100%. Also, for example, for the same violation, there is one photo at the time of the violation, and the car number is clear but the top of the driver's forehead has not been photographed, and the specified car number information and driver information are If it can be obtained, a verification probability of 80% is calculated.
　ここでは、交通違反を証明できる確率を算定するため、交通違反の証明の確実性をより厳密かつ詳細に判定できる。更に、交通違反を取り締まる警察官等は、立証の確率に応じて交通違反情報を確認することができ、効率的に交通違反を処理することができる。 Here, since the probability of proving traffic violations is calculated, the certainty of proof of traffic violations can be determined more precisely and in detail. Furthermore, police officers who control traffic violations can confirm traffic violation information according to the probability of verification, and can efficiently handle traffic violations.
　第５の発明に係る交通違反管理システムは、第４の発明に係る交通違反管理システムであって、判定手段は、所定範囲の上記確率毎に、複数の交通違反情報を整理して記憶手段に保存する。
　ここでは、所定範囲の交通違反を証明できる確率に応じて、交通違反情報を整理して保存するため、例えば、確率の高い交通違反情報のみを抽出したり、確率の低い交通違反情報を削除または別の記憶手段に移動させたりすることが可能になる。このため、効率的に交通違反を処理できることに加え、記憶手段の記憶データ量を抑えることができ、記憶手段を効率的に使用できる。 A traffic violation management system according to a fifth invention is the traffic violation management system according to the fourth invention, wherein the determination means organizes a plurality of traffic violation information into a storage means for each probability within a predetermined range. save.
Here, in order to organize and store traffic violation information according to the probability of proving traffic violations within a predetermined range, for example, extracting only traffic violation information with high probability or deleting traffic violation information with low probability or It can be moved to another storage means. For this reason, in addition to being able to handle traffic violations efficiently, the amount of data stored in the storage means can be suppressed, and the storage means can be used efficiently.
　第６の発明に係る交通違反管理システムは、第２の発明に係る交通違反管理システムであって、判定手段は、交通違反を証明できる確率を算出することにより確実性を判定し、表示制御手段は、表示手段の画面に、所定範囲の上記確率毎に複数の交通違反情報を整理して表示させる。
　ここで、所定範囲の交通違反を証明できる確率に応じて、交通違反情報を整理して表示手段に表示するため、例えば、所定範囲の確率毎に交通違反件数を出力したり、確率の昇順または降順に交通違反情報を表示できる。このため、交通違反を取り締まる警察官等は、立証の確率に応じて交通違反情報を確認することができ、効率的に交通違反を処理することができる。 A traffic violation management system according to a sixth aspect of the present invention is the traffic violation management system according to the second aspect of the present invention, wherein the determining means determines certainty by calculating the probability that the traffic violation can be proved, and the display control means Arranges and displays a plurality of traffic violation information for each probability within a predetermined range on the screen of the display means.
Here, in order to organize the traffic violation information and display it on the display means according to the probability of proving the traffic violation in the predetermined range, for example, outputting the number of traffic violations for each probability in the predetermined range, Traffic violation information can be displayed in descending order. For this reason, police officers who control traffic violations can confirm traffic violation information according to the probability of verification, and can efficiently handle traffic violations.
　第７の発明に係る交通違反管理システムは、第２または第６の発明のいずれか１つに係る交通違反管理システムであって、入力操作を受け付ける入力部を更に備える。表示制御手段は、入力部の入力操作によって選択される確実性に応じて交通違反情報を抽出し、表示手段に表示させる。
　ここでは、検索機能によって確率に応じた交通違反情報を抽出し、表示手段に表示することができるため、交通違反を取り締まる警察官等は、立証の確率に応じて交通違反情報を確認することができ、効率的に交通違反を処理することができる。 A traffic violation management system according to a seventh aspect is the traffic violation management system according to any one of the second and sixth aspects, further comprising an input unit that receives an input operation. The display control means extracts traffic violation information according to the certainty selected by the input operation of the input unit, and displays the traffic violation information on the display means.
Here, traffic violation information according to the probability can be extracted by the search function and displayed on the display means, so police officers who crack down on traffic violations can check the traffic violation information according to the probability of verification. And can handle traffic violations efficiently.
　第８の発明に係る交通違反管理システムは、第１、第２または第６の発明のいずれか１つに係る交通違反管理システムであって、撮像手段は道路を撮像するカメラであり、交通違反はカメラの画像により検出される。
　ここでは、カメラ画像により交通違反を立証する確実性を判定するため、立証の確実性を向上させることができる。 A traffic violation management system according to an eighth invention is the traffic violation management system according to any one of the first, second and sixth inventions, wherein the imaging means is a camera for imaging a road, and the traffic violation Is detected by the camera image.
Here, since the certainty of verifying the traffic violation is determined by the camera image, the certainty of the verification can be improved.
　第９の発明に係る交通違反管理システムは、第１、第２または第６の発明のいずれか１つに係る交通違反管理システムであって、交通違反に対する違反金の請求書類を作成する違反金請求書類作成手段を更に備え、違反金請求書類作成手段は、作成した違反金の請求書類を交通違反情報に関連付けて記憶手段に保存する。
　ここでは、交通違反情報を更に違反金請求書類に関連付けて保存するため、交通違反を取り締まる警察官等は、更に効率的に交通違反を処理することができる。 A traffic violation management system according to a ninth invention is the traffic violation management system according to any one of the first, second or sixth inventions, and is a violation fee for creating a claim document for a traffic violation fee. A billing document creation unit is further provided, and the violation bill request document creation unit stores the created billing document for the violation fee in the storage unit in association with the traffic violation information.
Here, since the traffic violation information is further stored in association with the violation billing document, a police officer or the like who controls the traffic violation can process the traffic violation more efficiently.
　第１０の発明に係る交通違反管理システムは、画像取得手段と、人物特定手段と、判定手段と、表示制御手段と、を備える。画像取得手段は、撮像手段により撮像された交通違反の時の画像を取得する。人物特定手段は、取得した画像から、交通違反が検出された車両の運転者および所有者および同乗者うちの少なくとも一の人物を特定する。判定手段は、取得した画像から、交通違反を証明できる確実性を判定する。表示制御手段は、少なくとも上記確実性と、確実性の判定に用いた画像と、人物特定手段により特定された人物の情報と、人物特定手段に用いられた画像とを交通違反毎に関連付けた交通違反情報を、確実性に応じた順番に画面に表示させる。
　ここでは、立証に要する情報だけでなくその立証の確実性も関連付けて表示される。このため、交通違反の取締りに必要な情報を効率的に表示することができる。よって、交通違反を取り締まる警察官等は、例えば、立証の確実性のある交通違反情報を優先的に確認することができる。 A traffic violation management system according to a tenth invention includes image acquisition means, person identification means, determination means, and display control means. The image acquisition means acquires an image at the time of traffic violation imaged by the imaging means. The person specifying means specifies at least one person among a driver, an owner, and a passenger of the vehicle in which the traffic violation is detected from the acquired image. The determination means determines the certainty that the traffic violation can be proved from the acquired image. The display control means is a traffic that associates at least the certainty, the image used for the determination of certainty, the information of the person specified by the person specifying means, and the image used for the person specifying means for each traffic violation. Violation information is displayed on the screen in order according to certainty.
Here, not only the information required for verification but also the certainty of the verification is displayed in association with each other. For this reason, it is possible to efficiently display information necessary for traffic violation control. Therefore, a police officer or the like who controls traffic violations can preferentially confirm traffic violation information with certainty of verification.
　第１１の発明に係る交通違反管理方法は、画像取得ステップと、人物特定ステップと、判定ステップと、記憶ステップと、画像取得ステップとを含む。画像取得ステップにおいては、撮像手段により撮像された交通違反の時の画像を取得する。人物特定ステップにおいては、取得した画像から交通違反が検出された車両の運転者および所有者および同乗者うちの少なくとも一の人物を特定する。判定ステップにおいては、取得した画像から、交通違反を証明できる確実性を判定する。記憶ステップにおいては、少なくとも上記確実性と、確実性の判定に用いた画像と、人物特定ステップにおいて特定された人物の情報と、人物特定ステップに用いられた画像とを関連付けた交通違反情報を、交通違反毎に保存する。 The traffic violation management method according to the eleventh invention includes an image acquisition step, a person identification step, a determination step, a storage step, and an image acquisition step. In the image acquisition step, an image at the time of traffic violation imaged by the imaging means is acquired. In the person specifying step, at least one person among the driver, the owner, and the passenger of the vehicle in which the traffic violation is detected from the acquired image is specified. In the determination step, the certainty that the traffic violation can be proved is determined from the acquired image. In the storing step, traffic violation information that associates at least the certainty, the image used for the determination of certainty, the information of the person specified in the person specifying step, and the image used in the person specifying step, Save every traffic violation.
　本交通違反管理方法は、交通違反が検出された画像に基づいて、人物特定ステップにおいて違反した人物を特定するともに、判定ステップにおいてその立証の確実性を判定し、立証に用いる画像と関連付けて保存する。つまり、本交通違反管理方法では、立証に要する情報だけでなくその立証の確実性も関連付けて保存される。このため、交通違反の取締りに必要な情報を効率的に管理することができる。よって、交通違反を取り締まる警察官等は、例えば、立証の確実性のある交通違反情報を優先的に抽出することができる。
（発明の効果）
　本発明に係る交通違反管理システムおよび交通違反管理方法によれば、交通違反の取締りに必要な情報を効率的に管理することが可能である。 The traffic violation management method specifies a person who has violated in the person specifying step based on the image in which the traffic violation is detected, determines the certainty of the verification in the determining step, and stores it in association with the image used for the verification. To do. That is, in this traffic violation management method, not only the information required for verification but also the certainty of the verification is stored in association with each other. For this reason, it is possible to efficiently manage information necessary for traffic violation control. Therefore, a police officer or the like who controls traffic violations can preferentially extract traffic violation information with certainty of verification.
(The invention's effect)
According to the traffic violation management system and the traffic violation management method according to the present invention, it is possible to efficiently manage information necessary for traffic violation control.
（ａ）および（ｂ）は、本発明の一実施形態に係る交通違反管理システムに対して撮像された画像を供給するカメラの設置例を示す図。(A) And (b) is a figure which shows the example of installation of the camera which supplies the image imaged with respect to the traffic violation management system which concerns on one Embodiment of this invention. 本実施形態に係る交通違反管理システムの全体構成を示すブロック図。The block diagram which shows the whole structure of the traffic violation management system which concerns on this embodiment. 図２の交通違反管理システムに含まれる立証確率判定手段の構成を示すブロック図。The block diagram which shows the structure of the verification probability determination means contained in the traffic violation management system of FIG. 図２の交通違反管理システムに含まれる人物特定手段の構成を示すブロック図。The block diagram which shows the structure of the person specific means contained in the traffic violation management system of FIG. （ａ）～（ｃ）は、図２の交通違反管理システムに含まれる表示手段の表示画面の切り替え表示の一例を示す図。(A)-(c) is a figure which shows an example of the display switching of the display screen of the display means contained in the traffic violation management system of FIG. 図２の交通違反管理方法システムによる立証確率判定処理の流れを示すフローチャート。The flowchart which shows the flow of the verification probability determination process by the traffic violation management method system of FIG. 図２の交通違反管理方法システムによる表示制御処理の流れを示すフローチャート。The flowchart which shows the flow of the display control processing by the traffic violation management method system of FIG. 本発明の交通違反管理システムの構成例を示す図。The figure which shows the structural example of the traffic violation management system of this invention.
　本発明の一実施形態に係る交通違反管理システム１００について、図１～図８を用いて説明すれば以下の通りである。
　＜１．交通違反管理システム１００の概要＞
　本実施形態に係る交通違反管理システム１００は、接続される交通違反取締装置によって取得される違反検出情報（交通違反の内容、場所、画像を含む）を取得し、同違反検出情報に基づき、交通違反の立証の確実性を判定し、立証確率に応じて交通違反情報を管理する。 A traffic violation management system 100 according to an embodiment of the present invention will be described below with reference to FIGS.
<1. Overview of Traffic Violation Management System 100>
The traffic violation management system 100 according to the present embodiment acquires violation detection information (including traffic violation contents, location, and images) acquired by a connected traffic violation control device, and based on the violation detection information, traffic Determine the certainty of proof of violation and manage traffic violation information according to the probability of proof.
　交通違反管理システム１００は、例えば、交通違反の取締りを行う警察署等に設置される。警察署では、本システム１００において交通違反の発生を検出した場合、警察官等が、後述するように抽出された画像を確認しながら交通違反として取締りの対象とするか否かの決定を行う。つまり、本交通違反管理システム１００は、警察官等が効率よく交通違反の処理を実施できるようにサポートするためのシステムとして活用される。実際に使用される際には、警察官等は、本システム１００と接続されたＰＣ等を用いて、１件ずつＰＣの表示画面を確認しながら、交通違反の処理が行われる。入力手段は、マウス、キーボード、タッチパネル等が用いられる。 The traffic violation management system 100 is installed, for example, in a police station that controls traffic violations. In the police station, when the occurrence of a traffic violation is detected in the system 100, a police officer or the like determines whether or not the traffic violation is subject to control while checking an extracted image as will be described later. That is, the traffic violation management system 100 is utilized as a system for supporting police officers and the like so that they can efficiently handle traffic violations. When actually used, a police officer or the like uses a PC or the like connected to the system 100 to process traffic violations while checking the display screen of the PC one by one. As the input means, a mouse, a keyboard, a touch panel or the like is used.
　交通違反管理システム１００は、所定の交通違反取締装置（例えば、自動速度違反取締り装置、自動車ナンバー自動読取装置、自動信号無視取締機等）に接続される。交通違反取締装置は、撮像手段としてのカメラを含み、交通違反管理システム１００に対して画像を供給する。
　カメラは、例えば、図１（ａ）に示すように、交差点における所定の位置に設置されるカメラ１０である。カメラ１０は、設置された道路およびその道路を走行する車両を含む画像を撮像する。そして、カメラ１０は、後述するように、交通違反管理システム１００に対して、撮像した画像を送信する。 The traffic violation management system 100 is connected to a predetermined traffic violation control device (for example, an automatic speed violation control device, an automobile number automatic reading device, an automatic signal ignore control device, etc.). The traffic violation control apparatus includes a camera as an imaging unit and supplies an image to the traffic violation management system 100.
The camera is, for example, a camera 10 installed at a predetermined position at an intersection as shown in FIG. The camera 10 captures an image including an installed road and a vehicle that travels on the road. And the camera 10 transmits the imaged image with respect to the traffic violation management system 100 so that it may mention later.
　カメラ１０は、例えば、取得される画像を用いて交通違反および人物を特定するために、交差点内を移動する車両正面および運転者の撮影が可能な位置に設置される。設置位置としては、例えば、図１（ａ）および図１（ｂ）に示すように、カメラ１０専用に設けられた支柱（逆Ｕ字型、Ｌ字型）１０２等に設置されてもよいし、信号機や街灯、歩道橋、標識等、既存の設備に取り付けられてもよい。
　なお、図示のように、カメラ１０はレーン毎に設置する必要はなく、複数レーンに１台であってもよいし、１レーンに複数台設定してもよい。 For example, in order to identify traffic violations and persons using acquired images, the camera 10 is installed at the front of a vehicle moving within an intersection and at a position where a driver can take a photograph. As the installation position, for example, as shown in FIG. 1A and FIG. 1B, it may be installed on a column (reverse U-shaped, L-shaped) 102 or the like provided exclusively for the camera 10. It may be attached to existing equipment such as traffic lights, street lights, pedestrian bridges, signs, etc.
As shown in the figure, it is not necessary to install the camera 10 for each lane. One camera may be provided for a plurality of lanes, or a plurality of cameras 10 may be set for one lane.
　＜２．本交通違反管理システム１００の構成＞
　本実施形態の交通違反管理システム１００は、交通違反検出時に撮像した画像（写真や映像を含む）を取得する。更に交通違反管理システム１００は、取得した画像から違反者を特定するとともに、交通違反の立証の確率を算出する。つまり、交通違反管理システム１００は、交通違反の立証確率に応じて情報を自動的に整理、保存し、表示することで、警察官等による交通違反の取締り効率を向上させる。なお、ここで違反者とは、車両の運転者、同乗者、車両の保有者等、各国において規定された法律等に基づいて定められる者であり、国や自治体ごとに特定対象が異なっていてもよい。 <2. Configuration of the Traffic Violation Management System 100>
The traffic violation management system 100 according to the present embodiment acquires an image (including a photograph and a video) captured when a traffic violation is detected. Further, the traffic violation management system 100 identifies the offender from the acquired image and calculates the probability of verifying the traffic violation. In other words, the traffic violation management system 100 automatically organizes, stores, and displays information according to the probability of traffic violation verification, thereby improving the efficiency of traffic violation control by a police officer or the like. In this case, the violator is a person who is determined based on the laws and regulations prescribed in each country, such as the driver of the vehicle, the passenger, the owner of the vehicle, etc. Also good.
　本実施形態において、検出される交通違反の内容（種別）とは、画像を用いて立証が可能な交通違反であって、例えば、信号無視、速度超過、通行禁止違反、通行区分違反、追い越し禁止違反、指定場所一時不停止、放置駐車違反、通行帯違反等が含まれる。
　交通違反管理システム１００は、図２に示すように、検出情報取得手段１１（画像取得手段の一例）と、立証確率判定手段１２（判定手段の一例）と、人物特定手段１３（人物特定手段の一例）と、違反金請求書類作成手段１４（違反金請求書類作成手段の一例）と、記憶手段１５（記憶手段の一例）と、表示制御手段１６（表示制御手段の一例）と、表示手段１７（表示手段の一例）と、を備えている。交通違反管理システム１００はまた、入力部１５０（入力部の一例）に接続される。 In the present embodiment, the detected traffic violation content (type) is a traffic violation that can be verified using an image. For example, signal ignorance, overspeed, prohibition of traffic violation, violation of traffic classification, prohibition of overtaking This includes violations, temporary suspension of designated locations, neglected parking violations, traffic zone violations, etc.
As shown in FIG. 2, the traffic violation management system 100 includes a detection information acquisition unit 11 (an example of an image acquisition unit), a verification probability determination unit 12 (an example of a determination unit), and a person identification unit 13 (a person identification unit). An example), a non-compliance claim document preparation means 14 (an example of a non-compliance claim request document preparation means), a storage means 15 (an example of storage means), a display control means 16 (an example of display control means), and a display means 17 (An example of display means). The traffic violation management system 100 is also connected to an input unit 150 (an example of an input unit).
　検出情報取得手段１１は、違反検出手段１９より違反情報を取得する。
　違反検出手段１９は、例えば、自動速度違反取締装置、自動車ナンバー自動読取装置、自動信号無視取締機等の交通違反取締装置であり、撮像手段であるカメラ１０（撮像手段の一例）を含む。これらの装置により交通違反が検出された場合、カメラ１０は対象車両のナンバープレートと運転者を撮像し、画像を生成する。ここで、自動速度違反取締装置は、例えば、レーダ式やループコイル式等があり、公知の技術を用いたもので良い。 The detection information acquisition unit 11 acquires violation information from the violation detection unit 19.
The violation detection means 19 is a traffic violation control apparatus such as an automatic speed violation control apparatus, an automobile number automatic reading apparatus, and an automatic signal ignore control apparatus, and includes a camera 10 (an example of an image pickup means) as an image pickup means. When a traffic violation is detected by these devices, the camera 10 captures the license plate and driver of the target vehicle and generates an image. Here, the automatic speed violation control apparatus includes, for example, a radar type and a loop coil type, and may use a known technique.
　なお、交通違反管理システム１００は、別のシステムに属する違反検出手段１９に接続されていてもよい。
　検出情報取得手段１１は、違反検出手段１９から違反検出情報を取得する。違反検出情報は、交通違反の内容（種別）と、交通違反が発生した場所、およびカメラ１０により撮像された画像（違反車両の画像や人物の画像）等、を含む。検出情報取得手段１１は、取得した画像を、立証確率判定手段１２および人物特定手段１３に対して送信する。 The traffic violation management system 100 may be connected to the violation detection means 19 belonging to another system.
The detection information acquisition unit 11 acquires violation detection information from the violation detection unit 19. The violation detection information includes the content (type) of the traffic violation, the location where the traffic violation has occurred, and the image captured by the camera 10 (an image of a violation vehicle or a person). The detection information acquisition unit 11 transmits the acquired image to the verification probability determination unit 12 and the person identification unit 13.
　検出情報取得手段１１は、取得した違反検出情報（画像データを含む）を一時的に保存する記憶部（図示省略）を備え、受信時間間隔やデータ量を調整した上で本システム１００による処理を開始するようにしてもよい。
　立証確率判定手段１２は、交通違反の内容や、違反車両が含まれる一つまたは複数の画像等の情報から、交通違反を立証するのに十分な情報が揃っているかどうかを判定し、その立証の確実性を判定するとともに、その立証確率を算出する。より具体的には、取得した交通違反の内容と、交通違反を撮影した画像の内容や鮮明さ等から、その交通違反を立証するための証拠として使用し得る画像が揃っているかを判定し、立証確率を算出する。画像の内容は、例えば、人物の顔が全て含まれているか、ナンバープレートが全て含まれているか、人の顔とナンバープレートとが一つの画像に含まれているか、全て含まれていない場合どの程度まで含まれているか、等を示す。また、各画像内容に加え、同一の違反を撮影した写真の枚数からも立証確率を算出する。 The detection information acquisition unit 11 includes a storage unit (not shown) that temporarily stores the acquired violation detection information (including image data), and performs processing by the system 100 after adjusting the reception time interval and the data amount. You may make it start.
The verification probability determination means 12 determines whether or not sufficient information for verifying the traffic violation is available from the content of the traffic violation and information such as one or a plurality of images including the vehicle in violation. The certainty is determined, and the verification probability is calculated. More specifically, based on the content of the traffic violation acquired and the content and clarity of the image of the traffic violation, it is determined whether there are images that can be used as evidence to prove the traffic violation. Calculate the probability of verification. The content of the image is, for example, when all faces of a person are included, all license plates are included, a person's face and license plate are included in one image, or not all Whether it is included to the extent. In addition to the contents of each image, the probability of verification is also calculated from the number of photographs taken of the same violation.
　立証確率判定手段１２は、後述する人物特定手段１３により人物が特定できた場合、交通違反毎に、人物特定手段１３により使用した画像や立証の判定に用いた画像、および人物特定手段１３により特定される人物情報等と、立証確率とを関連付けた交通違反情報を生成し、記憶手段１５に保存する。なお、立証確率判定手段１２の詳細な処理内容については、図３を用いて後段にて詳述する。 The verification probability determining means 12 specifies the image used by the person specifying means 13 or the image used for verification and the person specifying means 13 for each traffic violation when the person can be specified by the person specifying means 13 described later. The traffic violation information in which the personal information and the like to be associated with the verification probability is generated and stored in the storage unit 15. The detailed processing contents of the verification probability determination unit 12 will be described in detail later with reference to FIG.
　人物特定手段１３は、違反車両や交通違反に関連する人物を特定する。交通違反に関連する人物とは、違反車両の運転者、同乗者、所有者、違反車両の運転者の雇用主（企業等）等が含まれる。人物特定手段１３は、検出情報取得手段１１から受信した画像から読み取った車番情報と、予め記憶されている登録情報とを照会し、車両の持ち主を特定し、人物情報として出力する。また、人物特定手段１３は、公知の顔認証技術を用いて、画像から検出した運転者や同乗者の顔と、予め保有する免許証の写真情報とを照合し、違反した運転者や同乗者を特定する。人物特定手段１３は、特定した人物情報や車両情報を、立証確率判定手段１２に出力する。なお、人物特定手段１３が交通違反に関連する人物を特定する際の詳細な処理内容については、図４を用いて後段にて詳述する。 Person specifying means 13 specifies a person related to a violation vehicle or a traffic violation. The person related to the traffic violation includes a driver of the offending vehicle, a passenger, an owner, an employer (a company, etc.) of the driver of the offending vehicle, and the like. The person specifying unit 13 inquires the vehicle number information read from the image received from the detection information acquiring unit 11 and the registered information stored in advance, specifies the owner of the vehicle, and outputs it as person information. In addition, the person identification means 13 uses a known face authentication technique to collate the driver's or passenger's face detected from the image with the photo information of the license held in advance, and violates the driver or passenger. Is identified. The person specifying unit 13 outputs the specified person information and vehicle information to the verification probability determining unit 12. Detailed processing contents when the person specifying means 13 specifies a person related to the traffic violation will be described in detail later with reference to FIG.
　違反金請求書類作成手段１４は、交通違反毎に、交通違反の違反金（反則金）の請求書を作成する。より具体的には、違反金請求書類作成手段１４は、選択された交通違反の内容に基づいて、予め記憶された違反金に関する情報を参照し、違反金の金額を設定する。そして、違反金請求書類作成手段１４は、選択された交通違反で特定された人物情報に基づいて、請求書の送付先となる住所等を検出し、違反金請求書類を作成する。 The infringement fee claim document preparation means 14 creates an invoice for a traffic infringement fee (foul) for each traffic violation. More specifically, the breach money billing document creation means 14 refers to information on the breach money stored in advance based on the content of the selected traffic breach, and sets the amount of the breach money. Then, the non-compliance fee billing document creating means 14 detects an address or the like to which the invoice is to be sent based on the personal information specified by the selected traffic violation, and creates a non-violating bill request document.
　記憶手段１５は、立証確率判定手段１２が生成した交通違反情報を記憶する。なお、記憶手段１５は、例えば磁気記録装置、半導体メモリ等である。
　表示制御手段１６は、記憶手段１５に保存された交通違反情報を、立証確率の高いグループ順に表示するように、表示手段１７を制御する。
　表示手段１７は、例えば、液晶ディスプレイ等の表示装置であって、記憶手段１５に保存されている交通違反情報を立証確率に応じて表示する。なお、表示手段１７の表示画面における表示態様については、図５（ａ）から（ｃ）を用いて、後段にて詳述する。 The storage unit 15 stores the traffic violation information generated by the verification probability determination unit 12. The storage means 15 is, for example, a magnetic recording device, a semiconductor memory, or the like.
The display control means 16 controls the display means 17 so that the traffic violation information stored in the storage means 15 is displayed in the order of groups with the highest probability of verification.
The display unit 17 is a display device such as a liquid crystal display, for example, and displays traffic violation information stored in the storage unit 15 according to the probability of verification. The display mode on the display screen of the display unit 17 will be described in detail later with reference to FIGS.
　入力部１５０は、交通違反管理システム１００に接続されるマウス、キーボード、タッチパネル等により構成され、ユーザー（警察官等）によって操作される。入力部１５０の操作に応じて、違反金請求書類作成手段１４や表示制御手段１６等による機能が実行される。 The input unit 150 includes a mouse, a keyboard, a touch panel and the like connected to the traffic violation management system 100 and is operated by a user (a police officer or the like). In accordance with the operation of the input unit 150, functions by the non-compliance fee billing document creation means 14, the display control means 16, and the like are executed.
　＜２－１．立証確率判定手段１２の構成＞
　立証確率判定手段１２について、図３を用いて以下に説明する。
　立証確率判定手段１２は、図３に示すように、記憶手段１５の一部であるデータベース（ＤＢ）２１にアクセス可能である。
　ＤＢ２１は、交通違反を立証するための条件（立証に使える画像の条件を含む）に関する情報（立証条件）を記憶する立証条件記憶部２１１と、立証確率判定手段１２により生成される交通違反情報を記憶する交通違反情報記憶部２１２とを含む。 <2-1. Configuration of Verification Probability Determination Unit 12>
The verification probability determination means 12 will be described below with reference to FIG.
As shown in FIG. 3, the verification probability determination unit 12 can access a database (DB) 21 that is a part of the storage unit 15.
The DB 21 stores the traffic violation information generated by the verification condition storage unit 211 for storing information (validation conditions) related to the conditions for verifying the traffic violation (including image conditions that can be used for verification) and the verification probability determination means 12. And a traffic violation information storage unit 212 for storing.
　ここで、立証条件は、ＤＢ２１の立証条件記憶部２１１に記憶されている。立証条件は、例えば、違反車両や人物を撮影した写真や画像の枚数、写り具合、内容、鮮明さ等の条件項目を含み、条件項目毎に立証可能性の基準となる閾値を設定する。
　立証確率判定手段１２は、立証条件記憶部２１１に記憶されている立証条件を参照し、これらの条件項目をどの程度満たしているか、例えば、閾値以上であるかどうか、人物の判別は可能かどうか等を判定する。例えば、同一違反について、違反時の車番が確認できる写真と運転者の顔が確認できる写真の２枚がある場合は、立証確率１００％と算定される。また、同一違反について、違反時の写真が１枚あり、車番は明確であるものの運転者のおでこから上が撮影できていない場合は、立証確率８０％が算定される。なお、立証確率判定手段１２は、立証条件をほとんど満たさない場合、立証確率を算定せず、立証が不可として処理を終了してもよい。また、立証確率判定手段１２は、立証確率が所定未満（例えば、８０％未満）の場合、立証確率を算定せず、立証が不可として処理を終了してもよい。 Here, the verification conditions are stored in the verification condition storage unit 211 of the DB 21. The verification condition includes, for example, condition items such as the number of photographs and images taken of the violating vehicle or a person, the image quality, the content, and the sharpness, and a threshold value serving as a reference for verification possibility is set for each condition item.
The verification probability determination means 12 refers to the verification conditions stored in the verification condition storage unit 211, and to what extent these condition items are satisfied, for example, whether or not the threshold value is exceeded or not, and whether the person can be determined. Etc. are determined. For example, if there are two photos of the same violation, one for confirming the car number at the time of the violation and another for confirming the driver's face, the probability of verification is calculated as 100%. Also, for the same violation, if there is one photo at the time of the violation and the car number is clear but the top of the driver's forehead has not been photographed, a probability of 80% is calculated. Note that the verification probability determination unit 12 may not calculate the verification probability and may terminate the process because the verification is impossible when the verification conditions are hardly satisfied. In addition, when the verification probability is less than a predetermined value (for example, less than 80%), the verification probability determination unit 12 may end the process without calculating the verification probability and making verification impossible.
　人物の判別が可能な画像の条件として、例えば、運転者を判別する場合は、画像中の運転者の顔が鮮明で免許証の顔写真と十分に照合できることが考えられる。その他にも、車両の保有者を判別する場合は、画像中の違反車両の車両番号が鮮明で十分に読み取り可能であることが考えられる。
　上記立証条件は、国や自治体の法律、条例、運用等に応じた立証に必要な条件に基づいて予め記憶される。例えば、１枚の画像中に、特定可能な違反車両と運転者とが含まれていければならない、複数の画像を組み合わせた場合に各画像に特定可能な違反車両と人物とが立証可能な状態で含まれていなければならない、交通違反の立証には人物の写真が２枚以上なければならないといった条件である。また、運転者に対して取締りを行う国であれば、運転者のみを特定する条件（運転者の画像や写真の有無）が設定され、車両の所有者に対してのみ取締りを行う国であれば車両番号のみを特定する条件が設定される。かかる前提条件は、ＤＢ２１等に予め記憶される。立証確率判定手段１２は、記憶された前提条件を参照し、取得した違反検出情報が前提条件を満たしているかどうかを判定する。立証確率判定手段１２は、立証確率を判定する前に、前提条件を満たさない場合は、立証不可として処理を終了してもよい。なお、これらの前提条件は、本交通違反管理システム１００が導入される国や自治体の法律や運用等に基づいて適宜変更される。 For example, in the case of discriminating the driver, it is conceivable that the driver's face in the image is clear and can be sufficiently matched with the face photo of the license. In addition, when determining the owner of a vehicle, it is conceivable that the vehicle number of the violating vehicle in the image is clear and sufficiently readable.
The above-mentioned verification conditions are stored in advance based on the conditions necessary for verification according to the laws, regulations, operations, etc. of national and local governments. For example, an identifiable violation vehicle and driver must be included in a single image. When multiple images are combined, the identifiable violation vehicle and person can be verified in each image. In order to prove traffic violations, there must be at least two photographs of a person. In addition, if the country controls the driver, a condition that specifies only the driver (whether there is a driver's image or photo) is set, and the country controls the vehicle only. For example, a condition for specifying only the vehicle number is set. Such preconditions are stored in advance in the DB 21 or the like. The verification probability determination unit 12 refers to the stored precondition and determines whether the acquired violation detection information satisfies the precondition. If the precondition is not satisfied before the verification probability is determined, the verification probability determination unit 12 may terminate the process as a verification impossible. These preconditions are appropriately changed based on the laws and operations of the country or local government where the traffic violation management system 100 is introduced.
　立証条件は、証拠の重要度に応じて重み付けがなされていてもよい。例えば、ナンバープレートが画像中にあるとする条件項目が、取得された画像の枚数よりも重要度が高い場合、ナンバープレートの画像の鮮明性は立証への寄与度が高く、画像の枚数は立証への寄与度は低いと考えられる。この場合、前者の重み係数は大きく、後者の重み係数は小さく設定される。 The verification conditions may be weighted according to the importance of the evidence. For example, if the condition item that the license plate is in the image is more important than the number of acquired images, the clarity of the license plate image has a high contribution to the verification, and the number of images is verified. The contribution to is considered low. In this case, the former weight coefficient is set large and the latter weight coefficient is set small.
　このようにして、立証確率判定手段１２は、ＤＢ２１に記憶された立証条件と、取得された画像とを照合して、画像に含まれる対象車両が交通違反を犯したことを立証する確率を算定する。
　立証確率判定手段１２はまた、後述する人物特定手段１３により人物が特定できた場合、交通違反毎に、人物特定手段１３により使用した画像や立証の判定に用いた画像、および人物特定手段１３により特定される人物情報等と、立証確率とを関連付けた交通違反情報を生成する。そして立証確率判定手段１２は、生成した交通違反情報を交通違反情報記憶部２１２に保存する。交通違反情報は、立証確率ごとに交通違反情報が管理、出力可能なように保存される（立証確率１００％、立証確率８０％以上、立証確率８０％未満等）。なお、交通違反情報として保存される画像は、違反検出情報として取得した画像全てでなくともよく、その一部であってもよい。例えば、立証条件および／または上記前提条件に合致する画像、或いは後述する人物特定手段１３によって用いられた画像のみ保存するようにしてもよい。 In this way, the verification probability determination unit 12 compares the verification conditions stored in the DB 21 with the acquired image, and calculates the probability of verifying that the target vehicle included in the image has committed a traffic violation. To do.
The verification probability determination means 12 also uses an image used by the person identification means 13 or an image used for determination of verification for each traffic violation and the person identification means 13 when a person can be identified by the person identification means 13 described later. Traffic violation information that associates the identified personal information and the verification probability is generated. The verification probability determination unit 12 stores the generated traffic violation information in the traffic violation information storage unit 212. The traffic violation information is stored for each verification probability so that the traffic violation information can be managed and output (100% verification probability, 80% verification probability, less than 80% verification probability, etc.). Note that the image stored as traffic violation information may not be all the images acquired as violation detection information, or may be a part thereof. For example, only an image that matches the verification condition and / or the above preconditions, or an image that is used by the person specifying means 13 described later may be stored.
　立証条件記憶部２１１および交通違反情報記憶部２１２は、ＤＢ２１に設けられる必要はなく、他の接続可能な記憶装置（半導体メモリ、磁気記録媒体、光記録媒体等）に設けられていてもよい。 The verification condition storage unit 211 and the traffic violation information storage unit 212 do not need to be provided in the DB 21 and may be provided in another connectable storage device (semiconductor memory, magnetic recording medium, optical recording medium, etc.).
　＜２－２．人物特定手段１３の構成＞
　人物特定手段１３の詳細な構成について、図４を用いて以下に説明する。
　人物特定手段１３は、図４に示すように、記憶手段１５の一部であるデータベース（ＤＢ）２３にアクセス可能である。
　ＤＢ２３は、免許証情報記憶部２３１および自動車登録番号記憶部２３２を有する。免許証情報記憶部２３１は、運転免許取得者の顔写真、氏名、住所、生年月日等の情報を記憶する。自動車登録番号記憶部２３２は、自動車登録番号（ナンバープレート）、車両の名義人の氏名、住所等の情報を記憶する。 <2-2. Configuration of Person Identification Unit 13>
A detailed configuration of the person specifying means 13 will be described below with reference to FIG.
As shown in FIG. 4, the person specifying unit 13 can access a database (DB) 23 that is a part of the storage unit 15.
The DB 23 includes a license information storage unit 231 and an automobile registration number storage unit 232. The license information storage unit 231 stores information such as the face photograph, name, address, date of birth, etc. of the driver license holder. The automobile registration number storage unit 232 stores information such as an automobile registration number (number plate), the name of a vehicle owner, and an address.
　人物特定手段１３は、免許証情報記憶部２３１および自動車登録番号記憶部２３２を参照し、取得した違反検出情報における画像と照合することにより、交通違反を犯した違反車両に関連する人物（運転者、同乗者、所有者、使用者（企業等））を特定する。
　具体的には、人物特定手段１３は、例えば、画像に含まれる運転者、同乗者等の顔が、顔認証技術を用いて、免許証情報記憶部２３１に記憶された免許証の顔写真と一致するかどうかを判定する。その他にも、画像から検出された車両番号と、自動車登録番号記憶部２３２に記憶された車両情報とを照合し、違反車両の所有者等が特定する。人物特定手段１３は、特定した人物情報を立証確率判定手段１２に送信するとともに、人物特定に使用した画像は記憶手段１５に保存する。
　免許証情報記憶部２３１および自動車登録番号記憶部２３２は、ＤＢ２３に設けられる必要はなく、他の接続可能な記憶装置（半導体メモリ、磁気記録媒体、光記録媒体等）に設けられていてもよい。 The person specifying means 13 refers to the license information storage unit 231 and the automobile registration number storage unit 232, and collates with the image in the acquired violation detection information, so that the person (driver) , Passengers, owners, users (businesses, etc.).
Specifically, for example, the person specifying means 13 uses the face photograph of the driver's face stored in the driver's license information storage unit 231 using the face authentication technology for the face of the driver, passenger, etc. included in the image. Determine whether they match. In addition, the vehicle number detected from the image and the vehicle information stored in the automobile registration number storage unit 232 are collated, and the owner or the like of the violating vehicle specifies. The person specifying unit 13 transmits the specified person information to the verification probability determining unit 12 and stores the image used for specifying the person in the storage unit 15.
The license information storage unit 231 and the automobile registration number storage unit 232 do not have to be provided in the DB 23, and may be provided in another connectable storage device (semiconductor memory, magnetic recording medium, optical recording medium, etc.). .
　＜３．表示手段１７における表示態様＞
　本実施形態の交通違反管理システム１００では、上述のように、立証確率判定手段１２および人物特定手段１３によって、交通違反毎に立証確率が算出され、対応する画像やその他付随する情報と共に記憶手段１５に保存される。そして、表示制御手段１６は、入力部１５０による操作等に応じて、記憶手段１５（ＤＢ２１）に保存された交通違反情報を所定のフォーマットに変換し、表示手段１７に表示する。 <3. Display Mode in Display Unit 17>
In the traffic violation management system 100 of the present embodiment, as described above, the verification probability determination unit 12 and the person identification unit 13 calculate the verification probability for each traffic violation, and the storage unit 15 together with the corresponding image and other accompanying information. Saved in. Then, the display control means 16 converts the traffic violation information stored in the storage means 15 (DB 21) into a predetermined format in accordance with an operation by the input unit 150 and displays it on the display means 17.
　具体的には、液晶ディスプレイ等の表示手段１７の画面には、図５（ａ）～（ｃ）に示すように、交通違反に関する各種情報を表示する。
　図５（ａ）の画面１７ａは、本交通違反管理システム１００によって立証確率が算定された交通違反情報を、所定範囲の立証確率のグループ毎（図示例では、１００％、９９％～８０％、８０％未満）に件数を表示する例を示す。また、画面１７ａにおいては、立証確率が高いグループ順に上から並べられて表示されている。このため、ユーザー（警察官等）は、画面１７ａを見て、立証確率が高いグループを優先して選択することができる。なお、選択操作は、入力部１５０により行われる。ユーザーが画面１７ａを見て関心のある立証確率の高いグループを選択すると、画面１７ｂは図５（ｂ）の画面１７ｂに遷移する。 Specifically, as shown in FIGS. 5A to 5C, various types of information on traffic violations are displayed on the screen of the display unit 17 such as a liquid crystal display.
The screen 17a in FIG. 5A displays the traffic violation information for which the verification probability is calculated by the traffic violation management system 100 for each group of verification probabilities within a predetermined range (in the illustrated example, 100%, 99% to 80%, An example of displaying the number of cases in less than 80%) is shown. On the screen 17a, the screens are displayed in order from the group having the highest probability of verification. Therefore, a user (a police officer or the like) can preferentially select a group having a high verification probability by looking at the screen 17a. The selection operation is performed by the input unit 150. When the user views the screen 17a and selects an interested group with a high probability of verification, the screen 17b transitions to the screen 17b in FIG.
　図５（ｂ）の画面１７ｂは、図５（ａ）で選択された立証確率が高いグループ（立証確率１００％）の交通違反情報をリスト表示した例を示す。画面１７ｂでは、各交通違反情報に関する主要な情報（日付、違反種別、違反者名、場所等）が表示される。ここでは、交通違反情報のリストは、日付順、違反種別順、同一違反者の数が多い順等で表示するようにしてもよい。ユーザーが画面１７ｂを見て関心のある交通違反情報を選択すると、画面１７ｂは図５（ｃ）の画面１７ｃに遷移する。 The screen 17b in FIG. 5B shows an example in which the traffic violation information of the group having a high verification probability (100% verification probability) selected in FIG. 5A is displayed as a list. On the screen 17b, main information (date, violation type, violator name, location, etc.) regarding each traffic violation information is displayed. Here, the list of traffic violation information may be displayed in order of date, order of violation type, order with the same number of violators, etc. When the user views the screen 17b and selects the traffic violation information of interest, the screen 17b transitions to the screen 17c in FIG.
　図５（ｃ）の画面１７ｃは、図５（ｂ）で選択された交通違反情報の詳細な内容を示す。交通違反情報は、同図に示すように、例えば、交通違反の内容（種別）、違反場所、違反者名（少なくとも運転者および車両所有者の一方）、画像の撮像日時、違反を特定する画像（少なくとも人物および車両が特定できる画像）を含む。同図に示すように、画面１７ｃには、一つの交通違反情報が表示される。 The screen 17c in FIG. 5 (c) shows the detailed contents of the traffic violation information selected in FIG. 5 (b). As shown in the figure, the traffic violation information includes, for example, the content of the traffic violation (type), the location of the violation, the name of the offender (at least one of the driver and the vehicle owner), the date and time of image capture, and an image that identifies the violation. (At least an image that can identify a person and a vehicle). As shown in the figure, one traffic violation information is displayed on the screen 17c.
　本実施形態の交通違反管理システム１００では、以上のように、１つの交通違反を立証するために必要な情報（違反内容、人物および車両を特定するための画像、違反場所、画像の撮像日時等）と算定された立証確率とが記憶手段１５（ＤＢ２１）内に関連付けされた状態で保存される。このため、これらの関連付けされた情報を、立証確率に応じて表示手段１７に表示することができる。立証確率に応じて表示するとは、例えば、図５（ａ）の画面１７ａに示すように所定範囲の立証確率毎に交通違反件数を表示したり、立証確率の昇順または降順に交通違反情報を表示したりすることを含む。 In the traffic violation management system 100 of the present embodiment, as described above, information necessary to prove one traffic violation (violation content, image for specifying a person and a vehicle, violation location, image capturing date / time, etc.) ) And the calculated verification probability are stored in a state associated with each other in the storage unit 15 (DB21). For this reason, these associated information can be displayed on the display means 17 according to the verification probability. For example, the number of traffic violations is displayed for each verification probability within a predetermined range as shown in the screen 17a of FIG. 5A, or traffic violation information is displayed in ascending or descending order of the verification probability. Including doing.
　以上の表示制御により、本システム１００を用いて交通違反の取締りを行う警察官は、まず図５（ａ）に示す画面１７ａを確認して、立証確率の高いグループの交通違反情報を取得する。そして、図５（ｂ）に示す画面１７ｂにおいて、更に関心のある交通違反情報を選択して、図５（ｃ）においてその詳細を確認することができる。よって、警察官は、処理が早くできる可能性のある立証確率の高い案件から着手することができ、交通違反の取締り効率を従来よりも向上させることができる。 With the above display control, a police officer who controls traffic violations using the system 100 first confirms the screen 17a shown in FIG. 5A, and acquires traffic violation information of a group with a high probability of verification. Then, on the screen 17b shown in FIG. 5B, the traffic violation information of further interest can be selected and the details can be confirmed in FIG. 5C. Therefore, the police officer can start from a case with a high probability of probing that can be processed quickly, and can improve the efficiency of traffic violation control.
　＜４、交通違反管理システム１００の処理の流れ＞
　＜４－１．立証確率算定処理＞
　本実施形態の交通違反管理システム１００において、立証確率を算定し交通違反情報を生成する際の具体的な処理の流れについて、図６のフローチャートを用いて説明すれば以下の通りである。 <Processing flow of the traffic violation management system 100>
<4-1. Probability calculation process>
In the traffic violation management system 100 of the present embodiment, a specific processing flow when calculating the verification probability and generating the traffic violation information will be described with reference to the flowchart of FIG.
　本実施形態の交通違反管理システム１００では、図６に示すフローチャートに従って、以下の交通違反管理方法を実施する。
　ステップＳ６０１において、交通違反管理システム１００の検出情報取得手段１１は、違反検出手段１９より一つの違反検出情報を取得する。違反検出情報は、上述の通り、交通違反の内容（種別）と、交通違反が発生した場所、およびカメラ１０により撮像された画像を含む。交通違反内容（種別）とは、例えば、信号無視、速度超過、通行禁止違反、通行区分違反、追い越し禁止違反、指定場所一時不停止、放置駐車違反、通行帯違反等、画像を用いて立証が可能な交通違反である。違反検出を取得した場合、検出情報取得手段１１はステップＳ６０２に進む。 In the traffic violation management system 100 of this embodiment, the following traffic violation management method is implemented according to the flowchart shown in FIG.
In step S <b> 601, the detection information acquisition unit 11 of the traffic violation management system 100 acquires one violation detection information from the violation detection unit 19. The violation detection information includes the content (type) of the traffic violation, the location where the traffic violation has occurred, and the image captured by the camera 10 as described above. Traffic violation details (types) are, for example, verified using images such as signal ignorance, overspeed, traffic prohibition violation, traffic classification violation, overtaking prohibition violation, designated place temporary stoppage, neglected parking violation, traffic zone violation, etc. It is a possible traffic violation. When the violation detection is acquired, the detection information acquisition unit 11 proceeds to step S602.
　ステップＳ６０２において、検出情報取得手段１１は、違反検出情報に含まれる画像を取得し、立証確率判定手段１２および人物特定手段１３に送信する。
　ステップＳ６０３において、立証確率判定手段１２は、検出情報取得手段１１から取得された交通違反内容（種別）や画像を含む違反検出情報に基づき立証確率を算定する。具体的には、立証確率判定手段１２は、ＤＢ２１の立証条件記憶部２１１にアクセスし、取得した画像が立証条件をどの程度満たしているか、閾値以上であるかどうか、人物の判別が可能かどうか等判定する。 In step S <b> 602, the detection information acquisition unit 11 acquires an image included in the violation detection information and transmits the image to the verification probability determination unit 12 and the person identification unit 13.
In step S603, the verification probability determination unit 12 calculates the verification probability based on the violation detection information including the traffic violation content (type) and image acquired from the detection information acquisition unit 11. Specifically, the verification probability determination unit 12 accesses the verification condition storage unit 211 of the DB 21 to determine how much the acquired image satisfies the verification condition, whether it is equal to or greater than a threshold, and whether a person can be determined. Judge equally.
　立証条件は、例えば、例えば、違反車両や人物を撮影した写真や画像の枚数、写り具合、内容、鮮明さ等の条件項目毎に、閾値を設定する。
　立証確率判定手段１２は、例えば、同一違反について、違反時の車番が確認できる写真と運転者の顔が確認できる写真の２枚がある場合は、立証確率１００％と算定される。また、例えば、同一違反について、違反時の写真が１枚あり、車番は明確であるものの運転者のおでこから上が撮影できていない場合は、立証確率８０％が算定される。 As the verification condition, for example, a threshold value is set for each condition item such as the number of photographs or images taken of a violating vehicle or a person, the image quality, the content, and the clarity.
For example, if there are two photographs for the same violation, a photograph that allows confirmation of the vehicle number at the time of the violation and a photograph that allows confirmation of the driver's face, the verification probability determination means 12 is calculated as 100%. For example, for the same violation, if there is one photograph at the time of the violation and the car number is clear but the top of the driver's forehead has not been photographed, a probability of verification of 80% is calculated.
　立証確率判定手段１２が用いる立証条件は、上述したように、各国や自治体の法律や条例、運用等に応じて定められており、立証確率を判定する際に立証条件を満たしているかどうか判定する。
　立証確率判定手段１２は、立証条件をほとんど満たさない場合や車両や人物の判別できない場合は、立証確率を算定せず、立証が不可能として処理を終了してもよい。 As described above, the verification conditions used by the verification probability determination means 12 are determined according to the laws, ordinances, operations, etc. of each country or local government, and it is determined whether the verification conditions are satisfied when determining the verification probability. .
The verification probability determination means 12 may terminate the process because the verification probability is impossible without calculating the verification probability when the verification conditions are hardly satisfied or when the vehicle or the person cannot be determined.
　ステップＳ６０４において、人物特定手段１３は、取得した画像から交通違反に関連する人物を特定する。交通違反に関連する人物は、違反車両の運転者、同乗者、所有者、違反車両の運転者の雇用主（企業等）等が含まれる。人物特定手段１３は、これらの人物情報のうち少なくとも違反車両の運転者および所有者のうち少なくとも一方を特定する。
　人物特定手段１３は、取得した画像から読み取った車番情報と、ＤＢ２３の自動車登録番号記憶部２３２にアクセスして取得した登録情報と照合し、車両情報やその所有者を特定する。また、人物特定手段１３は、取得した画像から取得した運転者や同乗者の顔情報と、ＤＢ２３の免許証情報記憶部２３１にアクセスして取得した人物の顔情報とを照合し、運転者や同乗者を特定する。そして、人物特定手段１３は、特定した免許証番号、所有者、運転者、同乗者等の情報を立証確率判定手段に出力する。なお、特定された人物が複数の場合、例えば、所有者と運転者とが異なっている場合や運転者に加えて同乗者も特定できた場合、それぞれの情報を立証確率判定手段１２に出力し、人物特定に使用した画像を記憶手段１５に保存する。 In step S604, the person specifying unit 13 specifies a person related to the traffic violation from the acquired image. The person related to the traffic violation includes a driver of the violating vehicle, a passenger, an owner, an employer (a company, etc.) of the driver of the violating vehicle, and the like. The person specifying unit 13 specifies at least one of the driver and the owner of the offending vehicle among these pieces of person information.
The person specifying unit 13 compares the vehicle number information read from the acquired image with the registration information acquired by accessing the automobile registration number storage unit 232 of the DB 23, and specifies the vehicle information and its owner. In addition, the person specifying means 13 collates the driver and passenger face information acquired from the acquired image with the face information of the person acquired by accessing the license information storage unit 231 of the DB 23, and Identify passengers. Then, the person specifying means 13 outputs the specified license number, owner, driver, passenger information, etc. to the verification probability determining means. When there are a plurality of specified persons, for example, when the owner and the driver are different, or when the passenger can be specified in addition to the driver, the respective information is output to the verification probability determining means 12. The image used for the person identification is stored in the storage means 15.
　運転者および所有者のうち少なくとも一方を特定できた場合はステップＳ６０５に進み、特定できなかった場合は処理を終了する。
　ステップＳ６０５において、立証確率判定手段１２は、ステップＳ６０４において算出された立証確率と、人物特定手段１３により使用した画像や立証の判定に用いた画像、および人物特定手段１３により特定される人物情報等とを関連付けて交通違反情報を生成し、ＤＢ２１の交通違反情報記憶部２１２に保存する。 If at least one of the driver and the owner can be specified, the process proceeds to step S605, and if not specified, the process ends.
In step S605, the verification probability determining unit 12 determines the verification probability calculated in step S604, the image used by the person specifying unit 13, the image used for determining verification, the person information specified by the person specifying unit 13, and the like. To generate traffic violation information and store it in the traffic violation information storage unit 212 of the DB 21.
　＜４－２．表示制御処理＞
　次に、本実施形態の交通違反管理システム１００による交通違反情報の表示制御処理について図７を参照しながら説明する。
　ステップＳ７０１において、交通違反管理システム１００の表示制御手段１６は、ユーザー（取締りを行う警察官等）の入力部１５０（図２）の入力操作に応じて、画面１７ａ（図５（ａ））を表示手段１７に表示させる。ユーザーは、画面１７ａを見て、立証確率に応じて選択すべきグループを決める。 <4-2. Display control processing>
Next, traffic violation information display control processing by the traffic violation management system 100 of this embodiment will be described with reference to FIG.
In step S701, the display control means 16 of the traffic violation management system 100 displays the screen 17a (FIG. 5 (a)) in accordance with the input operation of the input unit 150 (FIG. 2) of the user (a police officer or the like who performs control). It is displayed on the display means 17. The user looks at the screen 17a and determines a group to be selected according to the verification probability.
　ステップＳ７０２において、ユーザーは入力部１５０を介して画面１７ａから、例えば「１．立証確率１００％」のグループを選択する。
　ステップＳ７０３において、表示制御手段１６は、ステップＳ７０３の入力部１５０の入力操作に応じて、表示手段１７の画面を画面１７ａから画面１７ｂ（図５（ｂ））に遷移させる。画面１７ｂは、立証確率判定手段１２により立証確率１００％と判定された交通違反情報のリストを表示する。ユーザーは、画面１７ｂを見て、関心のある交通違反情報を決める。 In step S <b> 702, the user selects, for example, a group of “1. Probability of 100%” from the screen 17 a via the input unit 150.
In step S703, the display control unit 16 changes the screen of the display unit 17 from the screen 17a to the screen 17b (FIG. 5B) in response to the input operation of the input unit 150 in step S703. The screen 17b displays a list of traffic violation information determined by the verification probability determination means 12 as a verification probability of 100%. The user determines the traffic violation information of interest by looking at the screen 17b.
　ステップＳ７０４において、ユーザーは入力部１５０を介して画面１７ｂから、関心のある一つの交通違反情報を選択する。
　ステップＳ７０５において、表示制御手段１６は、ステップＳ７０４の入力部１５０の入力操作に応じて、表示手段１７の画面を画面１７ｂから画面１７ｃ（図５（ｃ））に遷移させる。画面１７ｃは、選択された交通違反情報の詳細を表示する。ユーザーは、画面１７ｃを見て、交通違反の内容を確認し、最終的に違反者へ通告するかどうか（違反金を請求するかどうかを含む）を決める。 In step S704, the user selects one traffic violation information of interest from the screen 17b via the input unit 150.
In step S705, the display control means 16 changes the screen of the display means 17 from the screen 17b to the screen 17c (FIG. 5C) according to the input operation of the input unit 150 in step S704. The screen 17c displays details of the selected traffic violation information. The user looks at the screen 17c, confirms the content of the traffic violation, and finally decides whether to notify the offender (including whether to charge the offense).
　ステップＳ７０６において、ユーザーは、画面１７ｃに表示された交通違反について、違反者へ通告する場合は、入力部１５０を介して入力操作（画面上のボタンの選択等）を実行し、ステップＳ７０７に進む。通告しない場合はステップＳ７０８に進む。
　ステップＳ７０７においては、違反金請求書類作成手段１４は、ステップＳ７０６の入力操作に応じて、通告や請求先の住所等を含む違反金請求書類を作成する。具体的には、違反金請求書類作成手段１４は、選択された交通違反の内容に基づいて、予め記憶された違反金に関する情報を参照し、違反金の金額を算出する。そして、選択された交通違反で特定された人物情報に基づいて、請求書の送付先となる住所等を検出し、違反金請求書類を作成する。作成された違反金請求書類データは記憶手段１５に記憶される。違反金請求書類は、別途入力操作に応じて印刷等出力される。
　ステップＳ７０８において、表示制御手段１６は、入力部１５０を介して画面を終了させる操作があった場合は処理を終了し、他の画面へ戻る場合は指定された画面に戻る（ステップＳ７０９）。 In step S706, when notifying the violator of the traffic violation displayed on the screen 17c, the user performs an input operation (selecting a button on the screen, etc.) via the input unit 150, and proceeds to step S707. . If not notified, the process proceeds to step S708.
In step S707, the breach money claim document creation means 14 creates a breach money claim document including a notification, a billing address, etc. in response to the input operation in step S706. Specifically, the breach money claim document creation means 14 refers to information on the breach money stored in advance based on the content of the selected traffic breach, and calculates the amount of the breach money. Then, based on the personal information specified by the selected traffic violation, an address or the like to which the invoice is sent is detected, and a violation claim document is created. The created non-compliance claim data is stored in the storage means 15. The non-compliance billing document is printed out in response to a separate input operation.
In step S708, the display control means 16 ends the process when there is an operation to end the screen via the input unit 150, and returns to the designated screen when returning to another screen (step S709).
　＜５．効果等＞
　以上のように、本実施形態の交通違反管理システム１００および同システムにより実行される交通違反管理方法では、立証確率と、検出された交通違反毎に立証確率を算定し、交通違反を立証するために必要な情報（違反内容、特定用画像、その他の情報等）とが関連づけられて保存される。更に、本実施形態の交通違反管理システム１００および交通違反管理方法によれば、これらの情報を立証確率に応じて抽出し、表示させることができる。これにより、警察署等において、交通違反のうち立証確率が高い交通違反に関する情報を抽出することが可能となる。よって、立証確率が高い違反案件から警察官等が確認して違反金等の請求を行うことが出来るので、警察官等の交通違反の取締りの効率を従来よりも大幅に向上させることができる。 <5. Effect>
As described above, the traffic violation management system 100 and the traffic violation management method executed by the system according to the present embodiment calculate the verification probability and the verification probability for each detected traffic violation, and verify the traffic violation. Necessary information (violation content, image for identification, other information, etc.) is stored in association with each other. Furthermore, according to the traffic violation management system 100 and the traffic violation management method of this embodiment, these pieces of information can be extracted and displayed according to the verification probability. This makes it possible to extract information on traffic violations with a high probability of verification among traffic violations at a police station or the like. Therefore, since police officers can confirm and claim charges for violations from violation cases with a high probability of proof, the efficiency of traffic violation control by police officers and the like can be greatly improved compared to the prior art.
　［他の実施形態］
　以上、本発明の一実施形態について説明したが、本発明は上記実施形態に限定されるものではなく、発明の要旨を逸脱しない範囲で種々の変更が可能である。
　（Ａ）
　交通違反管理システム１００は、例えば、図８に示すような構成により実施されてもよい。 [Other Embodiments]
As mentioned above, although one Embodiment of this invention was described, this invention is not limited to the said embodiment, A various change is possible in the range which does not deviate from the summary of invention.
(A)
The traffic violation management system 100 may be implemented, for example, with a configuration as shown in FIG.
　交通違反管理システム１００は、インターネットやＬＡＮ（Ｌｏｃａｌ　Ａｒｅａ　Ｎｅｔｗｏｒｋ）、ＷＡＮ（Ｗｉｄｅ Ａｒｅａ Ｎｅｔｗｏｒｋ）等のネットワークＮにより外部の交通違反取締装置（違反検出手段１９）に接続される。交通違反管理システム１００はまた、記憶装置１６０に接続される。
　交通違反管理システム１００は、コンピュータ端末により構成され、ＣＰＵ（Ｃｅｎｔｒａｌ Ｐｒｏｃｅｓｓｉｎｇ Ｕｎｉｔ）１１０、ＲＡＭ（Ｒａｎｄｏｍ Ａｃｃｅｓｓ Ｍｅｍｏｒｙ）１２０、出力部１３０、通信部１４０、入力部１５０等を備えている。 The traffic violation management system 100 is connected to an external traffic violation control device (violation detection means 19) via a network N such as the Internet, a LAN (Local Area Network), or a WAN (Wide Area Network). The traffic violation management system 100 is also connected to the storage device 160.
The traffic violation management system 100 includes a computer terminal, and includes a CPU (Central Processing Unit) 110, a RAM (Random Access Memory) 120, an output unit 130, a communication unit 140, an input unit 150, and the like.
　ＣＰＵ１１０は、各種の演算処理等を実行するとともに、ＲＡＭ１２０に読み込まれて展開される所定の制御プログラムを実行する。この制御プログラムにより、交通違反管理システム１００の各手段（検出情報取得手段１１、立証確率判定手段１２、人物特定手段１３、違反金請求書類作成手段１４、表示制御手段１６等）の機能が実行される。
　ＲＡＭ１２０は、ＳＲＡＭ（Ｓｔａｔｉｃ ＲＡＭ）またはＤＲＡＭ（Ｄｙｎａｍｉｃ ＲＡＭ）等のメモリ素子で構成され、ＣＰＵ１１０の処理過程で発生したデータ等の記憶を行うものである。 The CPU 110 executes various arithmetic processes and the like, and executes a predetermined control program that is read into the RAM 120 and expanded. By this control program, the function of each means of the traffic violation management system 100 (detection information acquisition means 11, proof probability judgment means 12, person identification means 13, violation fee bill creation means 14, display control means 16, etc.) is executed. The
The RAM 120 is configured by a memory element such as SRAM (Static RAM) or DRAM (Dynamic RAM), and stores data generated during the processing of the CPU 110.
　出力部１３０は、画像および音声等のアナログ信号またはデジタル信号を伝送するケーブル等を接続する接続端子を有しており、これらのケーブルを介して上述した表示手段１７に接続されている。出力部１３０は、表示制御手段１６の指令に応じて記憶装置１６０から読み出された各種の情報を画像信号に変換し、ケーブルを介して表示手段１７へ出力する。 The output unit 130 has connection terminals for connecting cables or the like for transmitting analog signals or digital signals such as images and sounds, and is connected to the display means 17 described above via these cables. The output unit 130 converts various types of information read from the storage device 160 into image signals in accordance with instructions from the display control unit 16 and outputs the image signals to the display unit 17 via a cable.
　通信部１４０は、通信ケーブルを接続するための接続端子或いは無線通信インターフェースを有し、ネットワークＮに接続される。通信部１４０は、ネットワークＮに接続された交通違反取締装置（違反検出手段１９）やカメラ１０との間でデータの送受信を行う。
　入力部１５０は、（マウス、キーボード、画面上で操作するタッチパネル等）により構成される。入力部１５０は、ユーザーの操作による情報の入力およびメニューの選択等を受け付けて、受け付けた操作内容をＣＰＵ１１０へ通知する。
　記憶装置１６０は、半導体メモリ、磁気記録媒体、光記録媒体等により構成される。なお、上述の記憶手段１５は、この記憶装置１６０に含まれるものであってもよいし、別途接続された大容量記憶装置であってもよい。また、記憶装置１６０はネットワークを介して交通違反管理システム１００に接続されていてもよい。 The communication unit 140 has a connection terminal or a wireless communication interface for connecting a communication cable, and is connected to the network N. The communication unit 140 transmits / receives data to / from the traffic violation control device (violation detection unit 19) or the camera 10 connected to the network N.
The input unit 150 is configured by (a mouse, a keyboard, a touch panel operated on a screen, or the like). The input unit 150 accepts input of information by user operation, menu selection, and the like, and notifies the CPU 110 of the accepted operation content.
The storage device 160 includes a semiconductor memory, a magnetic recording medium, an optical recording medium, and the like. The storage means 15 described above may be included in the storage device 160, or may be a separately connected mass storage device. In addition, the storage device 160 may be connected to the traffic violation management system 100 via a network.
　（Ｂ）
　上記実施形態の交通違反管理システム１００では、交通違反を証明する確実性の判定として、立証確率判定手段１２により立証確率を算出しているが、必ずしも具体的な確率を算出しなくともよい。立証確率判定手段１２に代えて立証の可否を判定する判定手段を設けてもよい。この場合、例えば、立証確率判定手段１２に代わる判定手段は、取得した違反検出情報が、ＤＢ２１の立証条件記憶部２１１に記憶される立証条件を満たしているかどうかを判定する。これらの条件を満たしている場合、判定手段は、交通違反毎に人物特定手段１３により使用した画像や判定に用いた画像、および人物特定手段１３により特定される人物情報等を含む交通違反情報を生成し、記憶手段１５に保存する。その他の構成は、上記実施形態と同様である。
　上記構成によれば、立証が確実と判定された交通違反情報のみ記憶手段１５に記憶されるため、処理すべきデータ量を抑制することができ、警察官等の交通違反の取締りの効率を従来よりも向上させることができる。また、記憶手段１５における記憶データ量を抑えることができる。 (B)
In the traffic violation management system 100 of the above embodiment, the verification probability is calculated by the verification probability determination means 12 as the determination of certainty for proving the traffic violation, but it is not always necessary to calculate a specific probability. Instead of the verification probability determination unit 12, a determination unit that determines whether or not verification is possible may be provided. In this case, for example, a determination unit that replaces the verification probability determination unit 12 determines whether the acquired violation detection information satisfies a verification condition stored in the verification condition storage unit 211 of the DB 21. When these conditions are satisfied, the determination unit obtains traffic violation information including an image used by the person specifying unit 13 for each traffic violation, an image used for the determination, and personal information specified by the person specifying unit 13. Generated and stored in the storage means 15. Other configurations are the same as those in the above embodiment.
According to the above configuration, since only the traffic violation information that has been determined to be proved is stored in the storage means 15, the amount of data to be processed can be suppressed, and the efficiency of traffic violation control by a police officer or the like can be improved. Can be improved. In addition, the amount of data stored in the storage unit 15 can be suppressed.
　（Ｃ）
　上記実施形態の交通違反管理システム１００においては、人物特定手段１３により人物情報を取得してから、立証確率判定手段１２により立証確率を判定するようにしてもよい（図６のステップＳ６０３とＳ６０４を入れ替える）。人物特定手段１３により人物情報が取得できた場合は、立証確率判定手段１２により立証確率を判定する。人物情報が取得できなかった場合は、処理を終了する。 (C)
In the traffic violation management system 100 of the above embodiment, the person identification unit 13 may acquire the person information, and then the verification probability determination unit 12 may determine the verification probability (steps S603 and S604 in FIG. 6 are performed). Replace). When the person information can be acquired by the person specifying unit 13, the verification probability determination unit 12 determines the verification probability. If the person information cannot be acquired, the process ends.
　人物情報が取得できた場合であっても、例えば、取得できた画像の枚数が立証条件で指定される所定枚数より少ない場合には、交通違反を証明する確率は小さくなり、立証が不可能と判定される。また、例えば、立証条件で運転者と保有者の両方が特定されなければならないとされている場合に、人物情報として車両の所有者の情報が取得できたとしても、運転者が不鮮明で、その人物情報を取得できなければ、交通違反を証明する確率は小さくなり、立証が不可能と判定される。
　以上のような処理を行うことにより、人物が特定できている違反検出情報のみについて立証確率を算定することができるため、算定処理の効率を向上させることができる。 Even if the personal information can be acquired, for example, if the number of acquired images is less than the predetermined number specified in the verification condition, the probability of proving a traffic violation becomes small and verification is impossible. Determined. In addition, for example, when it is supposed that both the driver and the owner must be specified in the verification condition, even if the vehicle owner information can be acquired as the personal information, the driver is unclear, If the personal information cannot be acquired, the probability of proving the traffic violation is reduced and it is determined that the verification is impossible.
By performing the processing as described above, the verification probability can be calculated only for the violation detection information in which the person can be specified, so that the efficiency of the calculation processing can be improved.
　（Ｄ）
　上記実施形態の交通違反管理システム１００では、違反金請求書類作成手段１４は、入力部１５０を介して選択操作に応じて違反金請求書類を作成しているが、これに限定されない。違反金請求書類作成手段１４は、検出情報取得手段１１により違反検出情報が取得され、人物特定手段１３により人物情報が取得できた場合は、違反金請求書類を作成し、交通違反情報と共にＤＢ２１等に保存するようにしてもよい。この場合、表示制御手段１６が交通違反情報を表示手段１７に表示させるとき（図５の画面１７ｂや１７ｃ）、違反金額も併せて表示させるようにしてもよい。 (D)
In the traffic violation management system 100 of the above-described embodiment, the non-compliance fee claim document creating means 14 creates the non-conformity claim document according to the selection operation via the input unit 150, but is not limited thereto. If the violation detection information is acquired by the detection information acquisition unit 11 and the person information can be acquired by the person specifying unit 13, the violation bill request document generation unit 14 generates a violation fee request document and DB 21 etc. together with the traffic violation information. You may make it save to. In this case, when the display control means 16 displays the traffic violation information on the display means 17 ( screens 17b and 17c in FIG. 5), the violation amount may be displayed together.
　（Ｅ）
　上記実施形態の交通違反管理システム１００では、液晶ディスプレイ等の表示手段１７を含む構成を例として挙げて説明した。しかし、本発明はこれに限定されるものではない。
　例えば、液晶ディスプレイ等の表示手段を含まないシステムとして、本発明の交通違反管理システムを構成してもよい。 (E)
In the traffic violation management system 100 of the above embodiment, the configuration including the display means 17 such as a liquid crystal display has been described as an example. However, the present invention is not limited to this.
For example, the traffic violation management system of the present invention may be configured as a system that does not include display means such as a liquid crystal display.
　この場合には、外部装置として、液晶ディスプレイ等の表示手段を用いることで、簡素な構成により効率よく交通違反の取締りを実施することができるという、上記と同様の効果を得ることができる。
　また、交通違反管理システム１００は、表示手段１７を含み、記憶手段１５を含まないシステムとして構成されていてもよい。 In this case, by using a display means such as a liquid crystal display as an external device, it is possible to obtain the same effect as described above that it is possible to efficiently control traffic violations with a simple configuration.
The traffic violation management system 100 may be configured as a system that includes the display unit 17 and does not include the storage unit 15.
　（Ｆ）
　上記実施形態では、交通違反管理システム１００は、カメラ１０を含む違反検出手段１９によって違反検出情報を取得しているが、これに限定されない。例えば、一般の人からの携帯端末やカメラ画像を含む通報であってもよい。この場合であっても、人物特定手段１３により取得された画像や写真等から人物を特定し、立証確率判定手段１２により立証確率を算定可能である。 (F)
In the above embodiment, the traffic violation management system 100 acquires the violation detection information by the violation detection means 19 including the camera 10, but the present invention is not limited to this. For example, the report may include a mobile terminal or camera image from a general person. Even in this case, it is possible to specify a person from an image, a photograph or the like acquired by the person specifying unit 13 and calculate the verification probability by the verification probability determining unit 12.
　（Ｇ）
　上記実施形態では、外部の違反検出手段１９から送信される情報を用いて、警察署等において交通違反の立証確率を算定する交通違反管理システム１００を例として挙げている。しかし、本発明はこれに限定されるものではない。
　例えば、交通違反管理システム１００が違反検出手段を備えていてもよい。この場合、交通違反管理システム１００は、カメラ等の撮像手段から画像を取得し、同画像から交通違反を特定する。交通違反の特定方法としては、例えば、信号無視の場合には、カメラが設置された交差点等における信号機の切り替わりに関する情報に基づき信号無視違反を特定する。また、速度超過違反の場合には、カメラが設置された道路における制限速度に関する情報や、カメラ撮像速度等の情報に基づき速度超過違反を特定する。 (G)
In the above embodiment, the traffic violation management system 100 that calculates the probability of traffic violation at a police station or the like using information transmitted from the external violation detection means 19 is taken as an example. However, the present invention is not limited to this.
For example, the traffic violation management system 100 may include violation detection means. In this case, the traffic violation management system 100 acquires an image from imaging means such as a camera, and identifies a traffic violation from the image. As a traffic violation specifying method, for example, in the case of ignoring a signal, the signal ignoring violation is specified based on information related to switching of traffic lights at an intersection where a camera is installed. In the case of an overspeed violation, the overspeed violation is identified based on information on the speed limit on the road where the camera is installed, information on the camera imaging speed, and the like.
　（Ｈ）
　上記実施形態の交通違反管理システム１００において、表示制御手段１６は、ユーザーの入力操作に応じて、立証確率が低い（例えば、立証確率が５０％未満のもの）交通違反情報を表示手段１７に表示させてもよい。そして、ユーザーの入力操作に応じて選択された立証確率が低い交通違反情報は、交通違反情報記憶部２１２より削除してもよい。或いは、交通違反管理システム１００が立証確率が低い交通違反情報を自動的に削除または別の記憶装置に移動させるようにしてもよい。これにより、記憶手段１５の記憶データ量を抑えることができ、記憶容量を有効に使用することができる。 (H)
In the traffic violation management system 100 of the above-described embodiment, the display control unit 16 displays traffic violation information on the display unit 17 with a low probability of verification (for example, a probability of verification of less than 50%) according to a user input operation. You may let them. The traffic violation information with a low verification probability selected according to the user's input operation may be deleted from the traffic violation information storage unit 212. Alternatively, the traffic violation management system 100 may automatically delete or move traffic violation information with a low probability of verification to another storage device. Thereby, the amount of data stored in the storage unit 15 can be suppressed, and the storage capacity can be used effectively.
　（Ｉ）
　上記実施形態の交通違反管理システム１００は、様々な種別の交通違反を検出・管理することも可能である。かかる交通違反は、速度超過や信号無視の他、通行禁止・Ｕターン禁止違反、通行区分違反、逆走、追い越し禁止違反、指定場所一時不停止、放置駐車違反、通行帯違反、路線バス等優先通行帯違反、車間距離不保持、無灯火、携帯電話使用等を含む。 (I)
The traffic violation management system 100 according to the above embodiment can also detect and manage various types of traffic violations. Such traffic violations include speeding, signal ignorance, traffic prohibition / U-turn prohibition violation, traffic classification violation, reverse running, overtaking prohibition violation, designated place temporary stop, neglected parking violation, traffic zone violation, route bus, etc. Includes traffic zone violations, inability to maintain distances between vehicles, no lights, use of mobile phones, etc.
　（Ｊ）
　上記交通違反管理システム１００において、ＤＢ２１、２３は一つのデータベースにより構成されていてもよい。また、ＤＢ２１、２３は、交通違反管理システム１００の一部として含まれていてもよいし、別のシステムに含まれ交通違反管理システム１００がアクセス可能に設けられていてもよい。 (J)
In the traffic violation management system 100, the DBs 21 and 23 may be configured by a single database. The DBs 21 and 23 may be included as part of the traffic violation management system 100, or may be included in another system so that the traffic violation management system 100 can be accessed.
　（Ｋ）
　上記交通違反管理システム１００により実行される処理方法の実行順序は、必ずしも、上記実施形態の記載に制限されるものではなく、発明の要旨を逸脱しない範囲で、実行順序を入れ替えることができる。
　また、交通違反管理システム１００により実行される処理方法である交通違反管理方法、同方法をコンピュータに実行させるコンピュータプログラム、およびそのプログラムを記録したコンピュータ読み取り可能な記録媒体は、本発明の範囲に含まれる。ここで、コンピュータ読み取り可能な記録媒体としては、例えば、フレキシブルディスク、ハードディスク、ＣＤ－ＲＯＭ、ＭＯ、ＤＶＤ、ＤＶＤ－ＲＯＭ、ＤＶＤ－ＲＡＭ、ＢＤ（Ｂｌｕ－ｒａｙ（登録商標）　Ｄｉｓｃ）、半導体メモリを挙げることができる。また、コンピュータプログラムは、上記記録媒体に記録されたものに限られず、電気通信回線、無線または有線通信回線、インターネットを代表とするネットワーク等を経由して伝送されるものであってもよい。 (K)
The execution order of the processing methods executed by the traffic violation management system 100 is not necessarily limited to the description of the above embodiment, and the execution order can be changed without departing from the gist of the invention.
Further, a traffic violation management method that is a processing method executed by the traffic violation management system 100, a computer program that causes a computer to execute the method, and a computer-readable recording medium that records the program are included in the scope of the present invention. It is. Here, examples of the computer-readable recording medium include a flexible disk, a hard disk, a CD-ROM, an MO, a DVD, a DVD-ROM, a DVD-RAM, a BD (Blu-ray (registered trademark) Disc), and a semiconductor memory. Can be mentioned. The computer program is not limited to the one recorded on the recording medium, but may be transmitted via an electric communication line, a wireless or wired communication line, a network represented by the Internet, or the like.
　本発明の交通違反管理システムおよび方法は、交通違反の取締りに関する情報を効率的に検出・管理することができるという効果を奏する。よって、国や自治体に採用される交通違反管理システムとして広く活用が期待される。 The traffic violation management system and method of the present invention has the effect of being able to efficiently detect and manage information related to traffic violation control. Therefore, it is expected to be widely used as a traffic violation management system adopted by the national and local governments.
　１０　　　カメラ（撮像手段）
　１１　　　検出情報取得手段
　１２　　　立証確率判定手段
　１３　　　人物特定手段
　１４　　　違反金請求書類作成手段
　１５　　　記憶手段
　１６　　　表示制御手段
　１７　　　表示手段
　１７ａ～１７ｃ　表示画面
　１９　　　違反検出手段
　２１　　　ＤＢ（データベース）
　２３　　　ＤＢ（データベース）
１００　　　交通違反管理システム
１０１　　　信号機
１０１ａ　　支柱
１０２　　　専用支柱
１１０　　　ＣＰＵ
１２０　　　ＲＡＭ
１４０　　　通信部
１５０　　　入力部
１６０　　　記憶装置
２１１　　　立証条件記憶部
２１２　　　交通違反情報記憶部
２３１　　　免許証情報記憶部
２３２　　　自動車登録番号記憶部 10 Camera (imaging means)
DESCRIPTION OF SYMBOLS 11 Detection information acquisition means 12 Proof-of-probability determination means 13 Person identification means 14 Violation money claim document preparation means 15 Storage means 16 Display control means 17 Display means 17a-17c Display screen 19 Violation detection means 21 DB (database)
23 DB (database)
100 traffic violation management system 101 traffic light 101a post 102 dedicated post 110 CPU
120 RAM
140 communication unit 150 input unit 160 storage device 211 verification condition storage unit 212 traffic violation information storage unit 231 license information storage unit 232 automobile registration number storage unit

Claims (11)

  1. 　撮像手段により撮像された交通違反の時の画像を取得する画像取得手段と、
    　取得した画像から、前記交通違反が検出された車両の運転者および所有者および同乗者うちの少なくとも一の人物を特定する人物特定手段と、
    　前記取得した画像から、前記交通違反を証明できる確実性を判定する判定手段と、
    　少なくとも前記確実性と、前記確実性の判定に用いた画像と、前記人物特定手段により特定された人物の情報と、前記人物特定手段に用いられた画像とを関連付けた交通違反情報を、前記交通違反毎に保存する記憶手段と、
    を備えた、交通違反管理システム。     Image acquisition means for acquiring an image at the time of traffic violation imaged by the imaging means;
    A person identifying means for identifying at least one person among a driver and an owner and a passenger of the vehicle in which the traffic violation is detected from the acquired image;
    A determination means for determining certainty that the traffic violation can be proved from the acquired image;
    Traffic violation information associating at least the certainty, the image used for determining the certainty, the information of the person specified by the person specifying unit, and the image used for the person specifying unit, Storage means to save for each violation;
    Traffic violation management system with
  2. 　表示手段の画面に、前記確実性に応じた順番に前記交通違反情報を表示させる表示制御手段、
    を更に備えた、請求項１に記載の交通違反管理システム。     Display control means for displaying the traffic violation information in the order according to the certainty on the screen of the display means;
    The traffic violation management system according to claim 1, further comprising:
  3. 　前記交通違反情報は、前記判定手段により前記確実性があると判定され、かつ、前記人物特定手段により人物が特定できた場合に、前記記憶手段に保存される、
    請求項１または２に記載の交通違反管理システム。     The traffic violation information is stored in the storage means when it is determined that the certainty is determined by the determination means and a person can be specified by the person specifying means.
    The traffic violation management system according to claim 1 or 2.
  4. 　前記判定手段は、前記交通違反を証明できる確率を算出することにより前記確実性を判定する、
    請求項１または２に記載の交通違反管理システム。     The determination means determines the certainty by calculating a probability that the traffic violation can be proved;
    The traffic violation management system according to claim 1 or 2.
  5. 　前記判定手段は、所定範囲の前記確率毎に、複数の前記交通違反情報を整理して前記記憶手段に保存する、
    請求項４に記載の交通違反管理システム。     The determination means organizes a plurality of traffic violation information for each probability within a predetermined range and stores the traffic violation information in the storage means.
    The traffic violation management system according to claim 4.
  6. 　前記判定手段は、前記交通違反を証明できる確率を算出することにより前記確実性を判定し、
    　前記表示制御手段は、前記表示手段の画面に、所定範囲の前記確率毎に複数の前記交通違反情報を整理して表示させる、
    請求項２に記載の交通違反管理システム。     The determination means determines the certainty by calculating a probability that the traffic violation can be proved,
    The display control means arranges and displays a plurality of traffic violation information for each probability within a predetermined range on the screen of the display means.
    The traffic violation management system according to claim 2.
  7. 　入力操作を受け付ける入力部を更に備え、
    　前記表示制御手段は、前記入力部の入力操作によって選択される前記確実性に応じて交通違反情報を抽出し、前記表示手段に表示させる、
    請求項２または６に記載の交通違反管理システム。     An input unit for receiving an input operation;
    The display control means extracts traffic violation information according to the certainty selected by the input operation of the input unit, and displays the traffic violation information on the display means.
    The traffic violation management system according to claim 2 or 6.
  8. 　前記撮像手段は道路を撮像するカメラであり、
    　前記交通違反は前記カメラの画像に基づき検出される、
    請求項１、２、または６に記載の交通違反管理システム。     The imaging means is a camera for imaging a road;
    The traffic violation is detected based on the camera image;
    The traffic violation management system according to claim 1, 2, or 6.
  9. 　前記交通違反に対する違反金の請求書類を作成する違反金請求書類作成手段を更に備え、
    　前記違反金請求書類作成手段は、作成した違反金の請求書類を、前記交通違反情報に関連付けて前記記憶手段に保存する、
    請求項１、２または６に記載の交通違反管理システム。     And further comprising a non-compliance claim preparation means for preparing a non-compliance claim document for the traffic violation,
    The infringement fee claim document creating means stores the created infringement claim bill document in the storage means in association with the traffic violation information.
    The traffic violation management system according to claim 1, 2 or 6.
  10. 　撮像手段により撮像された交通違反の時の画像を取得する画像取得手段と、
    　取得した画像から、前記交通違反が検出された車両の運転者および所有者および同乗者うちの少なくとも一の人物を特定する人物特定手段と、
    　前記取得した画像から、前記交通違反を証明できる確実性を判定する判定手段と、
    　少なくとも前記確実性と、前記確実性の判定に用いた画像と、前記人物特定手段により特定された人物の情報と、前記人物特定手段に用いられた画像とを前記交通違反毎に関連付けた交通違反情報を、前記確実性に応じた順番に画面に表示させる表示制御手段と、
    を備えた、交通違反管理システム。     Image acquisition means for acquiring an image at the time of traffic violation imaged by the imaging means;
    A person identifying means for identifying at least one person among a driver and an owner and a passenger of the vehicle in which the traffic violation is detected from the acquired image;
    A determination means for determining certainty that the traffic violation can be proved from the acquired image;
    Traffic violation in which at least the certainty, the image used for determining the certainty, the information of the person specified by the person specifying means, and the image used for the person specifying means are associated for each traffic violation Display control means for displaying information on the screen in an order according to the certainty, and
    Traffic violation management system with
  11. 　撮像手段により撮像された交通違反の時の画像を取得する画像取得ステップと、
    　取得した画像から、前記交通違反が検出された車両の運転者および所有者および同乗者うちの少なくとも一の人物を特定する人物特定ステップと、
    　前記取得した画像から、前記交通違反を証明できる確実性を判定する判定ステップと、
    　少なくとも前記確実性と、前記確実性の判定に用いた画像と、前記人物特定ステップにおいて特定された人物の情報と、前記人物特定ステップに用いられた画像とを関連付けた交通違反情報を、前記交通違反毎に保存する記憶ステップと、
    を含む、交通違反管理方法。     An image acquisition step of acquiring an image at the time of the traffic violation imaged by the imaging means;
    A person identifying step for identifying, from the acquired image, at least one person among a driver and an owner and a passenger of the vehicle in which the traffic violation is detected;
    A determination step for determining certainty that the traffic violation can be proved from the acquired image;
    Traffic violation information associating at least the certainty, the image used for the determination of certainty, the information of the person specified in the person specifying step, and the image used in the person specifying step, A storage step to save for each violation;
    Including traffic violation management methods.
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