Vehicle management device, system, method, and program

Abstract

The present invention makes it possible to efficiently inspect whether or not a vehicle is damaged, according to the type of vehicle. An image acquisition means (31) acquires a first image captured at a first time using a camera (50). The image acquisition means (31) also acquires a second image captured at a second time using the camera (50). A vehicle type information acquisition means (32) acquires vehicle type information of a vehicle. An image processing means (33) compares the first image and the second image using an image processing logic corresponding to the acquired vehicle type information. A detection means (34) detects damage caused to the vehicle on the basis of the result of the comparison by the image processing means (33).

Description

[Technical field]

[0001] FIELD OF THE DISCLOSURE The present disclosure relates to vehicle management devices, systems, methods, and computer readable media. [Background technology]

[0002] Generally, a user who rents a vehicle from a rental car company visually checks the vehicle for scratches, dents, and other damage together with an employee (clerk) of the rental car company at the rental car company's store before renting the vehicle. When the vehicle is returned, the user and the clerk visually check the vehicle for scratches again. By checking the vehicle for scratches both before and after renting the vehicle, if there is a scratch on the vehicle, it is possible to determine whether the scratch was made by the user or was there before the vehicle was rented.

[0003] As a related technique, Patent Document 1 discloses a vehicle management server that manages vehicles such as rental cars that are lent to users. In Patent Document 1, a user terminal equipped with a camera is used to check for scratches. The user terminal is configured as a tablet terminal or a smartphone with a dedicated application installed. Before using a rental car, the user uses the user terminal to take images of the front, rear, left and right sides of the vehicle. The user terminal transmits the captured images (pre-ride images) to the vehicle management server. When returning the rental car, the user uses the user terminal to take images of the front, rear, left and right sides of the vehicle. The user terminal transmits the captured images (post-ride images) to the vehicle management server.

[0004] The vehicle management server compares the pre-boarding image with the post-boarding image. The vehicle management server determines whether there is a change between the pre-boarding image and the post-boarding image that is equal to or greater than a set threshold. When the vehicle management server determines that there is a change between the pre-boarding image and the post-boarding image that is equal to or greater than the threshold, it transmits a vehicle confirmation alert to the administrator terminal, indicating that the vehicle may have been damaged, such as new scratches or dents. In Patent Document 1, the vehicle rental company can appropriately manage whether the user has caused damage, such as scratches or dents, to the vehicle by using the images transmitted from the user terminal. In addition, the user can prove that he or she has not caused any new damage, such as scratches or dents, to the vehicle while using the vehicle. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 6830690 Summary of the Invention [Problem to be solved by the invention]

[0006] Generally, rental car companies own vehicles of multiple models, and vehicles rented to users are not of a single model. When inspecting for damage using camera images, it is considered that the appearance of the vehicle in the camera images changes depending on the model. In this case, it is considered that image comparison cannot be performed efficiently if the same image processing logic is used to compare images of vehicles of different models. In Patent Document 1, pre-boarding images and post-boarding images are taken by the user, and the difference in the appearance of the vehicle in those images depending on the model is not taken into consideration. Therefore, the vehicle management server described in Patent Document 1 cannot efficiently inspect whether or not the vehicle is damaged depending on the model.

[0007] In view of the above circumstances, one of the objectives of the present disclosure is to provide a vehicle management device, system, method, and computer-readable medium that can efficiently inspect whether a vehicle has been damaged according to the vehicle type. [Means for solving the problem]

[0008] In order to achieve the above object, the present disclosure provides, as a first aspect, a vehicle management device, which includes an image acquisition means for acquiring, using one or more cameras that capture images of a vehicle to be rented to a user, a first image captured before the vehicle is rented to the user and a second image captured using the cameras after the vehicle is rented to the user, a vehicle model information acquisition means for acquiring vehicle model information of the vehicle, an image processing means for comparing the first image with the second image using image processing logic according to the acquired vehicle model information, and a detection means for detecting damage caused to the vehicle based on a result of the comparison in the image processing means.

[0009] The present disclosure provides a vehicle management system as a second aspect. The vehicle management system includes one or more cameras that capture images of a vehicle rented to a user, and a vehicle management device used to manage the vehicle. The vehicle management device includes an image acquisition means that acquires a first image captured by the camera before the vehicle is rented to the user, and a second image captured by the camera after the vehicle is rented to the user, a vehicle model information acquisition means that acquires vehicle model information of the vehicle, an image processing means that compares the first image with the second image using image processing logic according to the acquired vehicle model information, and a detection means that detects damage caused to the vehicle based on a result of the comparison in the image processing means.

[0010] The present disclosure provides, as a third aspect, a vehicle management method, which includes: acquiring, using one or more cameras that photograph a vehicle to be rented to a user, a first image taken before the vehicle is rented to the user and a second image taken using the cameras after the vehicle is rented to the user, acquiring vehicle type information of the vehicle, comparing the first image with the second image using image processing logic according to the acquired vehicle type information, and detecting damage caused to the vehicle based on a result of the comparison.

[0011] The present disclosure provides, as a fourth aspect, a computer-readable medium, which stores a program for causing a computer to execute a process including: acquiring, using one or more cameras that capture images of a vehicle to be rented to a user, a first image captured before the vehicle is rented to the user, and a second image captured using the cameras after the vehicle is rented to the user, acquiring vehicle model information of the vehicle, comparing the first image with the second image using image processing logic according to the acquired vehicle model information, and detecting damage caused to the vehicle based on a result of the comparison. Effect of the Invention

[0012] The vehicle management device, system, method, and computer-readable medium according to the present disclosure can efficiently inspect whether or not a vehicle has been damaged according to the vehicle type. [Brief description of the drawings]

[0013] [Figure 1] 1 is a block diagram showing a schematic configuration of a vehicle management system according to the present disclosure. [Diagram 2] FIG. 1 is a block diagram illustrating a vehicle management system according to an embodiment of the present disclosure. [Diagram 3] FIG. 1 is a schematic diagram showing an example of camera arrangement. [Figure 4] FIG. 4 is a diagram showing an example of reservation information. [Diagram 5] FIG. 4 is a diagram showing an example of vehicle information. [Figure 6] FIG. 4 is a block diagram showing an example of the configuration of an image processing unit. [Figure 7] 4 is a flowchart showing an operation procedure in the vehicle management device. [Figure 8] FIG. 1 is a block diagram showing an example of the configuration of a computer device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Prior to describing the embodiments of the present disclosure, an overview of the present disclosure will be described. Fig. 1 shows a schematic configuration of a vehicle management system according to the present disclosure. The vehicle management system 10 has a vehicle management device 30 and one or more cameras 50. The camera 50 is a camera that photographs vehicles rented to users. The vehicle management device 30 is a device used to manage vehicles rented to users.

[0015] The vehicle management device 30 has an image acquisition means 31, a vehicle type information acquisition means 32, an image processing means 33, and a detection means 34. The image acquisition means 31 acquires a first image taken by the camera 50 at a first time. The image acquisition means 31 also acquires a second image taken by the camera 50 at a second time that is later than the first time.

[0016] Vehicle type information acquisition means 32 acquires vehicle type information of the vehicle to be rented to the user. Image processing means 33 compares the first image with the second image using image processing logic according to the vehicle type information acquired by vehicle type information acquisition means 32. Detection means 34 detects damage caused to the vehicle based on the result of the comparison in image processing means 33.

[0017] In the present disclosure, the image processing means 33 compares the first image and the second image using image processing logic according to the vehicle type information of the vehicle. For example, if the first image and the second image are compared using the same image processing logic when the vehicle is large and when it is small, it may not be possible to accurately and efficiently compare the images. In contrast, in the present disclosure, the images are compared using image processing logic according to the vehicle type. Therefore, the present disclosure can efficiently inspect whether or not the vehicle is damaged.

[0018] Hereinafter, an embodiment of the present disclosure will be described in detail with reference to the drawings. Note that the following description and drawings are omitted and simplified as appropriate for clarity of explanation. In addition, in each drawing, the same elements and similar elements are given the same reference numerals, and duplicate explanations are omitted as necessary.

[0019] FIG. 2 illustrates a vehicle management system according to an embodiment of the present disclosure. The vehicle management system 100 includes a vehicle management device 110, a database 130, and a camera 150. The vehicle management device 110 is a device for managing vehicles such as rental cars that are rented out to users. The camera 150 photographs the vehicles that are rented out to users. The camera 150 is disposed, for example, in each of a plurality of stores of a rental car company. Note that, although only one camera 150 is illustrated in FIG. 1, the number of cameras 150 is not limited to one. A plurality of cameras 150 may be disposed in one store. The vehicle management device 110 corresponds to the vehicle management device 30 illustrated in FIG. 1. The camera 150 corresponds to the camera 50 illustrated in FIG. 1.

[0020] FIG. 3 shows an example of the arrangement of the cameras 150. In the example of FIG. 3, four cameras 150A-150D are arranged in the photographing area 200. The vehicle 210 is a vehicle that is rented to a user. The camera 150A photographs the vehicle 210 from the front side of the vehicle. The camera 150B photographs the right side of the vehicle 210. The camera 150C photographs the left side of the vehicle 210. The camera 150D photographs the vehicle 210 from the rear side of the vehicle. Instead of using multiple fixed cameras 150A-150D, the camera 150 may be moved to photograph the vehicle 210 from multiple directions.

[0021] The photographing area 200 is a damage check zone, and is provided, for example, in an aisle through which a vehicle rented to a user or a vehicle returned passes. A plurality of photographing areas 200 (damage check zones) may be provided in a store (departure store) from which a vehicle is rented to a user. A plurality of photographing areas 200 (damage check zones) may also be provided in a store (return store) where a user returns a vehicle. The photographing area 200 may be provided in a parking lot. The photographing area 200 may be surrounded by a fence or the like so that the brightness of the image is not affected by the weather.

[0022] When the vehicle 210 is rented to a user, the vehicle 210 is photographed in the photographing area 200 using the cameras 150A-150D. For example, when the user rents the vehicle, the user moves the vehicle 210 to the photographing area 200, which is a scratch check zone set up in a store. If another vehicle is already present in the photographing area 200, the user waits in front of the photographing area 200. After the image of the vehicle 210 is photographed using the cameras 150A-150D, the user drives the vehicle 210 and starts moving.

[0023] When the user returns the vehicle 210, the vehicle 210 is photographed by the cameras 150A-150D in the photographing area 200. For example, when the user returns the vehicle 210 to a store, the user moves the vehicle 210 to the photographing area 200, which is a scratch check zone. After an image of the vehicle 210 is photographed in the photographing area 200, the user performs a procedure for returning the vehicle 210. Note that the rental store and the return store do not necessarily have to be the same, and may be different. For example, the user may rent the vehicle 210 in City A and return the vehicle 210 in City B.

[0024] 2, the database 130 includes a reservation DB (database) 131 and a vehicle DB 132. The reservation DB 131 is a database that stores reservation information of users. The vehicle DB 132 is a database that stores information (vehicle information) of the vehicle 210 rented to the user.

[0025] FIG. 4 shows an example of reservation information. In the example of FIG. 4, the reservation information includes a reservation ID (Identifier), a reservation time, an image at departure, an image at return, and a determination result. The reservation ID is identification information for uniquely identifying the reservation information. The vehicle number indicates the registration number of the vehicle 210 rented to the user. The reservation time indicates the reservation date and time. The image at departure indicates identification information of an image taken by the camera 150 when the vehicle 210 (see FIG. 3) is rented. The image at return indicates identification information of an image taken by the camera 150 when the vehicle 210 is returned. The determination result indicates the determination result of the presence or absence of damage, which will be described later. The reservation information may further include a departure store and a return store. The reservation information may include the presence or absence of an insurance / compensation contract such as CDW (Collision Damage Waiver).

[0026] Fig. 5 shows an example of vehicle information. In the example of Fig. 5, the vehicle information includes a vehicle number, a vehicle type, and a color. The vehicle number indicates the registration number of the vehicle 210. The vehicle type indicates the vehicle type of the vehicle 210. The vehicle type indicates, for example, the vehicle name or model name of the vehicle 210. The color indicates color information of the vehicle 210.

[0027] Returning to FIG. 2 again, the vehicle management device 110 has an image acquisition unit 111, a vehicle information acquisition unit 112, an image processing unit 113, and a damage detection unit 114. The vehicle management device 110 is configured as a computer device such as a server having one or more memories and one or more processors. At least a part of the functions of each unit in the vehicle management device 110 can be realized by the processor operating according to a program read from the memory. Each unit of the vehicle management device 110 does not necessarily have to be physically located in the same device. The vehicle management device 110 may be configured, for example, by multiple computer devices connected to each other via a network. The vehicle management device 110 is located, for example, in a rental car company's store or management center. The vehicle management device 110 may be a cloud server.

[0028] The image acquisition unit 111 acquires an image of the vehicle 210 taken by using the camera 150. The image acquisition unit 111 acquires, for example, images of the front, rear, right side, and left side of the vehicle 210. The image acquisition unit 111 acquires an image (first image) of the vehicle 210 taken at a first time and an image (second image) of the vehicle 210 taken at a second time. The first time is, for example, a time before the vehicle is lent to the user. The second time is a time when the user returns the vehicle 210. Here, the "time when the user returns the vehicle 210" includes a time when the vehicle 210 returns to the store for return, and also includes a time when the return procedure of the vehicle 210 has not been completed. The first image is, for example, taken at the departure store at the time of departure. The second image is, for example, taken at the return store at the time of return. The image acquisition unit 111 corresponds to the image acquisition means 31 shown in FIG. 1.

[0029] The vehicle information acquisition unit 112 acquires vehicle information of the vehicle 210. The vehicle information includes vehicle model information of the vehicle 210. The vehicle information acquisition unit 112 acquires, for example, identification information of the vehicle 210, and acquires the vehicle model information based on the acquired identification information. For example, the registration number of the vehicle 210 is used as the identification information of the vehicle 210. For example, the vehicle information acquisition unit 112 acquires the registration number (vehicle number) from an image of a license plate included in an image captured by the camera 150. The vehicle information acquisition unit 112 refers to the vehicle DB 132 (see FIG. 5 ) and acquires the vehicle model (vehicle name) associated with the acquired vehicle number as the vehicle model information. The vehicle information acquisition unit 112 may acquire color information of the vehicle 210 from the vehicle DB 132.

[0030] Alternatively, the vehicle information acquisition unit 112 may acquire vehicle type information using the reservation DB 131 and the vehicle DB 132. In this case, the vehicle information acquisition unit 112 acquires a vehicle number associated with the user's reservation ID from the reservation DB 131 (see FIG. 4). The vehicle information acquisition unit 112 refers to the vehicle DB 132 and acquires the vehicle type associated with the acquired vehicle number as vehicle type information. Note that the method of acquiring the vehicle identification information is not limited to the above-mentioned method. For example, the vehicle information acquisition unit 112 may acquire the identification information from an RFID (Radio Frequency IDentification) tag attached to the vehicle 210. The vehicle information acquisition unit 112 corresponds to the vehicle type information acquisition means 32 shown in FIG. 1.

[0031] The image processing unit 113 performs image processing to compare the first image with the second image. In the image processing, the image processing unit 113 compares the first image with the second image using image processing logic according to the vehicle model information acquired by the vehicle information acquisition unit 112. In the comparison, the image processing unit 113 dynamically identifies an area in the image corresponding to the vehicle 210 (its body), and compares the first image with the second image in the identified area. For example, the image processing unit 113 may switch the size of the area of ​​the body of the vehicle 210 whose surface faces the camera 150 according to the vehicle model. Areas whose surface does not face the camera 150 are easily affected by reflection and therefore scratches cannot be stably detected, so the image processing unit 113 may exclude such areas from the comparison target.

[0032] For example, the image processing unit 113 may switch the image processing engine used for image processing between a small vehicle and a large vehicle depending on the size of the vehicle 210. Also, the image processing unit 113 may switch the setting parameters of the image processing engine between a small vehicle and a large vehicle depending on the size of the vehicle 210. The image processing unit 113 may switch the image processing logic depending on the color (body color) of the vehicle 210. Furthermore, the image processing unit 113 may switch the image processing logic depending on the combination of the color or brightness of the background in the image and the color of the vehicle 210. For example, when the background is dark and the color of the vehicle 210 is dark, it is considered that it is difficult to distinguish between the vehicle area and the background area in the image. Also, when the color of the background and the color of the vehicle 210 are similar, it is considered that it is difficult to distinguish between the vehicle area and the background area in the image. The image processing unit 113 may use image processing logic that is effective in such a situation in a situation where it is difficult to distinguish between the vehicle area and the background area in the image.

[0033] The image processing unit 113 may adjust the brightness between the images before comparing the first image with the second image. By adjusting the brightness, the difference in brightness between images taken under different weather conditions can be reduced. Also, for example, the difference in brightness between an image taken at night and an image taken under backlight conditions can be reduced. In comparing the first image with the second image, the image processing unit 113 may use the first image as a reference and detect how much the second image has changed from the first image. The image processing unit 113 corresponds to the image processing means 33 shown in FIG. 1.

[0034] FIG. 6 shows a configuration example of the image processing unit 113. The image processing unit 113 includes an area division unit 121 and an image comparison unit 122. The area division unit 121 divides the image acquired by the image acquisition unit 111 into a plurality of areas according to the vehicle type information acquired by the vehicle information acquisition unit 112. The area division unit 121 divides the image captured by the camera 150 into a first area including only the background, a second area including both the background and the vehicle 210 (its body), and a third area including only the vehicle 210. The area division unit 121 divides the first image acquired by the image acquisition unit 111 into a first area, a second area, and a third area. The area division unit 121 divides the second image acquired by the image acquisition unit 111 into a first area, a second area, and a third area.

[0035] For example, if the vehicle 210 is a small vehicle, it is considered that the image divided by the region dividing unit 121 includes more first regions and second regions than a standard-sized vehicle. On the other hand, if the vehicle 210 is a large vehicle, it is considered that the image divided by the region dividing unit 121 includes more second regions and third regions than a standard-sized vehicle. In other words, the proportions of the first regions, second regions, and third regions included in the images divided by the region dividing unit 121 are different between a small vehicle and a large vehicle.

[0036] In this embodiment, the region division unit 121 may divide the image into a first region, a second region, and a third region using image processing logic according to the size of the vehicle 210. For example, when the vehicle 210 is a small vehicle, the region division unit 121 may perform region division using image processing logic such that the ratio of the first region and the second region is larger than in the case of a standard-sized vehicle. When the vehicle 210 is a large vehicle, the region division unit 121 may perform region division using image processing logic such that the ratio of the second region and the third region is larger than in the case of a standard-sized vehicle.

[0037] The image comparison unit 122 compares the first image with the second image in the second region and the third region divided by the region division unit 121. That is, the image comparison unit 122 compares the second region of the first image with the second region of the second image. The image comparison unit 122 also compares the third region of the first image with the third region of the second image. The first region is an area that includes only the background and does not include the vehicle 210, so the first region is excluded from the comparison target. For example, the image comparison unit 122 detects how much the second image has changed from the first image in the second and third regions, for example, for each pixel or for each predetermined block.

[0038] The damage detection unit 114 determines the presence or absence of damage, such as scratches or dents, based on the results of the comparison in the image processing unit 113. In other words, the damage detection unit 114 detects damage that has occurred on the vehicle 210 based on the results of the comparison in the image processing unit 113. For example, the damage detection unit 114 detects a location where the amount of change from the first image to the second image is equal to or greater than a threshold as a location where damage has occurred on the vehicle 210. The damage detection unit 114 may change the threshold used to determine the damaged location according to the color information of the vehicle 210. In this case, for example, the damaged location can be determined using different criteria for light colors and dark colors.

[0039] The damage detection unit 114 may change the threshold value according to the contract details included in the user's reservation information. For example, if the user has taken out insurance when making a rental car contract, the user will not be charged even if the vehicle is damaged. The damage detection unit 114 may change the threshold value according to whether the user has taken out insurance. For example, if the user has not taken out insurance, it is preferable to strictly determine the location of damage in order to clarify the location of responsibility. In that case, the damage detection unit 114 sets a relatively small value to the threshold value. On the other hand, if the user has taken out insurance, the damage can be repaired using insurance, so the determination of the location of damage does not need to be very strict. In that case, the damage detection unit 114 may set a relatively large value to the threshold value. If damage is detected, the damage detection unit 114 may output an alert to an employee of the rental car company, such as a clerk. The damage detection unit 114 corresponds to the detection means 34 shown in FIG. 1.

[0040] If damage is detected, the clerk visually checks the vehicle 210 together with the user to check whether damage has occurred. If damage is detected, the damage detection unit 114 may highlight or enlarge an image of the location of the detected damage in the second image and display it on the display. The clerk can check the presence or absence of damage by looking at the image displayed on the display together with the user. The damage detection unit 114 may display an image of the location where damage was detected (the damaged location) in the second image and an image of the location corresponding to the damaged location in the first image in a manner that allows comparison. In this case, the clerk and the user can check whether damage already existed at the time the first image was taken. If damage is confirmed, the clerk negotiates the cost with the user.

[0041] Next, the operation procedure will be described. Fig. 7 shows the operation procedure (vehicle management method) in the vehicle management device 110. The image acquisition unit 111 acquires images captured by the camera 150 (step S1). In step S1, the image acquisition unit 111 acquires, for example, four images captured using the four cameras 150A-150D (see Fig. 3).

[0042] The image acquisition unit 111 determines whether the vehicle 210 is a vehicle to be returned (step S2). In step S2, the image acquisition unit 111 refers to the reservation DB 131, for example, to determine whether the vehicle 210 is a vehicle to be returned or a vehicle to be rented out. If the image acquisition unit 111 determines in step S2 that the vehicle 210 is not a vehicle to be returned, it registers the image acquired in step S1 in the reservation DB 131 (see FIG. 4) as a departure image (first image) (step S3).

[0043] If the vehicle 210 is a vehicle to be returned, the image acquisition unit 111 registers the image acquired in step S1 as a return image (second image) in the reservation DB 131. If it is determined in step S2 that the vehicle 210 is a vehicle to be returned, the vehicle information acquisition unit 112 acquires vehicle model information of the vehicle 210 (step S4). In step S2, the vehicle information acquisition unit 112 acquires vehicle model information (vehicle model name), for example, from the vehicle information DB 132 (see FIG. 5).

[0044] In the image processing unit 113, the region dividing unit 121 divides the image acquired by the image acquiring unit 111 into a plurality of regions according to the vehicle type information acquired in step S4 (step S5). For example, in step S5, the region dividing unit 121 divides each of the departure image and the return image into the first region, the second region, and the third region described above. The image comparing unit 122 compares the departure image with the return image (step S6). For example, in step S6, the image comparing unit 122 compares the departure image with the return image in each of the second region and the third region.

[0045] As a result of the comparison in step S6, the damage detection unit 114 determines whether or not there is a large change from the first image to the second image (step S7). The damage detection unit 114 registers the determination result in step S7 in the reservation DB 131. If the damage detection unit 114 determines that there is a large change in step S7, it notifies a clerk or a person in charge of the management department of the rental car company of a damage alert (step S8). In step S8, the damage detection unit 114 notifies the clerk or person in charge of, for example, areas of the vehicle 210 where there is a large change in the image, that is, areas of the vehicle 210 where there is a high possibility of damage occurring.

[0046] In this embodiment, the image processing unit 113 performs image processing according to the vehicle type information of the vehicle 210 to compare a first image, which is an image at departure, with a second image, which is an image at return. In the image processing unit 113, the region dividing unit 121 uses the vehicle type information to divide the first image and the second image into a first region including only the background, a second region including the background and the vehicle body, and a third region including only the vehicle body. The image comparing unit 122 compares the first image and the second image in the second region and the third region.

[0047] When the vehicle 210 is a small vehicle, the divided image contains many first regions. In that case, the image comparison unit 122 does not perform image comparison for the first region, which is the background part. By omitting image comparison of the background part, it is possible to suppress unnecessary image comparison (image inspection). Therefore, in this embodiment, it is possible to reduce unnecessary calculation resources and achieve cost reduction. In addition, in this embodiment, since scratches are not erroneously detected in comparison of the background part, it is considered that erroneous detection can be reduced and inspection accuracy can be improved. On the other hand, when the vehicle 210 is a large vehicle, it is considered that the first region included in the divided image is small. In that case, the second region and the third region including the main body part of the vehicle 210 are increased, and the region to be compared is wide, so that omissions in image comparison can be suppressed and inspection accuracy can be improved.

[0048] In this embodiment, the damage detection unit 114 can detect new damage that has occurred to the vehicle 210 while it is being lent to a user, based on the comparison result between the first image and the second image compared by image processing according to the vehicle type information. In this embodiment, the image processing unit 113 performs image comparison by image processing according to the vehicle type information. Therefore, the vehicle management device 110 according to this embodiment can efficiently and accurately detect new damage that has occurred to the vehicle 210.

[0049] In this embodiment, the vehicle management device 110 may hold information for each vehicle type indicating which part of the image is the area where the body surface faces the camera 150. The image processing unit 113 can also use the information to compare images. For example, the image processing unit 113 can more efficiently inspect whether the vehicle 210 is damaged by excluding from the comparison areas that are easily affected by reflection and therefore cannot reliably detect damage.

[0050] In each of the above embodiments, the vehicle management device 110 may be configured as a computer device. Fig. 8 shows an example of the configuration of a computer device that may be used as the vehicle management device 110. The computer device 500 has a control unit (CPU: Central Processing Unit) 510, a storage unit 520, a ROM (Read Only Memory) 530, a RAM (Random Access Memory) 540, a communication interface (IF: Interface) 550, and a user interface 560.

[0051] The communication interface 550 is an interface for connecting the computer device 500 to a communication network via a wired communication means or a wireless communication means, etc. The user interface 560 includes a display unit such as a display, and an input unit such as a keyboard, a mouse, and a touch panel.

[0052] The storage unit 520 is an auxiliary storage device that can hold various data. The storage unit 520 does not necessarily need to be a part of the computer device 500, and may be an external storage device or a cloud storage connected to the computer device 500 via a network.

[0053] The ROM 530 is a non-volatile storage device. For example, a semiconductor storage device having a relatively small capacity, such as a flash memory, is used for the ROM 530. The programs executed by the CPU 510 may be stored in the storage unit 520 or the ROM 530. The storage unit 520 or the ROM 530 stores various programs for implementing the functions of each unit in the vehicle management device 110, for example.

[0054] The program includes a set of instructions (or software code) for making the computer perform one or more functions described in the embodiments when the program is loaded into the computer. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or the tangible storage medium includes RAM, ROM, flash memory, solid-state drive (SSD) or other memory technology, Compact Disc (CD)-ROM, digital versatile disc (DVD), Blu-ray (registered trademark) disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or a communication medium. By way of example and not limitation, the transitory computer-readable medium or the communication medium includes electrical, optical, acoustic, or other forms of propagating signals.

[0055] The RAM 540 is a volatile storage device. Various semiconductor memory devices such as a dynamic random access memory (DRAM) or a static random access memory (SRAM) are used for the RAM 540. The RAM 540 can be used as an internal buffer for temporarily storing data and the like. The CPU 510 loads a program stored in the storage unit 520 or the ROM 530 into the RAM 540 and executes it. The CPU 510 executes a program to realize the functions of each unit in the vehicle management device 110. The CPU 510 may have an internal buffer for temporarily storing data and the like.

[0056] Although the embodiments of the present disclosure have been described in detail above, the present disclosure is not limited to the above-described embodiments, and changes and modifications to the above-described embodiments that do not deviate from the spirit of the present disclosure are also included in the present disclosure.

[0057] For example, some or all of the above embodiments may be described as, but are not limited to, the following supplementary notes.

[0058] [Appendix 1] an image acquisition means for acquiring a first image taken at a first time using one or more cameras that photograph a vehicle to be rented to a user, and a second image taken at a second time after the first time using the cameras; A vehicle type information acquisition means for acquiring vehicle type information of the vehicle; an image processing means for comparing the first image with the second image using image processing logic corresponding to the acquired vehicle model information; and a detection means for detecting damage caused to the vehicle based on a result of the comparison in the image processing means.

[0059] [Appendix 2] The image processing means includes: Dividing the first image and the second image into a first region including only a background, a second region including both the background and the vehicle, and a third region including only the vehicle according to the vehicle type information; A vehicle management device as described in Appendix 1, which compares the second area of ​​the first image with the second area of ​​the second image, and compares the third area of ​​the first image with the third area of ​​the second image.

[0060] [Appendix 3] The vehicle management device described in Appendix 1 or 2, wherein the image processing means, when comparing the first image with the second image, detects how much the second image has changed from the first image using the first image as a reference.

[0061] [Appendix 4] The vehicle management device according to claim 3, wherein the detection means determines that the vehicle is damaged if the amount of change from the first image to the second image is greater than or equal to a threshold value.

[0062] [Appendix 5] The vehicle type information acquisition means further acquires color information of the vehicle, The vehicle management device according to claim 4, wherein the detection means changes the threshold value depending on the color information.

[0063] [Appendix 6] The vehicle management device according to any one of claims 1 to 5, wherein the vehicle type information acquisition means acquires identification information of the vehicle, and acquires the vehicle type information based on the acquired identification information.

[0064] [Appendix 7] The vehicle management device according to claim 6, wherein the vehicle type information acquisition means acquires vehicle type information associated with the acquired identification information from a database that stores the identification information and the vehicle type information.

[0065] [Appendix 8] The vehicle management device according to claim 6, wherein the vehicle type information acquisition means acquires the identification information from an image of the license plate of the vehicle included in the first image and the second image.

[0066] [Appendix 9] The vehicle management device according to any one of claims 1 to 8, wherein the vehicle type information acquisition means acquires a vehicle name of the vehicle as the vehicle type information.

[0067] [Appendix 10] A vehicle management device as described in any one of appendix 1 to 9, wherein the first time is the time before the vehicle is rented to the user, and the second time is the time when the user returns the vehicle.

[0068] [Appendix 11] A vehicle management device according to any one of claims 1 to 10, wherein the first image is taken at a departure store upon departure, and the second image is taken at a return store upon return.

[0069] [Appendix 12] One or more cameras for photographing a vehicle to be rented to a user; A vehicle management device used for managing the vehicle, The vehicle management device includes: an image acquisition means for acquiring a first image captured by the camera at a first time and a second image captured by the camera at a second time after the first time; A vehicle type information acquisition means for acquiring vehicle type information of the vehicle; an image processing means for comparing the first image with the second image using image processing logic corresponding to the acquired vehicle model information; and a detection means for detecting damage caused to the vehicle based on a result of the comparison in the image processing means.

[0070] [Appendix 13] The image processing means includes: Dividing the first image and the second image into a first region including only a background, a second region including both the background and the vehicle, and a third region including only the vehicle according to the vehicle type information; 13. The vehicle management system of claim 12, further comprising: comparing the second area of ​​the first image with the second area of ​​the second image; and comparing the third area of ​​the first image with the third area of ​​the second image.

[0071] [Appendix 14] Obtaining a first image taken at a first time using one or more cameras that photograph a vehicle to be rented to a user, and a second image taken at a second time after the first time using the cameras; Acquire vehicle model information of the vehicle; comparing the first image with the second image using image processing logic according to the acquired vehicle model information; detecting damage caused to the vehicle based on a result of the comparison.

[0072] [Appendix 15] Obtaining a first image taken at a first time using one or more cameras that photograph a vehicle to be rented to a user, and a second image taken at a second time after the first time using the cameras; Acquire vehicle model information of the vehicle; comparing the first image with the second image using image processing logic according to the acquired vehicle model information; A non-transitory computer-readable medium storing a program for causing a computer to execute a process including detecting damage caused to the vehicle based on a result of the comparison. [Explanation of symbols]

[0073] 10: Vehicle management system 30: Vehicle management device 31: Image acquisition means 32: Vehicle information acquisition means 33: Image processing means 34: Detection means 50: Camera 100: Vehicle management system 110: Vehicle management device 111: Image acquisition unit 112: Vehicle information acquisition unit 113: Image processing unit 114: Damage detection unit 121: Area division part 122: Image comparison section 130: Database 131: Reservation DB 132: Vehicle DB 150: Camera 200: Photo area 210: Vehicle

Claims

1. An image acquisition means for acquiring a first image taken at a first time using one or more cameras that photograph a vehicle, and a second image taken at a second time after the first time using the cameras; A vehicle type information acquisition means for acquiring vehicle type information of the vehicle; an image processing means for comparing an area in the first image that includes only the vehicle with an area in the second image that includes only the vehicle, the area being specified using image processing logic according to the acquired vehicle type information; and a detection means for detecting damage caused to the vehicle based on a result of the comparison in the image processing means.

2. The image processing means includes: Further identifying an area in each of the first image and the second image that includes only a background and an area in each of the first image and the second image that includes both the background and the vehicle according to the vehicle type information; The vehicle management device according to claim 1 , further comprising: comparing an area in the first image in which both the background and the vehicle are included with an area in the second image in which both the background and the vehicle are included.

3. 3. The vehicle management device according to claim 1, wherein the image processing means, when comparing the first image with the second image, detects how much the second image has changed from the first image using the first image as a reference.

4. 4. The vehicle management device according to claim 3, wherein the detection means determines that the vehicle is scratched when an amount of change from the first image to the second image is equal to or greater than a threshold value.

5. The vehicle type information acquisition means further acquires color information of the vehicle, The vehicle management device according to claim 4 , wherein the detection means changes the threshold value in accordance with the color information.

6. The vehicle management device according to claim 1 , wherein the vehicle type information acquisition means acquires identification information of the vehicle, and acquires the vehicle type information based on the acquired identification information.

7. 7. The vehicle management device according to claim 6, wherein the vehicle type information acquisition means acquires the vehicle type information associated with the acquired identification information from a database that stores the identification information and the vehicle type information.

8. One or more cameras for photographing a vehicle; A vehicle management device used for managing the vehicle, The vehicle management device includes: an image acquisition means for acquiring a first image captured by the camera at a first time and a second image captured by the camera at a second time after the first time; A vehicle type information acquisition means for acquiring vehicle type information of the vehicle; an image processing means for comparing an area in the first image that includes only the vehicle with an area in the second image that includes only the vehicle, the area being specified using image processing logic according to the acquired vehicle type information; and a detection means for detecting damage caused to the vehicle based on a result of the comparison in the image processing means.

9. A computer acquires a first image taken at a first time using one or more cameras that photograph a vehicle, and a second image taken at a second time after the first time using the cameras; The computer acquires vehicle type information of the vehicle, The computer compares an area in the first image that includes only the vehicle with an area in the second image that includes only the vehicle, the area being identified using image processing logic according to the acquired vehicle type information; The vehicle management method further comprises the computer detecting damage caused to the vehicle based on a result of the comparison.

10. Obtaining a first image taken at a first time using one or more cameras that photograph a vehicle, and a second image taken at a second time after the first time using the cameras; Acquire vehicle model information of the vehicle; comparing an area in the first image that includes only the vehicle with an area in the second image that includes only the vehicle, the area being identified using image processing logic according to the acquired vehicle type information; A program for causing a computer to execute a process including detecting damage caused to the vehicle based on a result of the comparison.

Images