Visibility assessment system, visibility assessment method, and program

Abstract

To provide a field of view determining system, a field of view determining method, and a program capable of determining the quality of a field of view on the basis of an image picked up by a camera.SOLUTION: A field of view determining system 1 is a system that determines the status of a field of view on the basis of an image picked up by a camera 10, and includes: an obtaining unit 13 that obtains a first extraction image T1 having the edge of an imaging object S1 extracted within a first image G1 picked up by the camera 10; and a determining unit 14 that determines the quality of the field of view on the basis of a second extraction image T2 having the edge of the imaging object S1 extracted within a second image G2 picked up by the camera 10 at a different time point from that of the first image G1 and of the first extraction image T1.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a visibility determination system, a visibility determination method, and a program.

[0002] At aircraft (mobile object) takeoff and landing points such as airports and heliports, it is necessary to determine whether the surrounding visibility is good. Traditionally, this has been checked visually by people at the takeoff and landing points, but automation is required.

[0003] Patent Document 1 discloses a technology that is mounted on a vehicle and determines the imaging environment of a camera from the vehicle. Patent Document 2 discloses a technique for checking the visibility of a road. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 3444192 [Patent Document 2] Patent No. 4749142 Summary of the Invention [Problem to be solved by the invention]

[0005] The present disclosure provides a visibility assessment system, a visibility assessment method, and a program that can determine whether visibility is good or bad based on an image captured by a camera. [Means for solving the problem]

[0006] The visibility assessment system of the present disclosure is a system for assessing visibility conditions based on an image captured by a camera, and includes an acquisition unit that acquires a first extracted image in which the edges of a target are extracted from a first image captured by the camera, a second extracted image in which the edges of the target are extracted from a second image captured by the camera at a different time than the first image, and a assessment unit that assesses whether the visibility is good or bad based on the first extracted image.

[0007] According to this configuration, the first extracted image and the second extracted image are obtained by extracting the edges of the target from the first image and the second image taken at different times by the same camera, so that it is possible to determine whether the visibility is good or bad. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram showing the configuration of a visibility determination system according to a first embodiment. [Figure 2] 3A and 3B are diagrams showing an image of a target in a first image and edges extracted from the first image. [Figure 3] FIG. 2 is an explanatory diagram showing a first image, an image in which edges are extracted from the first image, a sky region, and a non-sky region. [Figure 4] FIG. 4 is an explanatory diagram relating to the process of extracting a first region including the edge of a target (island) from the first image from which edges have been extracted. [Figure 5] FIG. 10 is an explanatory diagram relating to a process of generating a second extracted image using a second image, an edge-extracted second image, and a filter. [Figure 6] A diagram showing the target and known altitude in the second region. [Figure 7] 3A to 3C are diagrams showing examples of display modes of a display unit. [Figure 8] FIG. 10 is a diagram showing an example of generating a detour route based on images from cameras installed between the aircraft's starting point and destination point. [Figure 9] FIG. 10 is an explanatory diagram of another detour route. [Figure 10] 4 is a flowchart showing a data generation process executed by the data generation system of the first embodiment. [Figure 11] 3 is a flowchart showing a process executed by the visibility determination system of the first embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] First Embodiment A visibility determination system 1 and a data generation system 2 according to a first embodiment of the present disclosure will be described below with reference to the drawings. The visibility determination system 1 (or a device) of the first embodiment determines whether the visibility is good or bad based on an image captured by a camera. The data generation system 2 generates determination data used by the visibility determination system 1.

[0010] The visibility assessment system 1 can be used as an observation system. As shown in FIG. 1, the visibility assessment system 1 includes one or more cameras 10 that capture images of a target and a computer that processes images captured by the camera 10. The camera 10 may be any camera capable of capturing an image of the target. In the first embodiment, a panoramic camera using a fisheye lens is installed to capture a wide area, including the target, surrounding the camera installation location. The panoramic camera may be installed horizontally to capture images of one or more targets in a specific direction. Alternatively, a first panoramic camera facing a first direction and a second panoramic camera facing the opposite direction from the first direction may be installed back to back. FIG. 2 shows the target (S1) in a first image G1 and an image G3 showing edges extracted from the first image G1. The first image G1 is an image captured by the camera 10. In the first embodiment, as shown in FIG. 2, the target S1 is an island that appears when photographed from the camera installation location facing the sea. In an image obtained from the camera 10, the pixels in the image and their orientations are known.

[0011] The camera 10 does not have to be a panoramic camera using a fisheye lens, but may be a non-panoramic camera that can capture images in only a specific direction. The panoramic camera may also be installed facing vertically upward so that it can simultaneously capture images of multiple surrounding targets.

[0012] [Data Generation System 2] 1, the data generation system 2 includes an edge extraction unit 21, an averaging processing unit 22, and a judgment data generation unit 23. These units (21 to 23) are realized by software and hardware working together when a processor in a computer equipped with a processor such as a CPU, storage such as a memory, various interfaces, etc. executes a program stored in advance in the memory.

[0013] As shown in FIG. 2, the edge extraction unit 21 extracts edges in the first image G1 captured by the camera 10. If the first image G1 includes a target S1 (island), the extracted edges will include the edge of the target S1 (island). An edge is a portion of an image where the intensity of adjacent pixels changes suddenly, and can be extracted by calculating the difference in intensity between pixels. For example, as shown in FIG. 2, an edge extraction process is performed on the first image G1 captured by the camera 10 to obtain an image G3 representing edges. In image G3, white areas represent edges, and black areas represent non-edges. By capturing images multiple times with the camera 10, multiple first images G1 can be obtained in chronological order. The multiple first images G1 may be captured at regular intervals or at random intervals. FIG. 3 is an explanatory diagram showing the first image G1, an image G3 obtained by extracting edges from the first image G1, a sky region P1, and a non-sky region P2. As shown in FIG. 3, the first image G1 includes a sky region P1 that changes with weather conditions and a non-sky region P2 (background portion) where changes due to weather conditions are not or are difficult to observe. By obtaining multiple first images G1 captured at different times, it becomes possible to distinguish between the sky region P1 and the non-sky region P2. In the image on the lower left of FIG. 3, white indicates the sky region P1 and black indicates the non-sky region P2. In the image on the lower right of FIG. 3, gray indicates the sky region P1, and other edges indicate edges other than the sky region P1. Note that the multiple first images G1 do not need to be consecutive in chronological order, but it is preferable that the multiple first images G1 be consecutive in chronological order, as in this embodiment.

[0014] The averaging processor 22 performs averaging processing on multiple images G3 obtained by extracting edges from multiple first images G1 that are consecutive in time series as shown in Figures 2 and 3. The averaging processing makes it possible to distinguish between sky regions P1 and non-sky regions P2. As a specific example, for each image G3 (one frame), processing is performed in which one point value is added to pixels in areas with edges, and no point value is added to pixels in areas without edges. By performing this processing on multiple images G3, it is possible to identify pixels in areas with relatively low point values ​​as sky regions P1 and pixels in areas with relatively high point values ​​as non-sky regions P2.

[0015] The determination data generating unit 23 generates determination data. The determination data is data used in the visibility determining system 1, and includes a first extracted image T1 and a filter 24.

[0016] FIG. 4 is an explanatory diagram illustrating the process of extracting a first region Ar1 including the edge of the target S1 (island) from the first image G1 (image G3 showing the extracted edge) from which edges have been extracted. The first extracted image T1, as shown in FIG. 4, is an image in which the first region Ar1 including the edge of the target S1 (island) is extracted from the first image G1 (image G3 showing the extracted edge) from which edges have been extracted, capturing the entire target S1 (island). The first extracted image T1 is a reference image for comparison and is stored in the storage 1a of the visibility assessment system 1. The first region Ar1 is preferably extracted based on the shape of the outline of the sky area in the image. In the example of FIG. 2, the outline of the target S1 (island) constitutes part of the outline of the sky area. The outline of the sky area is easily obscured and changes depending on weather conditions, making it effective for assessing visibility. The coordinates of the first region Ar1 can be expressed as coordinates within the image G3.

[0017] FIG. 5 is an explanatory diagram illustrating a process for generating a second extracted image T2 using a second image G2, an edge-extracted second image G2 (an image G4 showing the edges), and a filter 24. As shown in FIG. 5, the filter 24 is data used to extract a second region Ar2 (described later) corresponding to the first region Ar1 from the second image G2 captured by the camera 10. The second image G2 is compared with the first extracted image T1 to determine the quality of the visibility, and is an image captured by the camera 10 at a different time than the first image G1. The filter 24 is generated based on the coordinates of the first region Ar1, the sky region P1, and the non-sky region P2 in the first image G1. As an example, the filter 24 extracts only edges within the first region Ar1, including the edge of the target S1 (island) and the area surrounding the edge of the target S1 (island). The filter 24 is stored in the storage 1a of the visibility assessment system 1.

[0018] [Visibility Assessment System 1] 1, the visibility assessment system 1 includes an edge extraction unit 11, a region extraction unit 12, an acquisition unit 13, and a determination unit 14. These units (11 to 14) are realized by software and hardware working together in a computer that includes a processor 1b such as a CPU, a storage 1a such as a memory, various interfaces, etc., and the processor 1b executes a program that is stored in advance in the storage 1a.

[0019] The edge extraction unit 11 has the same function as the edge extraction unit 21 of the data generation system 2. The edge extraction unit 11 extracts edges in the second image G2 captured by the camera 10, and obtains an image G4 representing the edges. If the second image G2 contains a target (island), the extracted edges will include the edges of the island of the target.

[0020] As shown in FIG. 5, the region extraction unit 12 extracts a second region Ar2 corresponding to the first region Ar1 from the second image G2 (image G4 representing the edge) from which the edges have been extracted. The second region Ar2 is a part of the second image G2 (image G4) from which the edges have been extracted. The positional relationship of the second region Ar2 with respect to image G4 is the same as the positional relationship of the first region Ar1 with respect to image G3. The region extraction unit 12 extracts the second region Ar2 from the second image G2 (image G4) from which the edges have been extracted using a filter 24 stored in the storage 1a. As shown in FIG. 5, by applying the filter 24 to the second image G2 (image G4) from which the edges have been extracted, a second extracted image T2 including the second region Ar2 is obtained. If the visibility is good, the second extracted image T2 will include the edge of the target S1 (island). On the other hand, when visibility is poor, the second extracted image T2 does not include the edges of the shooting target S1 (island), or includes fewer edges of the shooting target S1 (island) than when visibility is good.

[0021] The acquisition unit 13 acquires the first extracted image T1 stored in the storage 1a. The storage 1a is a memory in the same computer as the processor 1b, but is not limited to this. For example, the storage 1a may be an external storage device in a computer different from the processor 1b, and the acquisition unit 13 may acquire the first extracted image T1 via a communication network.

[0022] The determination unit 14 determines whether the visibility is good or bad based on the first extracted image T1 including the first region Ar1 and the second extracted image T2 including the second region Ar2. In the first embodiment, the determination unit 14 includes a clarity calculation unit 14a and is configured to calculate the clarity of the visibility as a determination result. The clarity calculation unit 14a calculates the clarity of the visibility based on the ratio of the number of pixels in the second region Ar2 in the second extracted image T2 to the number of pixels in the first region Ar1 in the first extracted image T1. Specifically, the clarity calculation unit 14a calculates the clarity of the visibility as the ratio of the number of pixels of the extracted edge in the second region Ar2 to the number of pixels of the edge in the first extracted image T1 (the number of pixels in the first region). The determination unit 14 determines that the visibility is good if the clarity is equal to or greater than a predetermined value (for example, an index value of 0.8 or a ratio of 80%), and determines that the visibility is poor if the clarity is less than the predetermined value.

[0023] The notification unit 15 is configured to be able to output a warning signal when the clarity calculated by the determination unit 14 is lower than a predetermined clarity threshold (for example, 30% in terms of percentage). As a result, when the calculated clarity is lower than the threshold, it means that the shooting target S1 is obscured by clouds or the like and cannot be seen, so visibility cannot be said to be good, and it is meaningful to output a warning signal to notify. The predetermined clarity threshold may be set in advance or may be set by the user.

[0024] The determination unit 14 may determine the quality of visibility for each altitude of the terrain. FIG. 6 is a diagram showing the shooting target S1 in the second area Ar2 and known altitudes. The same applies to the first area Ar1. For example, in the case of the shooting target S1 (island) shown in FIG. 2, the determination unit 14 determines the altitude of the terrain in the second area Ar2 as shown in FIG. 6. In the example of FIG. 6, the determination unit 14 determines the presence of an edge of the shooting target S1 at three altitudes of 400 m, 200 m, and 50 m according to the shape of the shooting target S1, and determines the quality of visibility for each altitude. The display unit 16 displays the determination results of the quality of visibility for each altitude (including areas with poor visibility) in accordance with the elevation data of the terrain.

[0025] FIG. 7 is a diagram showing an example of the display mode of the display unit 16. As shown in FIG. 7, the display unit 16 can display the elevation distribution on a map, a cross-sectional view of the terrain to be evaluated, a second extracted image that is the extraction result, and the visibility assessment result (including poor visibility areas) all together. On the map, the start point is marked with "S," the destination point is marked with "G," and multiple locations on the line from the start point to the destination point are marked with numbers (1 to 7). The numbers (1 to 7) on the map correspond to the numbers (1 to 7) on the cross-sectional view. The upper part of FIG. 7 is an example of good visibility on a clear day, and poor visibility areas are not shown. The lower part of FIG. 7 is an example of poor visibility at some altitudes on a cloudy day, and altitudes above 180 m are displayed as poor visibility areas.

[0026] Alternatively, a detour route generator 17 may be provided, as shown in FIG. 1. When the detour route generator 17 is provided, the camera is configured to capture 360-degree images. The contour shape of a sky region is set as the capture target, and a first region including the edge of the capture target is set for each direction. The capture target often includes the boundary between the surrounding mountains and the sky. Clarity is calculated for each direction in which the capture target is set. If the contour of the sky region that is the capture target cannot be extracted, visibility is determined to be poor. If the contour of the sky region that is the capture target can be extracted, visibility is determined to be good. FIG. 8 shows an example of generating a detour route based on images from a camera 10 installed between the aircraft's starting point and its destination. The bottom of FIG. 8 shows a 360-degree panoramic image of images captured by a fisheye camera. The top of FIG. 8 shows a map, with the camera's visibility assessment results indicated by circles, triangles, and crosses. From the camera installation location, the shortest route is northwest, but visibility is poor and the shortest route cannot be adopted (indicated by a cross in FIG. 8). Based on the camera image, the determination unit 14 determines that the visibility to the north, east, and south is good. Therefore, the detour route generation unit 17 generates a detour route for the moving object based on the determination result of the determination unit 14 based on the second image G2 obtained from the camera. In the example of Fig. 8, a route R1 that passes through the north is generated.

[0027] The determination unit 14 may also be configured as shown in FIG. 9. FIG. 9 is an explanatory diagram of another detour route. The determination unit 14 determines the quality of the surrounding visibility for each second image G2 obtained from multiple cameras installed at different locations. The detour route generation unit 17 generates a detour route for the moving object based on the determination result of the determination unit 14 based on the second image G2 of each location. When multiple candidate routes are generated, the detour route with the shortest distance may be generated.

[0028] [method] The information processing method executed by the visibility determination system 1 and the data generation system 2 will be described with reference to Fig. 10 and Fig. 11. Fig. 10 is a flowchart showing the data generation process executed by the data generation system 2 of the first embodiment. Fig. 11 is a flowchart showing the visibility determination process executed by the visibility determination system 1 of the first embodiment. The data generation process will be described. In step ST200 shown in FIG. 10, the camera 10 captures first images G1 as learning images at multiple time points. In step ST201, the edge extraction unit 21 performs edge extraction on each of the multiple first images G1. In step ST202, the averaging processing unit 22 performs averaging processing on the edge-extracted images in time series to identify a sky region. In step ST203, based on the images in which the sky region has been identified, the determination data generation unit 23 generates a first extracted image T1 showing a first region Ar1 including an island portion of the shooting target S1, and a filter 24 for extracting the first region Ar1 from the captured image. The visibility assessment process will be described. In step ST100 shown in FIG. 11, the camera 10 captures a second image G2 to be assessed. The second image G2 is captured at a different time than the first image G1. In step ST101, the edge extraction unit 11 extracts edges from the second image G2. In step ST102, the region extraction unit 12 extracts a second extracted image T2 from the edge-extracted second image G2 using the filter 24. The second extracted image T2 has a second region Ar2 that may include the edge of the target S1. In step ST103, the acquisition unit 13 acquires a first extracted image T1 in which the edge of the target S1 is extracted from the first image G1 captured by the camera 10. In step ST104, the assessment unit 14 assesses the visibility based on the first extracted image T1 and the second extracted image T2. Specifically, the clarity calculation unit 14a that constitutes the judgment unit 14 calculates the clarity of the field of view based on the ratio of the number of pixels in the second region Ar2 in the second extracted image T2 to the number of pixels in the first region Ar1 in the first extracted image T1.

[0029] In the above embodiment, the shooting target is a natural object such as an island, a mountain, or the outline of a sky area, but is not limited to this. For example, the shooting target may be a structure such as a building or tower fixed on the ground.

[0030] As described above, as in the first embodiment, the visibility assessment system 1 is a system 1 that assesses visibility conditions based on an image captured by a camera 10, and may include an acquisition unit 13 that acquires a first extracted image T1 in which the edge of the target S1 is extracted from a first image G1 captured by the camera 10, a second extracted image T2 in which the edge of the target S1 is extracted from a second image G2 captured by the camera 10 at a different time than the first image G1, and a assessment unit 14 that assesses whether the visibility is good or bad based on the first extracted image T1.

[0031] According to this configuration, the first extracted image T1 and the second extracted image T2 are used, which are obtained by extracting the edges of the target S1 from the first image G1 and the second image G2 taken at different times by the same camera 10, making it possible to determine whether the visibility is good or bad.

[0032] As in the first embodiment, the visibility assessment method may include obtaining a first extracted image T1 in which the edges of the target S1 are extracted from a first image G1 captured by the camera 10, and assessing the quality of the visibility based on a second extracted image T2 in which the edges of the target S1 are extracted from a second image G2 captured by the camera 10 at a different time than the first image G1, and the first extracted image T1.

[0033] Although not particularly limited, as in the system of the first embodiment, the first extracted image T1 may be generated by performing an averaging process on multiple first images G1 (images G3) from which edges have been extracted. The multiple first images G1 include not only the background but also changes over time in the obstructions of the shooting target S1, and by averaging the multiple first images G1, a first extracted image T1 that appropriately reflects the changes over time can be generated.Since the first extracted image T1 that is appropriate for the location is used, the accuracy of the judgment can be improved.

[0034] Although not particularly limited, as in the system 1 of the first embodiment, the first extracted image T1 is generated by extracting a first region Ar1 that is part of the edge-extracted first image G1 and includes the edge of the shooting target S1, and the visibility assessment system 1 further includes a region extraction unit 12 that extracts a second region Ar2 that is part of the edge-extracted second image G2 and corresponds to the first region Ar1, and the assessment unit 14 may assess the quality of the visibility based on the first extracted image T1 that includes the first region Ar1 and the second extracted image T2 that includes the second region Ar2 extracted by the region extraction unit 12. In this way, the first area Ar1 includes the edge of the target S1 and is part of the first image G1, and the second area Ar2 may include the edge of the target S1 and is also part of the image, thereby improving the accuracy of the judgment.

[0035] Although not particularly limited, as in the first embodiment, the first area Ar1 may be an area extracted based on the shape of the outline of an empty area in the first image G1. This configuration makes it possible to identify the positions of shooting targets such as clouds in the sky, the horizon adjacent to the sky, mountains, and islands, and extract the first area Ar1. These shooting targets are included in the second area Ar2 and are easily affected by weather, so the accuracy of determining visibility can be improved.

[0036] Although not particularly limited, as in the system of the first embodiment, the system may be provided with a clarity calculation unit 14a that calculates the clarity of the field of view based on the ratio of the number of pixels in the second region Ar2 in the second extracted image T2 to the number of pixels in the first region Ar1 in the first extracted image T1. This is useful because it makes it possible to express the quality of visibility in terms of clarity.

[0037] Although not particularly limited, as in the system of the first embodiment, the system may be provided with an alarm unit 15 that outputs a warning signal when the clarity calculated by the clarity calculation unit 14a is lower than a predetermined clarity threshold. If visibility becomes poor, the system will output a warning signal, making it more useful than manual monitoring, as it allows for automatic monitoring.

[0038] Although not particularly limited, as in the system of the first embodiment, a detour route for a moving body may be generated based on the judgment result of the judgment unit 14 based on the second image G2 obtained from multiple cameras 10 installed at different locations. It is possible to provide a detour route for a moving object that takes into account visibility.

[0039] Although not particularly limited, the determining unit 14 may determine whether the visibility is good or bad for each altitude of the terrain, as in the system of the first embodiment. This configuration is useful because it determines whether visibility is good or bad for each altitude of the terrain.

[0040] Although not particularly limited, like the system of the first embodiment, a display unit 16 may be provided that displays the poor visibility area based on the determination result of the determination unit 14 in accordance with the altitude data of the terrain. This configuration is useful because it allows poor visibility areas to be understood in relation to the elevation data of the terrain.

[0041] Although not particularly limited, as in the first embodiment, the shooting target may include a natural object or a structure fixed on the ground. Any object can be used as a shooting target as long as its position relative to the camera remains unchanged, making it useful for visibility assessment operations.

[0042] Although not particularly limited, the visibility determination system 1 may further include a camera 10, as in the first embodiment.

[0043] A program according to this embodiment causes one or more processors to execute the above-described method. Specifically, the program according to this embodiment causes one or more processors to acquire a first extracted image in which the edges of a target are extracted from a first image captured by a camera, and determine whether visibility is good or bad based on a second extracted image in which the edges of the target are extracted from a second image captured by the camera at a different time from the first image, and the first extracted image. A computer-readable temporary recording medium according to this embodiment stores the program.

[0044] Although the embodiments of the present disclosure have been described above with reference to the drawings, the specific configurations should not be considered to be limited to these embodiments. The scope of the present disclosure is defined not only by the description of the above embodiments but also by the claims, and further includes all modifications within the meaning and scope of the claims.

[0045] For example, the order of execution of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings, can be implemented in any order, as long as the output of a previous process is not used in a subsequent process. Even if the flow in the claims, specifications, and drawings is explained using terms such as "first" and "next" for convenience, this does not mean that the processes must be executed in this order.

[0046] Each unit (11 to 17, 21 to 23) shown in FIG. 1 is realized by executing a predetermined program on one or a processor, but each unit may be configured with a dedicated memory or dedicated circuit.

[0047] In the system of the above embodiment, each unit is implemented in the processor 1b of a single computer, but each unit may be distributed and implemented on multiple computers or in the cloud. In other words, the above method may be executed by one or multiple processors.

[0048] 1, the visibility determination system 1 and the data generation system 2 are implemented separately, but this is not limiting. For example, the components constituting the data generation system 2 may be incorporated into the visibility determination system 1.

[0049] The structures employed in the above-described embodiments can be employed in any other embodiment. For the sake of convenience, the various units (11 to 17) are shown in FIG. 1, but some of these units can be omitted as desired. For example, the notification unit 15, display unit 16, and detour route generation unit 17 can be provided as desired.

[0050] The specific configuration of each part is not limited to the above-described embodiment, and various modifications are possible within the scope of the present disclosure. [Explanation of symbols]

[0051] 1. Visibility Assessment System 12 Region extraction part 13 Acquisition Department 14 Judgment section 14a Clarity calculation section 15. Information Department 16 Display 17 Detour route generation unit G1 1st image G2 2nd image S1 Shooting Target T1 First extracted image T2 Second extracted image

Claims

1. A system for determining visibility conditions based on images captured by a camera fixed on the ground, an acquisition unit that acquires a first extracted image by extracting an edge of a target in a first image captured by the camera; a determination unit that determines whether the visibility was good or bad at the time the second image was captured based on a ratio of the number of pixels of the edge in the first extracted image to the number of pixels of the edge in the second extracted image, the second extracted image being an extracted image of the edge of the target in the second image captured by the camera at a time different from that of the first image; Equipped with A visibility determination system, wherein the first extracted image is generated by performing an averaging process on a plurality of the first images from which edges have been extracted.

2. The visibility determination system according to claim 1 , wherein the first extracted image is generated by performing an averaging process on a plurality of the first images from which edges have been extracted.

3. the first extracted image is generated by extracting a first region that is a part of the edge-extracted first image and includes an edge of the target; the visibility determination system further includes a region extraction unit that extracts a second region that is part of the edge-extracted second image and corresponds to the first region; The visibility assessment system according to claim 1 or 2, wherein the assessment unit assesses visibility based on the first extracted image including the first region and the second extracted image including the second region extracted by the region extraction unit.

4. The visibility determination system according to claim 3 , wherein the first region is an area extracted based on the shape of an outline of a target in an empty area in the first image.

5. 2. The visibility assessment system of claim 1, further comprising an alarm unit that outputs a warning signal when the clarity of visibility at the time the second image was captured, calculated based on the ratio of the number of pixels of the edge in a second extracted image in which the edge of the target is extracted in a second image captured by the camera at a different time from the first image, to the number of pixels of the edge in the first extracted image, is lower than a predetermined clarity threshold.

6. 5. The visibility determination system according to claim 3, wherein a positional relationship of the first region to the first extracted image is the same as a positional relationship of the second region to the second extracted image.

7. 7. The visibility determination system according to claim 1, wherein a detour route for a moving object is generated based on a determination result of the determination unit based on the second images obtained from a plurality of cameras installed at different locations.

8. The visibility determination system according to claim 1 , wherein the determination unit determines whether the visibility is good or bad for each altitude of the terrain.

9. 9. The visibility determination system according to claim 1, further comprising a display unit that displays the poor visibility area based on the determination result of said determination unit in accordance with altitude data of the terrain.

10. 10. The visibility determination system according to claim 1, wherein the target includes a natural object or a structure fixed on the ground.

11. The visibility determination system according to claim 1 , further comprising the camera.

12. acquiring a first extracted image by extracting an edge of a target in a first image captured by a camera fixed on the ground; determining whether the visibility was good or bad at the time when the second image was captured based on a ratio of the number of pixels of the edge in the first extracted image to the number of pixels of the edge in the second extracted image, the second extracted image being obtained by extracting the edge of the target in the second image captured by the camera at a time different from that of the first image; Including, A visibility determination method, wherein the first extracted image is generated by performing an averaging process on a plurality of edge-extracted first images.

13. acquiring a first extracted image by extracting an edge of a target in a first image captured by a camera fixed on the ground; determining whether the visibility was good or bad at the time when the second image was captured based on a ratio of the number of pixels of the edge in the first extracted image to the number of pixels of the edge in the second extracted image, the second extracted image being obtained by extracting the edge of the target in the second image captured by the camera at a time different from that of the first image; on one or more processors, The first extracted image is generated by performing an averaging process on a plurality of the first images from which edges have been extracted.

Images