Image processing device, image processing system, image processing method, and recording medium

Abstract

This image processing device comprises: an acquisition unit; a correction information generation unit; and a correction unit. The acquisition unit acquires a first image and a second image. The first image is captured by a first imaging means installed at a first point, and includes a reference object. The second image is captured by a second imaging means installed at a second point, and includes the same reference object as that of the first image. The correction information generation unit generates, by using the first image and the second image, correction information for correcting at least one of an image captured by the first imaging means and an image captured by the second imaging means. The correction unit corrects, by using the correction information, a target image including an object captured by at least one of the first imaging means and the second imaging means.

Description

Image Processing Apparatus, Image Processing System, Image Processing Method, and Recording Medium

[0001] The present invention relates to an image processing apparatus, an image processing system, an image processing method, and a recording medium.

[0002] In recent years, techniques related to image processing have been used in various fields. In order to perform image processing with high accuracy, it may be preferable to correct an image. For example, in Patent Document 1, an object setting unit that receives a setting of an object arranged in an imaging field of view, a color component of a partial image corresponding to the object in an imaging image captured in the imaging field of view, and a predetermined color component are used to obtain correction information for color correction, and a color correction unit that performs color correction processing on the imaging image using the correction information are provided. An information processing system is described.

[0003] International Publication No. 2024 / 034255

[0004] By processing images generated by each of a plurality of imaging devices installed at different locations, it may be necessary to determine the relevance of these images. When determining this relevance, it may be better to correct the images using appropriate correction conditions.

[0005] An image processing apparatus according to an aspect of the present disclosure includes: acquisition means for acquiring a first image including a reference object, captured by a first imaging means installed at a first location, and a second image including the reference object, captured by a second imaging means installed at a second location; correction information generation means for generating correction information for correcting at least one of the image captured by the first imaging means and the image captured by the second imaging means, using the first image and the second image; and correction means for correcting a target image including an object captured by at least one of the first imaging means and the second imaging means, using the correction information.

[0006] An image processing system in one aspect of the present disclosure comprises: a first imaging means installed at a first location; a second imaging means installed at a second location; and an image processing device, wherein the image processing device comprises: an acquisition means for acquiring a first image captured by the first imaging means and including a reference object; and a second image captured by the second imaging means and including the reference object; a correction information generation means for generating correction information to correct at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first image and the second image; and a correction means for correcting a target image including an object captured by at least one of the first imaging means and the second imaging means using the correction information.

[0007] An image processing method in one aspect of the present disclosure involves a hardware device acquiring a first image including a reference object, which is captured by a first imaging means installed at a first location, and a second image including the reference object, which is captured by a second imaging means installed at a second location, generating correction information for correcting at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first image and the second image, and correcting a target image including an object captured by at least one of the first imaging means and the second imaging means using the correction information.

[0008] A recording medium in one aspect of the present disclosure records a program, which, when executed by a computer, causes the computer to: acquire a first image including a reference object, captured by a first imaging means installed at a first location; and a second image including the reference object, captured by a second imaging means installed at a second location; generate correction information for correcting at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first and second images; and correct a target image including an object, captured by at least one of the first and second imaging means, using the correction information.

[0009] According to one example of this disclosure, an image can be corrected using appropriate correction conditions.

[0010] This figure shows an example configuration of the image processing system relating to this disclosure. This figure shows an example hardware configuration of the image processing device included in the image processing system. This flowchart shows an example of processing performed by the image processing device. This flowchart shows an example of processing performed by the image processing device. This figure shows an example configuration of the image processing system.

[0011] In this disclosure, the drawings are associated with one or more embodiments. In all drawings, similar components are denoted by the same reference numerals, and their descriptions are omitted where appropriate.

[0012] The image processing system includes, for example, an image processing device 10 and a plurality of imaging units, such as a first imaging unit 20 and a second imaging unit 30, as shown in Figure 1.

[0013] Multiple imaging units are installed in different locations. For example, multiple imaging units are installed so that their imaging ranges do not overlap. Multiple imaging units may be installed in facilities located in different locations, or they may be installed within the same facility. An example of the former is that multiple imaging units are installed in different airports, different train stations, or different bus stops. An example of the latter is within the premises of the same train station. In this case, at least one imaging unit is installed on the side of the train platform where trains enter, and at least one other imaging unit is installed on the side of the platform where trains leave. Multiple imaging units may also be surveillance cameras installed outdoors.

[0014] In the following description, the location where the first imaging unit 20 is installed will be referred to as the first location, and the location where the second imaging unit 30 is installed will be referred to as the second location. For example, the first location and the second location are different airports.

[0015] At least some of the multiple imaging units generate repeating images. For example, at least one of the first imaging unit 20 and the second imaging unit 30 described above generates repeating images. For example, the multiple imaging units may generate multiple frame images that constitute a video. Each of the multiple imaging units then transmits at least some of the multiple images it has generated to the image processing unit 10. Here, the multiple imaging units may transmit all of the images they have generated to the image processing unit 10, or they may select only images that satisfy predetermined conditions and transmit them to the image processing unit 10. These predetermined conditions are, for example, time information on when the images are captured, and may be transmitted from the image processing unit 10 to the imaging unit.

[0016] The image processing device 10 corrects images acquired from multiple imaging units. The image processing device 10 may perform correction on the entire image according to the same rules, or it may apply different rules to some pixels than to other pixels. The image processing device 10 also generates these rules.

[0017] The corrections performed by the image processing device 10 include, but are not limited to, correcting color (brightness, contrast, saturation, hue). For example, by performing corrections, the image processing device 10 can remove information equivalent to noise, such as raindrops, snow, mist, and smoke, that exist between the imaging unit and the object being imaged. When correcting color, the image processing device 10, for example, modifies the values ​​of multiple pixels that make up an image generated by at least one of the multiple imaging units.

[0018] The image processing device 10 includes an acquisition unit 110, a correction information generation unit 120, and a correction unit 130, and can utilize a storage unit 140.

[0019] The acquisition unit 110 acquires images captured by multiple imaging units. For example, the acquisition unit 110 acquires at least a first image captured by the first imaging unit 20 that includes an object, and a second image captured by the second imaging unit 30 that includes the same object as in the first image. Hereinafter, this object will be referred to as the reference object.

[0020] The reference object is a moving object that moves between, for example, a first location where the first imaging unit 20 is installed and a second location where the second imaging unit 30 is installed. This moving object may travel back and forth between the first and second locations, or it may only travel from one location to the other, or it may pass through other locations in between. In other words, the first location and the second location are bases used by a moving object of the same type. This moving object is, for example, at least one of an airplane, a road vehicle, and a railway vehicle.

[0021] For example, if the first and second locations are airports, the reference object is an airplane. Ideally, the airplane in the first image and the airplane in the second image should be the same aircraft. However, they may be different aircraft if their exterior color or the paint that gives them that color is the same. An example of this would be if the airline and aircraft type were the same.

[0022] Furthermore, if the first and second locations are train stations, the reference object is a railway vehicle. Similarly, if the first and second locations are bus stops, the reference object is a bus. In these examples as well, it is desirable that the vehicle in the first image and the vehicle in the second image are the same vehicle. Whether or not the vehicles are the same can be determined using railway timetables or bus license plates. However, if the exterior color or the paint that gives it that color is the same, they may be different vehicles.

[0023] The moving object may be a vehicle, a person, or an animal. If the moving object is a person, at least one of their clothing, ornaments, and personal belongings may also be treated as part of the person.

[0024] The correction information generation unit 120 generates correction information using the first image and the second image to correct at least one of the images captured by the first imaging unit 20 and the second imaging unit 30. This correction information is intended to improve the image identity of the portion of the two generated images that shows the same object, assuming that the first imaging unit 20 and the second imaging unit 30 have captured the same object. By using this correction information, it becomes easier to determine that the object contained in the two images is the same when the two images have captured the same object. The correction information may be information for correcting one of the first image and the second image, or it may be information for correcting both of them. In the latter case, the correction information generation unit 120 generates correction information for the first image and correction information for the second image.

[0025] Correction information is, for example, used to bring the colors of the parts of two images in which an object is depicted closer together. In this case, the correction information is information that changes the color of the image, for example, a rule for correcting the values ​​of each color that make up each pixel of the image (hereinafter referred to as pixel value). An example of this rule is a function. For example, the correction information increases or decreases the pixel value of one of the first imaging unit 20 and the second imaging unit 30 based on a predetermined rule.

[0026] The correction information generation unit 120, for example, extracts a region from the first image in which at least a part of the reference object is visible, i.e., the first region, and extracts a region from the second image in which the same part of the reference object as the first region is visible, i.e., the second region. The parts of the reference object visible in the first and second regions are, for example, regions of the reference object that have a distinctive appearance. For example, if the reference object is an airplane, this region is the region where the airline's mark is drawn. The correction information generation unit 120 may recognize the shape of the reference object and define a specific part of this shape, for example, a specific part of the fuselage of an airplane or a specific part of the body of a vehicle, as a distinctive region, and then extract the first and second regions from there.

[0027] The correction information generation unit 120 then calculates the difference between the pixel values ​​of the first region and the pixel values ​​of the second region, and generates correction information that reduces this difference. When the multiple pixels constituting the image are composed of data of multiple colors such as RGB, it is preferable that this rule be defined for each of the multiple colors. For example, the correction information generation unit 120 may calculate the average value of each of the multiple colors (e.g., RGB) constituting the image in the first region and the second region, and calculate the difference between these average values ​​as correction information.

[0028] The rules used as correction information may be one per image, or they may be set on a pixel-by-pixel basis. For example, if the entire characteristic region of the reference object has the same color, then one correction information rule may be sufficient for the image, making it easier to generate the correction information.

[0029] The correction unit 130 uses the correction information generated by the correction information generation unit 120 to correct the images captured by the first imaging unit 20 and the second imaging unit 30, specifically correcting the image captured by at least one of them. Hereinafter, the image to be corrected will be referred to as the target image. This correction is performed, for example, when comparing the target image with its corresponding image. This correction may be performed when the image processing device 10 inputs an image, or while the image is temporarily stored after input until comparison. An example of a target image is an image generated by the first imaging unit 20, and an example of a corresponding image is an image generated by the second imaging unit 30. Alternatively, the target image may be an image generated by the second imaging unit 30, and the corresponding image may be an image generated by the first imaging unit 20.

[0030] Furthermore, it is preferable that the correction information generation unit 120 stores the generated correction information in the storage unit 140 in association with the combination of the first imaging unit 20 and the second imaging unit 30. In this case, the correction unit 130 uses the correction information stored in the storage unit 140. It is preferable that the correction information generation unit 120 periodically updates the correction information stored in the storage unit 140. The interval at which this update is performed is, for example, one day or more and one year or less. The correction information may be updated at the timing of an event occurrence, such as during imaging.

[0031] If there are multiple combinations of the first imaging unit 20 and the second imaging unit 30, the correction information generation unit 120 generates correction information for each combination and stores it in the storage unit 140. The correction unit 130 then reads the correction information from the storage unit 140 that corresponds to the combination of the imaging unit that generated the target image and the imaging unit that generated the image corresponding to this target image, and uses it.

[0032] The image processing device 10 has a hardware configuration that includes, for example, a bus 1010, a processor 1020, a memory 1030, a storage device 1040, an input / output interface 1050, and a network interface 1060, as shown in Figure 2.

[0033] Bus 1010 is a data transmission path for the processor 1020, memory 1030, storage device 1040, input / output interface 1050, and network interface 1060 to send and receive data to and from each other. However, the method of connecting the processor 1020 and the other components to each other is not limited to bus connection.

[0034] Processor 1020 is a processor implemented using components such as a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit).

[0035] Memory 1030 is a main memory device implemented as RAM (Random Access Memory), etc.

[0036] The storage device 1040 is an auxiliary storage device implemented as a removable media such as an HDD (Hard Disk Drive), SSD (Solid State Drive), or memory card, or flash memory, and has a recording medium. The recording medium of the storage device 1040 stores program modules that realize each function of the image processing device 10 (for example, the acquisition unit 110, the correction information generation unit 120, the correction unit 130, and the processing unit 150 described later). The processor 1020 reads each of these program modules into the memory 1030 and executes them, thereby realizing each function corresponding to the program module. The storage device 1040 may also function as a storage unit 140 for storing correction information.

[0037] The input / output interface 1050 is an interface for connecting the image processing device 10 with various input / output devices. For example, the image processing device 10 may communicate with an external storage device (not shown) having a storage unit 140 for storing correction information via the input / output interface 1050. If the first imaging unit 20 and the second imaging unit 30 are located near the image processing device 10 and the connection is not made via a network, the input / output interface 1050 is also used to connect to the first imaging unit 20 and the second imaging unit 30.

[0038] The network interface 1060 is an interface for connecting the image processing device 10 to a network. It is used when the destination device is located far away and connection requires going through a network. This network may be, for example, a LAN (Local Area Network) or a WAN (Wide Area Network). The method by which the network interface 1060 connects to the network may be wireless or wired. The image processing device 10 may communicate with multiple imaging units via the network interface 1060, or it may communicate with an external storage device (not shown) having a storage unit 140 for storing correction information.

[0039] Note that the input / output interface 1050 and the network interface 1060 may be the same interface.

[0040] Also, the hardware configuration example for realizing the image processing apparatus 10 may be, for example, an FPGA (Field Programmable Gate Array) or a hardware logic circuit that implements the algorithm performed by the image processing apparatus 10, rather than a so-called computer.

[0041] The image processing apparatus 10 operates as follows, for example. First, the acquisition unit 110 acquires the first image and the second image (step S10).

[0042] When the first imaging unit 20 repeatedly generates a plurality of images, the acquisition unit 110 may acquire these plurality of images together with their shooting dates and times, and select the first image from the acquired images. In this case, the acquisition unit 110 may select, as the first image, an image generated at a predetermined timing. The acquisition unit 110 may also select the second image in the same manner.

[0043] Alternatively, the acquisition unit 110 may transmit information indicating the timing for generating the first image to the first imaging unit 20, and acquire, from the acquisition unit 110, the image generated at that timing as the first image. The acquisition unit 110 may also acquire the second image in the same manner.

[0044] Here, specific examples of the generation timing of the first image and the generation timing of the second image will be described.

[0045] When the first location and the second location are bases used by the same type of moving body, the acquisition unit 110 specifies at least one of the imaging timings of the first image and the second image using at least one of the movement plan information of this moving body at the first location and the movement plan information of this moving body at the second location. An example of the movement plan information is flight information of an airplane, a bus operation plan, and a train diagram in a railway.

[0046] For example, when the first location and the second location are airports and the reference object is an airplane, the acquisition unit 110 executes at least one of specifying the imaging timing of the first image using the flight information at the first location and specifying the imaging timing of the second image using the flight information at the second location. For example, when a flight number is specified, the acquisition unit 110 uses the flight information to specify the departure time and arrival time of that flight number, and sets the specified times as the imaging timing. Here, it is preferable that the imaging timing of the first image and the imaging timing of the second image are on the same day. Note that the specification of the flight number may be set in advance or may be input by the user of the image processing apparatus 10.

[0047] In addition, the reference object may transmit identification information for identifying the reference object by wireless communication. Examples of such reference objects are airplanes and vehicles. In this case, the acquisition unit 110 can specify at least one of the imaging timing of the first image and the imaging timing of the second image using the timing at which the identification information of the reference object is acquired. For example, the acquisition unit 110 may specify the imaging timing of the first image using the timing at which the identification information of the reference object is acquired at the first location. Similarly, the acquisition unit 110 may specify the imaging timing of the second image using the timing at which the identification information of the reference object is acquired at the second location. In these examples, the acquisition unit 110 sets an image taken at at least one of the timing at which the identification information is acquired, a predetermined time before that, or a predetermined time after that as the first image (or the second image). The predetermined time here is, for example, 1 second or more and 1 minute or less, but is not limited to these ranges.

[0048] In addition, when at least one of the first imaging unit 20 and the second imaging unit 30 generates a repeated image, the acquisition unit 110 may select an image in which the reference object appears as the first image and the second image.

[0049] For example, identification information for identifying the object may be displayed on the surface of a reference object. In this case, the acquisition unit 110 can select at least one of the first image and the second image by identifying an image containing the identification information displayed on the surface of the reference object. For example, if the reference object is an airplane, this identification information is a number assigned to the aircraft. This number may be represented by a string of characters or by code information such as a barcode or a two-dimensional code. If the reference object is a vehicle, an example of this identification information is the vehicle number displayed on the license plate. The acquisition unit 110 then processes a plurality of images generated by the first imaging unit 20 to identify an image of the aircraft or vehicle containing this identification information and selects the identified image as the first image. The acquisition unit 110 also processes a plurality of images generated by the second imaging unit 30 to identify an image of the aircraft or vehicle containing this identification information and selects the identified image as the second image.

[0050] Next, the correction information generation unit 120 generates correction information using the first image and the second image (step S20). Preferably, the correction information generation unit 120 stores this correction information in the storage unit 140. After that, the correction unit 130 acquires the target image and the image paired with the target image (step S30), and corrects the acquired target image using the correction information (step S40). This process makes it easier to determine that the object contained in the first image and the second image is the same when they both depict the same object. Here, the paired image may also be the image to be corrected, i.e., the target image.

[0051] The image processing device 10 may, for example, display the corrected target image and its corresponding image on a display. A person viewing the display can, for example, determine whether the subjects depicted in these images are the same.

[0052] When the same object is photographed by the first imaging unit 20 and the second imaging unit 30, variations may occur in the multiple images generated due to individual differences in the imaging devices of these imaging units. The cause of these individual differences is, for example, at least one of variations during production and changes over time. Therefore, even if the first imaging unit 20 and the second imaging unit 30 photograph the same object, differences in color information output by the first imaging unit 20 and the second imaging unit 30 may occur due to these individual differences, potentially leading to a misjudgment that the same object was photographed.

[0053] In response to this, the image processing device 10 generates correction information using the first and second images, which are known to have captured the same object, and corrects the target image using this correction information. Therefore, the possibility of the above-mentioned misjudgment can be reduced.

[0054] The correction information generation unit 120 of the image processing device 10 may further acquire environmental information, for example, as shown in step S12 of Figure 4. Here, the environmental information includes, for example, first environmental information relating to the environment of the first imaging unit 20 at the time the first image was generated, and second environmental information relating to the environment of the second imaging unit 30 at the time the second image was generated. In this case, the correction information generation unit 120 of the image processing device 10 may generate correction information using at least one of the first environmental information and the second environmental information.

[0055] The first environmental information and the second environmental information include, for example, at least one of weather information and light source information. The weather information includes, for example, at least one of the presence or absence of rainfall, snowfall, snow cover, fog, smoke, and dust or sand. The light source information includes, for example, at least one of the presence or absence of sunlight and information indicating whether or not an artificial light source is emitting light, for example, whether or not the lights are on. The light source information may further include at least one of the following: information indicating the relative direction of the light source with respect to a reference object, information indicating the direction of irradiation of light emitted from the light source, information indicating the color temperature of light emitted from the light source, and information indicating the change in light emitted from the light source over time. The correction information generation unit 120 then uses at least a portion of the first environmental information and the second environmental information as at least a portion of the correction information (step S20).

[0056] The correction unit 130 then uses the correction information to correct the color (brightness, contrast, saturation, hue) and remove information equivalent to noise, such as raindrops, snow, mist, and smoke, that exist between the imaging unit and the object being imaged. An example of the former type of correction is backlight correction.

[0057] In this way, noise is removed from the images generated by the first imaging unit 20 and the second imaging unit 30, so that when these imaging units photograph the same object, the image processing device 10 is more likely to be able to determine that the first imaging unit 20 and the second imaging unit 30 have photographed the same object.

[0058] The reason for this is explained in detail below. When comparing multiple images to determine the identity of a subject, a single image generally contains both information necessary for the determination and information that is unnecessary. Therefore, in order to accurately determine identity, it is necessary to perform correction to remove the unnecessary information mentioned above.

[0059] On the other hand, what is treated as unnecessary information depends on what the image is used for. For this reason, it is not common practice to remove information from an image in the imaging unit. In this embodiment, the correction unit 130 performs correction to remove unnecessary information. When the correction unit 130 performs this process, the image processing device 10 is more likely to be able to determine that the first imaging unit 20 and the second imaging unit 30 have captured the same object.

[0060] Furthermore, if some information is removed by the imaging unit, it is preferable to transmit information indicating the type of information removed from the imaging unit to the image processing device 10. In this way, the correction unit 130 can omit the removal process without having to determine whether or not the removal process is necessary. As a result, the processing load on the correction unit 130 is reduced.

[0061] In addition to the functions described above, the image processing device 10 may also include a processing unit 150, as shown in Figure 5. The processing unit 150 processes the target image after correction by the correction unit 130, and the image corresponding to this target image. As described above, the correction unit 130 may also perform correction processing on the corresponding image. In this case, the processing unit 150 will process multiple target images, as the corresponding image is also a target image.

[0062] One example of the processing performed by the processing unit 150 is to generate information about objects in the target image and information about objects in the corresponding image. For example, if the target image or the corresponding image contains a moving object, the processing unit 150 generates information about this moving object. Hereinafter, this information will be referred to as moving object information. The moving object information includes, for example, information indicating the type of moving object. For example, if the moving object is an animal, the moving object information includes information indicating the type of animal. Here, the processing unit 150 can specify the type of animal to an arbitrary degree. For example, the processing unit 150 may specify it down to the family level, or even down to the genus level, or even down to the species level.

[0063] The processing unit 150 may generate moving object information using, for example, a model generated by machine learning. In this case, the model is generated using images and moving object information as training data.

[0064] The processing unit 150 may identify the individual mobile object and include information identifying this individual object in the mobile object information.

[0065] For example, the processing unit 150 processes the image to generate information indicating the type of moving object and feature quantities indicating external characteristics, which are at least part of the moving object information. External characteristics include, for example, the shape, size, and pattern. The processing unit 150 then uses the identity of the moving object information to determine whether the moving object included in the target image and the moving object included in the paired image are the same individual. When the processing unit 150 identifies the individual moving object, it is preferable for the correction information generation unit 120 to correct both the target image and the paired image (for example, both the image generated by the first imaging unit 20 and the image generated by the second imaging unit 30). In this way, noise components caused by individual differences in the imaging units that generated the images are removed from both images, improving the processing accuracy of the processing unit 150, for example, the accuracy of determining whether they are the same individual. However, the target of correction is not limited to both the target image and the paired image. For example, the correction unit 130 may be configured to correct at least one of the target image and the paired image. Even when only the target image and at least one of its paired images are corrected, it is expected that the accuracy of the judgment will be improved compared to when no correction is performed.

[0066] The processing unit 150 may include identification information (e.g., an identification number) assigned to the moving object in the moving object information, as well as information indicating the type of the moving object and feature quantities indicating its external characteristics. The processing unit 150 then stores this moving object information in the storage unit 140, along with information identifying the imaging unit that captured the moving object (e.g., an identification number of the imaging unit).

[0067] Subsequently, when the processing unit 150 processes a new image and generates moving object information, it determines whether the moving object corresponding to that moving object information has been detected in the past. For example, the processing unit 150 uses the "information indicating the type of moving object and feature quantities indicating the external characteristics" included in the moving object information and the information stored in the storage unit 140 to determine whether the moving object has been detected in the past. If the moving object has been detected in the past, the processing unit 150 adds the identification information assigned to the moving object in the past detection to the newly generated moving object information and then stores it in the storage unit 140. On the other hand, if the moving object has not been detected in the past, it adds new identification information to the newly generated moving object information and then stores it in the storage unit 140.

[0068] In this way, the image processing device 10 can include information about the individual moving object in the moving object information.

[0069] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure can be made as can be understood by those skilled in the art within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0070] Furthermore, while the flowcharts used in the above description show multiple steps (processes) in sequence, the execution order of the steps performed in each embodiment is not limited to the order in which they are described. In each embodiment, the order of the illustrated steps can be changed to the extent that it does not impair the content.

[0071] Some or all of the above embodiments may also be described as follows, but are not limited to the following: 1. An image processing apparatus comprising: an acquisition means for acquiring a first image including a reference object, which is captured by a first imaging means installed at a first location; and a second image including the reference object, which is captured by a second imaging means installed at a second location; a correction information generation means for generating correction information for correcting at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first image and the second image; and a correction means for correcting a target image including an object captured by at least one of the first imaging means and the second imaging means using the correction information. 2. An image processing apparatus according to 1 above, wherein the target image includes a moving object, and the image processing apparatus comprises a processing means for generating moving object information, which is information about the moving object, by processing the corrected target image. 3. An image processing apparatus according to 2 above, wherein the first location and the second location are bases used for the same type of moving object, and the reference object is the moving object. 4. 5. An image processing apparatus according to item 3 above, wherein the acquisition means identifies at least one of the imaging timings for the first image and the second image using at least one of the movement plan information of the moving object at the first location and the movement plan information of the moving object at the second location. 5. An image processing apparatus according to any one of items 1 to 4 above, wherein the reference object transmits identification information for identifying the reference object by wireless communication, and the acquisition means performs at least one of identifying the imaging timing for the first image using the timing at which the identification information is acquired at the first location, and identifying the imaging timing for the second image using the timing at which the identification information is acquired at the second location.6. An image processing apparatus according to any one of items 1 to 5 above, wherein the surface of the reference object displays identification information for identifying the reference object, at least one of the first imaging means and the second imaging means generates repeated images, and the acquisition means performs at least one of the following: acquiring a plurality of images generated by the first imaging means and processing the plurality of images to identify an image containing the identification information and select the identified image as the first image; and acquiring a plurality of images generated by the second imaging means and processing the plurality of images to identify an image containing the identification information and select the identified image as the second image. 7. An image processing apparatus according to any one of items 1 to 6 above, wherein the correction information generation means further generates the correction information using at least one of first environmental information relating to the environment of the first imaging means at the timing when the first image was generated, and second environmental information relating to the environment of the second imaging means at the timing when the second image was generated. 8. 7. An image processing apparatus according to item 7 above, wherein the first environmental information and the second environmental information include at least one of weather information and light source information. 9. An image processing apparatus according to item 2 above, wherein the moving object is an animal, and the moving object information includes information indicating the type of animal. 10. An image processing apparatus according to item 2 or 9 above, wherein the correction means corrects at least one of the first target image generated by the first imaging means and the second target image generated by the second imaging means, and the moving object information includes information indicating the individual of the moving object. 11. An image processing apparatus according to any one of items 1 to 10 above, wherein the correction information includes information for changing the color of the image.12. An image processing system comprising: a first imaging means installed at a first location; a second imaging means installed at a second location; and an image processing device, wherein the image processing device comprises: acquisition means for acquiring a first image captured by the first imaging means and including a reference object; and a second image captured by the second imaging means and including the reference object; correction information generation means for generating correction information to correct at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first image and the second image; and correction means for correcting a target image including an object captured by at least one of the first imaging means and the second imaging means using the correction information. 13. An image processing method comprising: a hardware device acquiring a first image including a reference object, captured by a first imaging means installed at a first location; a second image including the reference object, captured by a second imaging means installed at a second location; generating correction information for correcting at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first and second images; and correcting a target image including an object captured by at least one of the first and second imaging means using the correction information. 14. A program that provides a computer with: an acquisition means for acquiring a first image including a reference object, which is captured by a first imaging means installed at a first location; a second image including the reference object, which is captured by a second imaging means installed at a second location; a correction information generation means for generating correction information to correct at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first image and the second image; and a correction means for correcting a target image including an object, which is captured by at least one of the first imaging means and the second imaging means, using the correction information. 15. A recording medium on which the program described in 14 above is recorded.

[0072] Furthermore, some or all of the configurations described in Appendices 2 to 11, which are subordinate to Appendice 1 above, may also be subordinate to each of Appendices 12 to 15 in the same way as Appendices 2 to 11. Moreover, not limited to Appendice 1 and Appendices 12 to 15, some or all of the configurations described as appendices may also be subordinate to various hardware, software, various recording means for recording software, or systems, without departing from the embodiments described above.

[0073] This application claims priority based on Japanese Patent Application No. 2025-002759, filed on 8 January 2025, and incorporates all of its disclosures herein.

[0074] 10 Image processing device 20 First imaging unit 30 Second imaging unit 110 Acquisition unit 120 Correction information generation unit 130 Correction unit 140 Storage unit 150 Processing unit

Claims

1. An image processing apparatus comprising: an acquisition means for acquiring a first image including a reference object, which is captured by a first imaging means installed at a first location; a second image including the reference object, which is captured by a second imaging means installed at a second location; a correction information generation means for generating correction information for correcting at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first image and the second image; and a correction means for correcting a target image including an object, which is captured by at least one of the first imaging means and the second imaging means, using the correction information.

2. An image processing apparatus according to claim 1, wherein the target image includes a moving object, and the image processing apparatus comprises processing means for generating moving object information, which is information relating to the moving object, by processing the corrected target image.

3. An image processing apparatus according to claim 2, wherein the first point and the second point are bases used by the same type of mobile body, and the reference object is the mobile body.

4. An image processing apparatus according to claim 3, wherein the acquisition means determines at least one of the imaging timings for the first image and the second image using at least one of the movement plan information of the moving body at the first location and the movement plan information of the moving body at the second location.

5. An image processing apparatus according to any one of claims 1 to 4, wherein the reference object transmits identification information for identifying the reference object via wireless communication, and the acquisition means performs at least one of the following: specifying the timing for capturing a first image using the timing at which the identification information is acquired at the first location, and specifying the timing for capturing a second image using the timing at which the identification information is acquired at the second location.

6. An image processing apparatus according to any one of claims 1 to 5, wherein the surface of the reference object is indicated with identification information for identifying the reference object, at least one of the first imaging means and the second imaging means generates repeated images, and the acquisition means performs at least one of the following: acquiring a plurality of images generated by the first imaging means and processing the plurality of images to identify an image containing the identification information and select the identified image as the first image; and acquiring a plurality of images generated by the second imaging means and processing the plurality of images to identify an image containing the identification information and select the identified image as the second image.

7. An image processing apparatus according to any one of claims 1 to 6, wherein the correction information generation means further generates the correction information using at least one of first environmental information relating to the environment of the first imaging means at the timing when the first image is generated, and second environmental information relating to the environment of the second imaging means at the timing when the second image is generated.

8. An image processing apparatus according to claim 7, wherein the first environmental information and the second environmental information include at least one of weather information and light source information.

9. An image processing apparatus according to claim 2, wherein the moving object is an animal, and the moving object information includes information indicating the type of animal.

10. An image processing apparatus according to claim 2 or 9, wherein the correction means corrects at least one of the first target image generated by the first imaging means and the second target image generated by the second imaging means, and the moving object information includes information indicating an individual moving object.

11. An image processing apparatus according to any one of claims 1 to 10, wherein the correction information includes information for changing the color of an image.

12. An image processing system comprising: a first imaging means installed at a first location; a second imaging means installed at a second location; and an image processing device, wherein the image processing device includes: an acquisition means for acquiring a first image captured by the first imaging means and including a reference object; and a second image captured by the second imaging means and including the reference object; a correction information generation means for generating correction information to correct at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first image and the second image; and a correction means for correcting a target image including an object captured by at least one of the first imaging means and the second imaging means using the correction information.

13. An image processing system according to claim 12, wherein the target image includes a moving object, and the image processing device comprises processing means for generating moving object information, which is information relating to the moving object, by processing the corrected target image.

14. An image processing system according to claim 13, wherein the first point and the second point are bases used by the same type of moving body, and the reference object is the moving body.

15. An image processing method comprising: a hardware device acquiring a first image including a reference object, captured by a first imaging means installed at a first location; a second image including the reference object, captured by a second imaging means installed at a second location; generating correction information for correcting at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first image and the second image; and correcting a target image including an object captured by at least one of the first imaging means and the second imaging means using the correction information.

16. An image processing method according to claim 15, wherein the target image includes a moving object, and the hardware device generates moving object information which is information relating to the moving object by processing the corrected target image.

17. An image processing method according to claim 16, wherein the first point and the second point are bases used by the same type of moving body, and the reference object is the moving body.

18. A recording medium for recording a program that, when executed by a computer, causes the computer to acquire a first image including a reference object, which is captured by a first imaging means installed at a first location, and which is captured by a second imaging means installed at a second location, which is captured by a second imaging means, which is captured by the reference object; generate correction information for correcting at least one of the image captured by the first imaging means and the image captured by the second imaging means using the first image and the second image; and correct a target image including an object, which is captured by at least one of the first imaging means and the second imaging means, using the correction information.

19. A recording medium according to claim 18, wherein the target image includes a moving object, and the operation includes generating moving object information which is information relating to the moving object by processing the corrected target image.

20. A recording medium according to claim 19, wherein the first location and the second location are bases used by the same type of mobile body, and the reference object is the mobile body.

Images