JP2020008924A - License plate recognition device, license plate recognition method, and program - Google Patents

Abstract

To suppress an increase of a processing load and a recognition leakage of a license plate.SOLUTION: A license plate recognition device includes a recognition section for performing license plate recognition processing from a moving image of a road surface on which mobile objects are traveling. When a congestion state of moving objects on a road surface is in a first state, the recognition section performs license plate recognition processing with respect to a first image selected from a moving image having a first frame rate, when a congestion state of mobile objects on a road surface is in a second state where a congestion level is higher than that of the first state, the recognition section performs license plate recognition processing with respect to a second image constituting a moving image that has a second frame rate lower than the first frame rate.SELECTED DRAWING: Figure 3

Description

  The present invention relates to a license plate recognition device, a license plate recognition method, and a program.

  In recent years, vehicle detection processing and license plate recognition processing provided on vehicles have been actively developed. For example, Patent Literature 1 discloses that a region corresponding to a different lane is cut out from each of a plurality of captured images obtained by repeatedly capturing images, a license plate is detected from the cut region, and any one of the lanes is used. There is disclosed a license plate detection device that changes an exposure amount for obtaining a captured image according to a captured image from which a region is cut out. In the license plate detection device, a single imaging device can detect a license plate from a wide area.

  Patent Literature 2 discloses a vehicle monitoring device that recognizes information described on a license plate using images obtained by a plurality of imaging units having different imaging directions. This vehicle monitoring device divides an image obtained by an imaging unit into a plurality of regions, cuts out an image from a specific region among the plurality of regions, detects a vehicle and recognizes a license plate in the cut-out image. I do. The extraction of the image is determined based on the vehicle type determination result, the vehicle speed measurement result, and the like.

JP-A-2006-95763 JP-A-2017-84417

  From the viewpoint of reducing the processing load and the accuracy of license plate recognition, an image to be recognized as a license plate is selected based on a change in a vehicle area in a moving image of a road surface, and a license plate recognition process is performed on the image. It is also conceivable to perform the method. However, in a traffic jam, a part of the vehicle is hidden by another vehicle, and the vehicle area is not detected. As a result, an image to be recognized as a license plate is not appropriately selected, and a license plate recognition omission occurs. Is concerned. On the other hand, if the license plate recognition process is performed on all the images constituting the moving image in the traffic congestion state, the processing load increases.

  Therefore, the present invention has been made in view of the above-described problems, and an object of the present invention is to provide a new and improved method capable of suppressing an increase in processing load and a recognition omission of a license plate. A license plate recognition device, a license plate recognition method, and a program are provided.

  In order to solve the above-described problems, according to an aspect of the present invention, there is provided a recognition unit that performs recognition processing of a license plate from a moving image of a road surface on which a moving object travels, and the recognition unit includes the moving object on the road surface. When the congestion state of the moving object is the first state, the recognition processing of the license plate is performed on the first image selected from the moving images having the first frame rate, and the congestion state of the moving object on the road surface is determined. In a second state in which the congestion degree is higher than the first state, a license plate of a second image forming a moving image having a second frame rate lower than the first frame rate is used. A license plate recognition device that performs a recognition process is provided.

  The license plate recognition device further includes an image selection unit that selects the first image from a group of images in which the moving object is detected among a group of images forming a moving image having the first frame rate. Is also good.

  The image selection unit is an image group corresponding to a time series position between an image in which the moving object is detected first and an image in which the moving object is detected last in an image group in which the moving object is detected. May be selected as the first image.

  The road surface has one or more lanes, and the recognition unit performs a license plate recognition process on an area corresponding to one lane in the first image, and performs the recognition process on the first image in the second image. The license plate recognition process may be performed on the area corresponding to the lane of the first lane and the area corresponding to the side of the one lane.

  The moving image of the road surface on which the moving object travels may be a moving image obtained by imaging the road surface from a side opposite to a traveling direction of the moving object.

  The license plate recognition device may further include a determination unit that determines a congestion state of the moving object on the road surface.

  The license plate recognition device, a detection unit that performs the detection processing of the moving object for an image group that constitutes a moving image of the road surface, and the detection of the moving object based on a change in the detection position of the moving object between images The apparatus may further include a speed measuring unit that measures a moving speed, wherein the determining unit may determine a congestion state of the moving object on the road surface based on a result of the measurement by the speed measuring unit.

  The license plate recognition device further includes an information acquisition unit configured to acquire information indicating a congestion state of the road surface, and the determination unit performs congestion of the moving object on the road surface based on the information acquired by the information acquisition unit. The state may be determined.

  The determination unit determines that the congestion state of the moving object on the road surface is the first state in the first time zone, and determines that the congestion state of the moving object on the road surface is the first state in the second time zone. The second state may be determined.

  According to another embodiment of the present invention, there is provided a license plate recognizing process including a process of recognizing a license plate from a moving image of a road surface on which a moving object travels. Performing a license plate recognition process on a first image selected from a moving image having a first frame rate when the congestion state of the moving object on the road surface is a first state; When the congestion state of the moving object on the road surface is a second state where the congestion degree is higher than the first state, a moving image having a second frame rate lower than the first frame rate is configured. Performing a license plate recognition process on the second image.

  According to another embodiment of the present invention, there is provided a computer configured to include a recognition unit configured to perform a license plate recognition process on a moving image of a road surface on which a moving object travels. When the congestion state of the moving object on the road surface is the first state, a license plate recognition process is performed on a first image selected from a moving image having a first frame rate, and When the congestion state of the moving object is the second state where the congestion degree is higher than the first state, the second image forming the moving image having the second frame rate lower than the first frame rate And a program for causing the device to function as a license plate recognizing device for performing license plate recognition processing.

  According to the present invention described above, it is possible to suppress an increase in processing load and omission of license plate recognition.

It is an explanatory view showing a license plate recognition system by an embodiment of the present invention. FIG. 4 is an explanatory diagram illustrating an example of an imaging range of an imaging unit. It is an explanatory view showing the composition of license plate recognition device 20 by an embodiment of the present invention. FIG. 9 is an explanatory diagram illustrating a specific example of a method of selecting a frame image in a normal state. It is explanatory drawing which shows the specific example of the selection method of the frame image in a traffic jam state. 4 is a flowchart illustrating an operation of the license plate recognition device 20 according to the embodiment of the present invention. It is explanatory drawing which shows the driving | running | working of the vehicle 10 in a traffic jam state. 9 is a flowchart showing the operation of the license plate recognition device 20 according to a first modification. FIG. 2 is a block diagram showing a hardware configuration of a license plate recognition device 20.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the specification and the drawings, components having substantially the same functional configuration are denoted by the same reference numerals, and redundant description is omitted.

  Further, in this specification and the drawings, a plurality of components having substantially the same function and configuration may be distinguished from each other by adding different alphabets after the same reference numeral. However, unless it is necessary to particularly distinguish each of a plurality of components having substantially the same functional configuration, each of the plurality of components is denoted by the same reference numeral.

<1. Overview of license plate recognition system>
Embodiments of the present invention relate to a license plate recognition system for recognizing a license plate of a vehicle traveling on a road surface. First, an outline of a license plate recognition system according to an embodiment of the present invention will be described with reference to FIGS.

  FIG. 1 is an explanatory diagram illustrating a license plate recognition system according to an embodiment of the present invention. As shown in FIG. 1, the vehicle includes a vehicle 10, a road surface imaging device 16, and a license plate recognition device 20. The road surface imaging device 16 and the license plate recognition device 20 are connected via the network 12. The network 12 is a wired or wireless transmission path for information transmitted from a device connected to the network 12. For example, the network 12 may include a public network such as the Internet, a telephone network, or a satellite communication network, various LANs (Local Area Network) including Ethernet (registered trademark), a WAN (Wide Area Network), and the like. Further, the network 12 may include a dedicated line network such as an IP-VPN (Internet Protocol-Virtual Private Network).

(vehicle)
The vehicle 10 is an example of a moving object, and runs on a road surface. The vehicle 10 has a license plate, and identification information for identifying the vehicle 10 is formed on the license plate. The identification information includes numbers, characters, place names, and the like. Although a four-wheeled vehicle is shown as the vehicle 10 in FIG. 1, the embodiment of the present invention can be applied to a two-wheeled vehicle, a bus, a truck, and the like.

(Road surface imaging device)
The road surface imaging device 16 is installed on the side of a road, and has a support frame 17 and an imaging unit 18. The support frame unit 17 supports the imaging unit 18 at a position where the imaging unit 18 can image the road surface from above. The imaging unit 18 captures an image of a road surface and acquires a moving image of the road surface. The imaging unit 18 may be a CCD (Charged-coupled devices) or a CMOS (Complementary metal-oxide-semiconductor). The imaging unit 18 is set to repeatedly image the road surface at a predetermined cycle, and images the road surface at an exposure time and a shutter speed according to an environmental change.

  Here, the imaging range of the imaging unit 18 will be described with reference to FIG. FIG. 2 is an explanatory diagram illustrating an example of an imaging range of the imaging unit 18. As shown in FIG. 2, the imaging range of the imaging unit 18 includes at least one lane area X. That is, the imaging unit 18 is supported by the support frame unit 17 so that the imaging range of the imaging unit 18 includes the lane area X.

  The road surface imaging device 16 transmits the moving image of the road surface acquired by the imaging unit 18 to the license plate recognition device 20 via the network 12. The transmission of the moving image of the road surface from the road surface imaging device 16 to the license plate recognition device 20 may be performed in real time, may be performed periodically, or may be performed in response to a request from the license plate recognition device 20. May be performed.

(License plate recognition device)
The license plate recognition device 20 recognizes a license plate of the vehicle 10 traveling on a road surface from a moving image of the road surface received from the road surface imaging device 16. The method of utilizing the license plate recognition result by the license plate recognition device 20 is not particularly limited. For example, the recognition result of the license plate may be transmitted to a server that processes the toll on the highway, and the server may execute the charging of the travel fee using the recognition result of the license plate.

<2. Configuration of license plate recognition device>
The outline of the license plate recognition system according to the embodiment of the present invention has been described above. Next, the configuration and operation of the license plate recognition device 20 according to the embodiment of the present invention will be sequentially described in detail.

  FIG. 3 is an explanatory diagram showing the configuration of the license plate recognition device 20 according to the embodiment of the present invention. As shown in FIG. 3, the license plate recognition device 20 according to the embodiment of the present invention includes a communication unit 220, a moving image storage unit 224, a vehicle detection unit 228, a speed measurement unit 232, a traffic jam determination unit 236, and an image selection unit 240. , A selected image storage unit 244 and a recognition unit 248.

(Communication department)
The communication unit 220 communicates with an external device. For example, the communication unit 220 receives a moving image of a road surface from the road surface imaging device 16. In addition, the communication unit 220 transmits the license plate recognition result obtained by the recognition unit 248 to an external device such as a server.

(Moving image storage unit)
The moving image storage unit 224 stores the moving image of the road surface received from the road surface imaging device 16 by the communication unit 220. The frame rate of the road moving image stored in the moving image storage unit 224 is not particularly limited, and may be, for example, 30 fps or 60 fps.

(Vehicle detector)
The vehicle detection unit 228 performs a detection process of the vehicle 10 on each frame image that forms the moving image of the road surface stored in the moving image storage unit 224. The vehicle detection unit 228 may detect the vehicle 10 by analyzing an optical flow of each frame image. Alternatively, the vehicle detection unit 228 may detect the vehicle 10 from each frame image using a discriminator for detecting the vehicle 10 obtained by machine learning. Specifically, the vehicle detection unit 228 may detect the vehicle 10 using the luminance gradient feature amount of the frame image and using a classifier that has learned in advance using the same luminance gradient feature amount. Here, the vehicle detection unit 228 may perform the detection processing of the vehicle 10 on all the frame images constituting the moving image stored in the moving image storage unit 224, or may store the detection processing in the moving image storage unit 224. The detection process of the vehicle 10 may be performed on a frame image group having a lower frame rate than the moving image that has been set. In this specification, the frame rate of a frame image group on which the vehicle detection unit 228 performs the detection processing of the vehicle 10 may be referred to as a first frame rate.

(Speed measurement unit)
The speed measuring unit 232 measures the moving speed of the vehicle 10 based on a change in the detection position of the vehicle 10 between successive frame images. Furthermore, the speed measuring unit 232 calculates, for each unit time such as one minute, ten minutes, or one hour, an average moving speed that is an average value of the moving speed of the vehicle 10 measured during the unit period.

(Congestion judgment section)
The congestion determination unit 236 determines the congestion state of the vehicle 10 on the road surface. The congestion determination unit 236 may determine the congestion state of the vehicle 10 based on the average traveling speed calculated by the speed measurement unit 232. For example, when the average traveling speed calculated by the speed measuring unit 232 exceeds the threshold, the congestion determining unit 236 determines that the congested state is the normal state (first state), and the congestion state is calculated by the speed measuring unit 232. If the average moving speed is equal to or less than the threshold, the congestion state may be determined to be a congestion state (second state) having a higher congestion degree than the normal state. The threshold value may be a value corresponding to a predetermined ratio of a legal speed set at a position where the road surface imaging device 16 is installed.

(Image selection section)
The image selection unit 240 selects a frame image from which a license plate is to be recognized by the recognition unit 248 from the moving images stored in the moving image storage unit 224. Here, the image selection unit 240 selects a frame image by a different method according to the result of the congestion determination by the congestion determination unit 236. Hereinafter, a method of selecting a frame image used in a normal state and a method of selecting a frame image used in a congested state will be described.

  In the normal state, since each vehicle 10 is hard to hide in another vehicle 10, it is expected that the detection of the vehicle 10 is performed with high accuracy. For this reason, in the normal state, if the vehicle 10 performs the license plate recognition processing on the detected frame image, the license plate recognition omission does not occur, and the license plate recognition is performed on all the frame images. The load of the recognition process can be significantly reduced as compared with the case where the process is performed.

  Further, since it is assumed that the same vehicle 10 is detected over a plurality of frame images, the vehicle 10 selects a frame image most suitable for license plate recognition from among the plurality of detected frame images. Is more desirable from the viewpoint of the load of the recognition processing. Here, according to a certain viewpoint, the frame image most suitable for recognizing the license plate is a frame image in which the vehicle 10 exists near the center. For this reason, in the normal state, the image selection unit 240 sets the time series of the middle (particularly, the center) between the first frame image in which the vehicle 10 is detected and the last frame image in which the vehicle 10 is detected. A frame image corresponding to the position may be selected. Hereinafter, a specific example of a method of selecting a frame image in such a normal state will be described with reference to FIG.

  FIG. 4 is an explanatory diagram showing a specific example of a method of selecting a frame image in a normal state. In the example shown in FIG. 4, the vehicle 10 is detected in the frame images f1 to f3, f4 to f6, and f7 to f9. In this example, the image selection unit 240 determines the center frame image f2 of the frame images f1 to f3, the center frame image f5 of the frame images f4 to f6, and the center frame of the frame images f7 to f9. Select the image f8.

  On the other hand, in a congested state, the vehicle 10 may not be detected because each vehicle 10 is hidden by another vehicle 10. For this reason, in a traffic congestion state, if the vehicle 10 performs the license plate recognition process on the detected frame image, the license plate may be missed. If a method of performing license plate recognition processing on all frame images constituting a moving image of a road surface is used, license plate recognition omission can be suppressed, but the processing load of the recognition processing becomes enormous in this method.

  For this reason, in a traffic jam state, the image selection unit 240 selects a frame image at a lower frame rate (second frame rate) than the frame rate of the moving image stored in the moving image storage unit 224. Hereinafter, a specific example of a method of selecting a frame image in such a congested state will be described with reference to FIG.

  FIG. 5 is an explanatory diagram showing a specific example of a method of selecting a frame image in a traffic jam state. The frame image group shown in FIG. 5 is a frame image group constituting a moving image stored in the moving image storage unit 224. The image selection unit 240 selects frame images from these frame image groups at regular intervals at a frame rate such as 30 fps, 15 fps, 4 fps, 2 fps, or 1 fps. In FIG. 5, the frame images selected by the moving image storage unit 224 are hatched. In the example illustrated in FIG. 5, when the frame rate of the frame image group is 60 fps, the frame rate of the frame image selected by the moving image storage unit 224 is 4 fps.

  The image selection unit 240 selects a frame image according to the above-described method according to the congestion state of the road surface. Then, in both the normal state and the traffic congestion state, the image selection unit 240 cuts out the lane area X described with reference to FIG. 2 from the selected frame image. Since the recognized lane region X is subjected to license plate recognition processing by the recognition unit 248, the extraction has the meaning of limiting the range in which license plate recognition processing is performed, and as a result, license plate recognition is performed. It is possible to reduce the processing load.

(Selected image storage unit)
The selected image storage unit 244 stores an image of the lane region extracted by the image selection unit 240 from among the frame images selected by the image selection unit 240. An image whose storage time in the selected image storage unit 244 has reached a certain time may be deleted, but the setting may be changed between a setting in which the image is deleted and a setting in which the image is not deleted. Good.

(Recognition unit)
The recognition unit 248 performs a license plate recognition process on the image stored in the selected image storage unit 244. That is, in the normal state, the recognizing unit 248 is in the middle (in particular, at the center) between the first frame image in which the vehicle 10 is detected from the moving image of the road surface and the last frame image in which the vehicle 10 is detected. A license plate recognition process is performed on the lane area included in the frame image corresponding to the series position. On the other hand, in a traffic congestion state, the recognition unit 248 performs a license plate recognition process on a lane region included in a frame image selected from a road surface moving image at a frame rate lower than the frame rate of the moving image. The recognition result of the license plate by the recognition unit 248 is transmitted from the communication unit 220 to the external device.

<3. Operation of license plate recognition device>
The configuration of the license plate recognition device 20 according to the embodiment of the present invention has been described above. Next, the operation of the license plate recognition device 20 according to the embodiment of the present invention will be described with reference to FIG.

  FIG. 6 is a flowchart showing the operation of the license plate recognition device 20 according to the embodiment of the present invention. As illustrated in FIG. 6, when the communication unit 220 starts receiving a moving image of the road surface from the road surface imaging device 16, the moving image storage unit 224 stores the moving image of the road surface received from the road surface imaging device 16 by the communication unit 220. It is stored (S304).

  Then, the vehicle detection unit 228 performs a detection process of the vehicle 10 on each frame image forming the moving image, and the speed measurement unit 232 calculates an average moving speed of the vehicle 10 (S308). Next, the congestion determination unit 236 determines the congestion state of the vehicle 10 based on the average traveling speed calculated by the speed measurement unit 232 (S312).

  When the congestion state is the normal state (S316 / normal state), the image selection unit 240 selects a frame image corresponding to the time-series position at the center of the frame section in which the vehicle 10 is detected (S320). On the other hand, when the congestion state is the congestion state (S316 / congestion state), the image selection unit 240 selects a frame image at a frame rate lower than the frame rate of the moving image stored in the moving image storage unit 224 ( S324). After S320 and after S324, the image selection unit 240 cuts out the lane region from the selected frame image, and the selected image storage unit 244 stores the cutout image of the lane region (S328).

  Then, the recognition unit 248 performs a license plate recognition process on the image stored in the selected image storage unit 244 (S332). The recognition result of the license plate by the recognition unit 248 is transmitted from the communication unit 220 to the external device (S336). Thereafter, the processing of S308 to S336 is repeated until the reception of the moving image from the road surface imaging device 16 is completed (S340).

<4. Effect>
According to the embodiment of the present invention described above, various effects can be obtained. For example, in the normal state, the vehicle 10 selects the most suitable frame image for license plate recognition among the plurality of detected frame images for license plate recognition processing. And the load of the recognition processing can be reduced. Further, in a traffic jam state, a frame image is selected at a frame rate lower than the frame rate of the moving image stored in the moving image storage unit 224 for the license plate recognition process. It is possible to suppress.

<5. Modification>
The embodiments of the present invention have been described above. Hereinafter, some modified examples of the embodiment of the present invention will be described. Each of the modified examples described below may be applied to the embodiment of the present invention alone, or may be applied to the embodiment of the present invention in combination. Further, each modification may be applied instead of the configuration described in the embodiment of the present invention, or may be additionally applied to the configuration described in the embodiment of the present invention.

(First Modification)
In the above, the example in which the image selecting unit 240 cuts out the lane region X described with reference to FIG. 2 from the frame image has been described. The first modified example is a modified example related to cutting out an area from a frame image. Hereinafter, the background that led to the recall of the first modification will be described with reference to FIG.

  FIG. 7 is an explanatory diagram illustrating traveling of the vehicle 10 in a traffic jam state. As shown in FIG. 7, in a traffic jam state, the vehicle 10v, which is a four-wheeled vehicle, runs in the lane. On the other hand, in a traffic jam state, the vehicle 10b, which is a two-wheeled vehicle, can travel on the side of the lane and pass through the vehicle 10v, which is a four-wheeled vehicle. The license plate of the motorcycle passing through the vehicle 10v may not be recognized from the image of the lane region X in some cases.

  Therefore, the image selecting unit 240 according to the first modified example cuts out the lane area X from the frame image in the normal state, and the areas Y1 and Y2 corresponding to the side of the lane area X in addition to the lane area X in the traffic jam state. From the frame image. The side part of the lane area X may be another lane area adjacent to the lane area X, or may be a road side or a road shoulder. Further, depending on the configuration of the road shoulder, the regions Y1 and Y2 may partially overlap the lane region X, or may be provided separately from the lane region X. With such a configuration, it is possible to prevent the license plate from being missed by the vehicle 10b, which is a motorcycle, in a traffic jam state. Since the vehicle 10b, which is a two-wheeled vehicle, generally has a license plate on the back, in the first modified example, the imaging unit 18 captures an image of the road surface from the opposite side in the traveling direction of the vehicle 10 as shown in FIG. Hereinafter, the operation of the license plate recognition device 20 according to the first modification will be summarized with reference to FIG.

  FIG. 8 is a flowchart showing the operation of the license plate recognition device 20 according to the first modification. Since the processing of S304 to S316 is substantially the same as the processing of S304 to S316 described with reference to FIG. 6, the detailed description of the processing of S304 to S316 is omitted here.

  When the congestion state is the normal state (S316 / normal state), the image selection unit 240 selects a frame image corresponding to the time-series position at the center of the frame section in which the vehicle 10 is detected (S320). Then, the image selection unit 240 cuts out the lane region from the selected frame image, and the selected image storage unit 244 stores the cutout image of the lane region (S328).

  On the other hand, when the congestion state is the congestion state (S316 / congestion state), the image selection unit 240 selects a frame image at a frame rate lower than the frame rate of the moving image stored in the moving image storage unit 224 ( S324). Then, the image selecting unit 240 cuts out the lane region and the side region from the selected frame image, and the selected image storage unit 244 stores the cut image of the lane region and the side region (S330).

  Then, the recognition unit 248 performs a license plate recognition process on the image stored in the selected image storage unit 244 (S334). The recognition result of the license plate by the recognition unit 248 is transmitted from the communication unit 220 to the external device (S336). Thereafter, the processing of S308 to S336 is repeated until the reception of the moving image from the road surface imaging device 16 is completed (S340).

  According to such a first modification, even when the vehicle 10 which is a two-wheeled vehicle is traveling on the side of a lane such as a lane boundary or a road shoulder in a traffic jam state, the license plate of the vehicle 10 can be recognized. Is possible. On the other hand, in the normal state, the processing load of the recognition processing can be reduced by not setting the side of the lane as the target of the license plate recognition processing.

  In the above description, an example in which the lane area and the side area are recognized after the lane area and the side area are extracted has been described. However, the extraction and the recognition processing may be sequentially performed for each area. For example, after the image selection unit 240 cuts out the lane area and the recognition unit 248 performs a license plate recognition process on the lane area, the image selection unit 240 cuts out the side area, and the recognition unit 248 sets the side area. On the other hand, a license plate recognition process may be performed. Conversely, after the image selection unit 240 cuts out the side area and the recognition unit 248 performs license plate recognition processing on the side area, the image selection unit 240 cuts out the lane area, and the recognition unit 248 sets the lane area. May be subjected to license plate recognition processing. Since the two-wheeled vehicle traveling in the regions Y1 and Y2 is considered to be traveling at a relatively high speed, a recognition process different from the license plate recognition process in the traffic lane region X may be performed. For example, similarly to the license plate recognition process in the lane area X in the normal state, the frame rate such as the frame rate of the moving image stored in the moving image storage unit 224 is higher than the frame rate used in the traffic lane area X. A configuration may be adopted in which a frame image most suitable for license plate recognition is selected from among a plurality of detected frame images of the vehicle 10b, which is a two-wheeled vehicle, using the frame images acquired at the frame rate and recognition is performed.

(Second Modification)
In the above, the example in which the congestion determination unit 236 determines the congestion state of the road surface based on the average traveling speed of the vehicle 10 has been described. The second modified example relates to another method for determining the congestion state of the road surface.

  For example, the communication unit 220 may receive congestion information from a server that distributes the congestion information, and the congestion determination unit 236 may determine the congestion state of the road surface based on the congestion information received by the communication unit 220. Alternatively, when there is statistical data such as a day of the week and a time zone during which traffic congestion occurs at the position where the road surface imaging device 16 is installed, a first time zone in which the normal operation mode is enabled based on the statistical data. , And a second time zone in which the operation mode in the traffic congestion state is enabled. Then, the congestion determination unit 236 may determine that the congestion state of the road surface is the normal state in the first time zone, and may determine that the congestion state of the road surface is the normal state in the first time zone. .

  According to the second modification, the vehicle detection unit 228 and the speed measurement unit 232 do not need to perform the vehicle detection process and the average moving speed calculation process in a traffic jam state. For this reason, according to the second modification, it is possible to reduce the processing load of the license plate recognition device 20 in a traffic jam state.

(Third Modification)
In the above, the example in which the congestion state has two stages of the normal state and the congestion state has been described. However, the stage of the congestion state is not limited to two stages. For example, the stage of the congestion state may be three or more stages such as a normal state, a light congestion state, and a heavy congestion state. In this case, the image selection unit 240 may select a frame image from a moving image at a lower frame rate as the degree of traffic congestion increases. According to such a configuration, the processing load of the license plate recognition device 20 can be reduced as a whole.

(Fourth modification)
Although the example in which the embodiment of the present invention is applied to one lane has been described above, the embodiment of the present invention is also applicable to a plurality of lanes. For example, it is possible to perform license plate recognition processing on a plurality of lanes by providing a plurality of imaging units 18 on a road and analyzing a moving image obtained by each imaging unit 18.

<6. Hardware Configuration>
The embodiments of the present invention have been described above. Information processing such as vehicle detection and license plate recognition described above is realized by cooperation between software and hardware of the license plate recognition device 20 described below.

  FIG. 9 is a block diagram showing a hardware configuration of the license plate recognition device 20. The license plate recognition device 20 includes a CPU (Central Processing Unit) 201, a ROM (Read Only Memory) 202, a RAM (Random Access Memory) 203, and a host bus 204. The license plate recognition device 20 includes a bridge 205, an external bus 206, an interface 207, an input device 208, a display device 209, an audio output device 210, a storage device (HDD) 211, a drive 212, A network interface 215.

  The CPU 201 functions as an arithmetic processing device and a control device, and controls overall operations in the license plate recognition device 20 according to various programs. Further, the CPU 201 may be a microprocessor. The ROM 202 stores programs used by the CPU 201, operation parameters, and the like. The RAM 203 temporarily stores programs used in the execution of the CPU 201, parameters that appropriately change in the execution, and the like. These are interconnected by a host bus 204 composed of a CPU bus and the like. By the cooperation of the CPU 201, the ROM 202, the RAM 203, and the software, the functions of the above-described vehicle detection unit 228, speed measurement unit 232, traffic congestion determination unit 236, image selection unit 240, recognition unit 248, and the like can be realized.

  The host bus 204 is connected to an external bus 206 such as a PCI (Peripheral Component Interconnect / Interface) bus via a bridge 205. Note that the host bus 204, the bridge 205, and the external bus 206 do not necessarily have to be separately configured, and these functions may be mounted on one bus.

  The input device 208 includes an input unit for a user to input information, such as a mouse, a keyboard, a touch panel, a button, a microphone, a sensor, a switch and a lever, and an input that generates an input signal based on an input by the user and outputs the input signal to the CPU 201. It is composed of a control circuit and the like. By operating the input device 208, the user of the license plate recognition device 20 can input various data to the license plate recognition device 20 and instruct a processing operation.

  The display device 209 includes a display device such as a CRT (Cathode Ray Tube) display device, a liquid crystal display (LCD) device, a projector device, an OLED (Organic Light Emitting Diode) device, and a lamp. The audio output device 210 includes an audio output device such as a speaker and headphones.

  The storage device 211 is a data storage device configured as an example of a storage unit of the license plate recognition device 20 according to the present embodiment. The storage device 211 may include a storage medium, a recording device that records data on the storage medium, a reading device that reads data from the storage medium, a deletion device that deletes data recorded on the storage medium, and the like. The storage device 211 is composed of, for example, a hard disk drive (HDD) or a solid storage drive (SSD), or a memory having an equivalent function. The storage device 211 drives a storage and stores programs executed by the CPU 201 and various data. The storage device 211 corresponds to the moving image storage unit 224 and the selected image storage unit 244.

  The drive 212 is a reader / writer for a storage medium, and is built in or externally attached to the license plate recognition device 20. The drive 212 reads information recorded on a removable storage medium 24 such as a mounted magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, and outputs the information to the RAM 203 or the storage device 211. The drive 212 can also write information to the removable storage medium 24.

  The network interface 215 is a communication interface including, for example, a communication device for connecting to the network 12. The network interface 215 may be a wireless LAN (Local Area Network) compatible communication device or a wire communication device that performs wired communication.

<7. Supplement>
As described above, the preferred embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to such examples. It is apparent that those skilled in the art to which the present invention pertains can conceive various changes or modifications within the scope of the technical idea described in the appended claims. It is understood that these also belong to the technical scope of the present invention.

  For example, each step in the processing of the license plate recognition device 20 in this specification does not necessarily need to be processed in a time-series manner in the order described in the flowchart. For example, each step in the process of the license plate recognition device 20 may be processed in an order different from the order described in the flowchart, or may be processed in parallel.

  In addition, a computer program for causing hardware such as a CPU, a ROM, and a RAM built in the license plate recognition device 20 to perform the same functions as those of the above-described configuration of the license plate recognition device 20 can be created. Also, a storage medium storing the computer program is provided.

Reference Signs List 10 vehicle 12 network 16 road surface imaging device 17 support frame unit 18 imaging unit 20 license plate recognition device 220 communication unit 224 moving image storage unit 228 vehicle detection unit 232 speed measurement unit 236 congestion determination unit 240 image selection unit 244 selection image storage unit 248 Recognition unit

Claims (11)

A recognition unit that performs recognition processing of a license plate from a moving image of a road surface on which a moving object travels,
The recognition unit,
When the congestion state of the moving object on the road surface is the first state, a license plate recognition process is performed on a first image selected from a moving image having a first frame rate;
When the congestion state of the moving object on the road surface is a second state where the congestion degree is higher than the first state, a moving image having a second frame rate lower than the first frame rate is configured. A license plate recognition device that performs a license plate recognition process on a second image.   The license plate recognition device further includes an image selection unit that selects the first image from a group of images in which the moving object is detected among a group of images forming a moving image having the first frame rate. The license plate recognition device according to claim 1.   The image selection unit is an image group corresponding to a time series position between an image in which the moving object is detected first and an image in which the moving object is detected last in an image group in which the moving object is detected. The license plate recognition device according to claim 2, wherein the first image is selected as the first image. The road surface has one or more lanes,
The recognition unit,
In the first state, a license plate recognition process is performed on an area corresponding to one lane in the first image,
4. The license plate recognition process according to claim 1, wherein in the second state, a license plate recognition process is performed on an area corresponding to the one lane and an area corresponding to a side portion of the one lane in the second image. The license plate recognition device according to any one of the preceding claims.   The license plate recognition device according to claim 4, wherein the moving image of the road surface on which the moving object travels is a moving image obtained by imaging the road surface from a side opposite to a traveling direction of the moving object.   The license plate recognition device according to any one of claims 1 to 5, wherein the license plate recognition device further includes a determination unit that determines a congestion state of the moving object on the road surface. The license plate recognition device,
A detection unit that performs the detection processing of the moving object on an image group forming a moving image of the road surface,
A speed measurement unit that measures a moving speed of the moving object based on a change in a detection position of the moving object between images,
The license plate recognition device according to claim 6, wherein the determination unit determines a congestion state of the moving object on the road surface based on a result of the measurement by the speed measurement unit. The license plate recognition device further includes an information acquisition unit that acquires information indicating the congestion state of the road surface,
The license plate recognition device according to claim 6, wherein the determination unit determines a congestion state of the moving object on the road surface based on information acquired by the information acquisition unit.   The determination unit determines that the congestion state of the moving object on the road surface is the first state in the first time zone, and determines that the congestion state of the moving object on the road surface is the first state in the second time zone. The license plate recognition device according to claim 6, wherein the license plate recognition device determines the second state. Including performing license plate recognition processing from a moving image of the road surface on which the moving object travels,
Performing the license plate recognition process,
When the congestion state of the moving object on the road surface is the first state, performing license plate recognition processing on a first image selected from a moving image having a first frame rate;
When the congestion state of the moving object on the road surface is a second state where the congestion degree is higher than the first state, a moving image having a second frame rate lower than the first frame rate is configured. Performing license plate recognition processing on the second image;
License plate recognition methods, including: Computer
A recognition unit that performs recognition processing of a license plate from a moving image of a road surface on which a moving object travels,
The recognition unit,
When the congestion state of the moving object on the road surface is the first state, a license plate recognition process is performed on a first image selected from a moving image having a first frame rate;
When the congestion state of the moving object on the road surface is a second state where the congestion degree is higher than the first state, a moving image having a second frame rate lower than the first frame rate is configured. A program for functioning as a license plate recognition device that performs a license plate recognition process on the second image.

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