Image processing device and image processing method

Abstract

To accurately detect an upward-facing marker from a captured image of the upward-facing marker.SOLUTION: An image processing device of the present technology includes: a control unit configured to control the flight of an aircraft based on a predetermined flight path including a flight path of the aircraft and a marker position where the upward-facing marker is placed; an imaging unit that is provided on the aircraft and configured to obtain at least one captured image based on the flight path and the marker position; and a detection unit configured to detect the upward-facing marker included in the captured image and output an image of the detected upward-facing marker and the position of the upward-facing marker in the captured image. The upward-facing marker has a shape in which multiple shapes are arranged, and adjacent shapes among the multiple shapes have different brightness or hue. The present technology can be applied, for example, to a case of detecting upward-facing markers installed on the ground from captured images obtained by aerial image capturing.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present technology relates to an image processing device and an image processing method, and in particular to an image processing device and an image processing method that enable, for example, accurate detection of an anti-aircraft sign from a captured image of the anti-aircraft sign. [Background technology]

[0002] For example, a technology has been proposed that makes it easy to measure buildings and other objects in real space by installing anti-aircraft markers, photographing them, and then creating a three-dimensional model based on the control points where the anti-aircraft markers are installed that appear in the captured images (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2005-140550 Summary of the Invention [Problem to be solved by the invention]

[0004] When photographing anti-aircraft markers and using the captured images of the anti-aircraft markers to measure buildings, soil volume, and other items, it is necessary to accurately detect the anti-aircraft markers from the captured images.

[0005] The present technology has been developed in consideration of such circumstances, and makes it possible to accurately detect anti-aircraft markers from captured images of the anti-aircraft markers. [Means for solving the problem]

[0006] The image processing device of the present technology is an image processing device that has a control unit that controls the flight of the aircraft based on a predetermined flight path that includes the flight path of the aircraft and the marker positions where anti-aircraft markers are placed, an imaging unit that is provided on the aircraft and captures at least one captured image based on the flight path and the marker positions, and a detection unit that detects the anti-aircraft markers included in the captured image and outputs the image of the detected anti-aircraft marker and the position of the anti-aircraft marker in the captured image, and the anti-aircraft markers included in the captured image have a shape in which multiple shapes are arranged, and adjacent shapes among the multiple shapes have different brightness or hue.

[0007] The image processing method of the present technology is an image processing method in which the control unit of an image processing device having a control unit, an imaging unit provided on the aircraft, and a detection unit controls the flight of the aircraft based on a flight path of the aircraft and a predetermined flight path that includes a marker position where an anti-aircraft marker having a shape in which a plurality of shapes are arranged and adjacent shapes among the plurality of shapes have different brightness or hue is arranged, the imaging unit captures at least one photographed image based on the flight path and the marker position, the detection unit detects the anti-aircraft marker included in the photographed image, and outputs an image of the detected anti-aircraft marker and the position of the anti-aircraft marker in the photographed image.

[0008] In the image processing device and image processing method of the present technology, the flight of the aircraft is controlled based on a predetermined flight path including the flight path of the aircraft and a marker position where an anti-aircraft marker is placed, the anti-aircraft marker being a shape in which a plurality of shapes are arranged, and adjacent shapes among the plurality of shapes have different brightness or hue; at least one photographed image is captured based on the flight path and the marker position; the anti-aircraft marker contained in the photographed image is detected; and an image of the detected anti-aircraft marker and the position of the anti-aircraft marker in the photographed image are output.

[0009] The detection unit may or may not be provided in the flying object.

[0010] The anti-aircraft marker may have a planar shape in which a plurality of circles having different radii are concentrically arranged, and adjacent circles among the plurality of circles have different brightness or hue.

[0011] The image processing device may be an independent device or an internal block constituting a single device.

[0012] The components of the image processing device can be distributed and housed in multiple devices.

[0013] The program can be provided by transmitting it via a transmission medium or by recording it on a recording medium. [Effects of the Invention]

[0014] According to the present technology, anti-aircraft markers can be detected with high accuracy from captured images of the anti-aircraft markers.

[0015] The effects described here are not necessarily limited to those described herein, and may be any of the effects described in this disclosure. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a diagram illustrating an overview of an embodiment of a soil volume measurement system to which the present technology is applied; [Figure 2] 10 is a flowchart illustrating an example of a workflow for soil volume measurement performed in the soil volume measurement system. [Figure 3] 1 is a plan view showing a first example of an anti-aircraft marker 10. FIG. [Figure 4] FIG. 2 is a plan view showing a second example of an anti-aircraft marker 10. [Figure 5] FIG. 10 is a plan view showing a third example of an anti-aircraft marker 10. [Figure 6] 10 is a perspective view showing an example of a second multi-circular sign as an anti-aircraft sign 10. FIG. [Figure 7] FIG. 2 is a diagram illustrating the colors of the anti-aircraft marker 10. [Figure 8]10A and 10B are diagrams illustrating whether or not mixture of two predetermined colors occurs. [Figure 9] FIG. 2 is a block diagram showing an example of the hardware configuration of a computer serving as a cloud server 30. [Figure 10] FIG. 2 is a block diagram showing an example of the functional configuration of a cloud server 30 that functions as an image processing device (detection device). [Figure 11] 10 is a flowchart illustrating an example of a detection process for detecting an anti-aircraft mark 10. [Figure 12] 10 is a flowchart illustrating an example of detailed processing for binarizing each pixel of a captured image. [Figure 13] FIG. 10 is a diagram showing an example of a template image of an anti-aircraft sign 10 (circles 11 and 12). [Figure 14] 10A and 10B are diagrams showing examples of filters that enhance the colors of the circles 11 and 12 in the candidate region and template image, respectively. [Figure 15] 10 is a flowchart illustrating an example of a process for extracting a distance DF between the hues of the circles 11 and 12 as a feature amount. [Figure 16] FIG. 2 is a block diagram showing an example of the configuration of the drone 20. [Figure 17] FIG. 10 is a diagram illustrating an overview of another embodiment of a soil volume measurement system to which the present technology is applied. [Figure 18] FIG. 1 is a plan view showing a first modified example of an anti-aircraft sign 10 that is a multi-circular sign. [Figure 19] FIG. 10 is a perspective view showing a second modified example of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 20] FIG. 10 is a perspective view showing a third modified example of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 21] FIG. 10 is a perspective view showing a fourth modified example of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 22] FIG. 10 is a perspective view showing a fifth modified example of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 23] FIG. 10 is a perspective view showing a sixth modified example of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 24]FIG. 10 is a perspective view showing a seventh modified example of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 25] FIG. 10 is a perspective view showing an eighth modified example of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 26] FIG. 10 is a perspective view showing a ninth modified example of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 27] FIG. 13 is a perspective view showing a tenth modified example of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 28] FIG. 11 is a perspective view showing an eleventh variant of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 29] This is a plan view showing a 12th variant of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 30] FIG. 13 is a perspective view showing a thirteenth variant of the anti-aircraft sign 10, which is a multi-circular sign. [Figure 31] FIG. 1 is a diagram illustrating an HLS color space. [Figure 32] 1 is a diagram for explaining an outline of detection of an anti-aircraft mark 10 using brightness. FIG. [Figure 33] 1 is a diagram for explaining an outline of detection of an anti-aircraft sign 10 using brightness when the anti-aircraft sign 10 has circles 11 to 13. FIG. [Figure 34] 10 is a flowchart illustrating another example of the detection process. [Figure 35] 10 is a flowchart illustrating an example of detailed processing for binarizing each pixel of a captured image performed in step S131-1. [Figure 36] 10 is a flowchart illustrating an example of processing for extracting the distance between the luminances of the circles 11 and 12 as feature amounts in the feature amount extraction processing performed in step S132. DETAILED DESCRIPTION OF THE INVENTION

[0017] <One embodiment of a soil volume measurement system applying this technology>

[0018] FIG. 1 is a diagram illustrating an outline of an embodiment of a soil volume measurement system to which the present technology is applied.

[0019] In the soil volume measurement system shown in Figure 1, soil volume is measured using a UAV (Unmanned Aerial Vehicle).

[0020] In Fig. 1, an anti-aircraft marker 10 is installed on the ground. The anti-aircraft marker 10 can be installed manually or scattered from an air vehicle such as an unmanned aerial vehicle (e.g., a drone) or a human-operated aircraft. Furthermore, the anti-aircraft marker 10 may be installed on the back of a drone so that the anti-aircraft marker 10 itself can move.

[0021] The anti-aircraft sign 10 is photographed from the air. In Fig. 1, a camera 21 is mounted on a drone 20, and the drone 20 is flown, and the camera 21 mounted on the drone 20 photographs the anti-aircraft sign 10 (aerial photography of the anti-aircraft sign 10).

[0022] A captured image (for example, a still image) obtained by capturing an image of the anti-aircraft beacon 10 with the camera 21 is transmitted to, for example, the cloud server 30 by wireless communication or wired communication.

[0023] Cloud server 30 detects anti-aircraft markers 10 appearing in the captured images by performing image processing on the captured images from camera 21. Furthermore, cloud server 30 creates a three-dimensional model of the terrain on the ground using the detection results of anti-aircraft markers 10, measures the soil volume of the terrain on the ground from the three-dimensional model, and outputs the measurement results of the soil volume measurement.

[0024] The processing performed by the cloud server 30 described above can be performed by the drone 20, not by the cloud server 30. The processing performed by the cloud server 30 described above can be shared between the drone 20 and the cloud server 30.

[0025] Furthermore, the method of aerial photography of the anti-aircraft sign 10 is not limited to the method using the drone 20. In other words, aerial photography of the anti-aircraft sign 10 can be performed using an unmanned aircraft such as the drone 20, as well as, for example, an aircraft piloted by a person, an artificial satellite, or the like.

[0026] The anti-aircraft marker 10 may be made of paper, plastic, or the like, on which a predetermined graphic is printed. The anti-aircraft marker 10 may be made of a stack of flat materials, such as plastic or rubber, in a predetermined shape. The anti-aircraft marker 10 may also be made of a display panel, such as an LCD (Liquid Crystal Display) or an organic EL (Electro Luminescence) display, that displays a predetermined graphic. The anti-aircraft marker 10 may also be made of a reflector or other object that can be unfolded.

[0027] FIG. 2 is a flowchart illustrating an example of a workflow for soil volume measurement performed by the soil volume measurement system of FIG.

[0028] In step S11, for example, a manager who will be performing the soil volume measurement makes a preliminary plan for the soil volume measurement. In the preliminary plan, the flight route of the drone 20 and the position of the control point where the anti-aircraft beacon 10 will be installed are determined.

[0029] In step S12, anti-aircraft beacons 10 are installed at control points set at intervals of, for example, several hundred meters according to a pre-planned plan. The installation of the anti-aircraft beacons 10 can be performed, for example, by hand or by a mobile robot. Furthermore, the anti-aircraft beacons 10 themselves may be mobile robots.

[0030] In step S13, the horizontal position (latitude and longitude) and altitude of the control point where the anti-aircraft beacon 10 is installed are measured.

[0031] In step S14, the drone 20 is flown according to a pre-planned plan, and the camera 21 mounted on the drone 20 takes an aerial photograph of the anti-aircraft marker 10, i.e., photographs of the ground on which the anti-aircraft marker 10 is installed (a specified ground surface area to be measured for soil volume).

[0032] In the aerial photography of the anti-aircraft marker 10, one or more photographed images are captured as photographed image data. Furthermore, the aerial photography of the anti-aircraft marker 10 is performed so that when the photographed ranges shown in all the photographed images are collected, the collection of photographed ranges shows the entire area where the anti-aircraft marker 10 is installed.

[0033] Furthermore, the aerial photography of the anti-aircraft sign 10 is performed so that the photographing range shown in one photographed image partially overlaps with the photographing range shown in another photographed image.

[0034] In step S15, the anti-aircraft beacon 10 installed on the ground is collected, and the photographed image data of the anti-aircraft beacon 10 photographed by the camera 21 is uploaded (transmitted) to the cloud server 30.

[0035] In step S16, the cloud server 30 performs a detection process to detect (an image of) the anti-aircraft marker 10 appearing in the captured image taken by the camera 21.

[0036] In step S17, the cloud server 30 performs a process of generating three-dimensional model data of the ground using the horizontal position and elevation of the control point measured in step S13 and the detection result data of the anti-aircraft sign 10 obtained in the detection process performed in step S16.

[0037] In step S18, the cloud server 30 performs soil volume measurement processing using the three-dimensional model data of the ground, and performs processing to output measurement result data of the soil volume measurement.

[0038] <Anti-aircraft Beacon 10>

[0039] FIG. 3 is a plan view showing a first example of the anti-aircraft sign 10. As shown in FIG.

[0040] The anti-aircraft markers 10 in FIG. 3 are known as star-shaped, X-shaped, and plus-shaped anti-aircraft markers.

[0041] In the star-shaped, X-shaped, and plus-shaped anti-aircraft signs 10, two adjacent regions are colored white and black, respectively, with no hue.

[0042] Here, when photographing an anti-aircraft sign 10 installed on the ground from the air, photographing the anti-aircraft sign 10 from as high an altitude as possible allows a wider range to be photographed and the number of captured images to be reduced.

[0043] By reducing the number of captured images, it is possible to reduce the overlapping range between the captured range shown in one captured image and the captured range shown in another captured image, the time required to upload the captured images to the cloud server 30, and the load on the cloud server 30 when processing the captured images.

[0044] However, when the anti-aircraft marker 10 is photographed from a high altitude, the image of the anti-aircraft marker 10 that appears in the photographed image will be small.

[0045] Furthermore, if the anti-aircraft marker 10 is a marker colored in white and black, such as a star-shaped, X-shaped, or plus-shaped anti-aircraft marker, the white may expand and the black may contract in the captured image, and snow accumulation may create similar patterns due to the black soil on the ground and the white snow, which may reduce the detection accuracy of the anti-aircraft marker 10 from the captured image.

[0046] Furthermore, for star-shaped, X-shaped, or plus-shaped anti-aircraft markers 10, the intersection of the boundary lines (extensions of the boundaries) between the white and black areas (marked areas) is detected as the center of the anti-aircraft marker 10. Therefore, if the white area expands and the black area contracts, the detection accuracy for detecting the center of the anti-aircraft marker 10 may decrease.

[0047] FIG. 4 is a plan view showing a second example of the anti-aircraft sign 10. As shown in FIG.

[0048] In the anti-aircraft sign 10 of FIG. 4, a black circle is arranged within a white rectangle.

[0049] The anti-aircraft marker 10 in Figure 4 has a simpler configuration than the anti-aircraft marker 10 in Figure 3, so an object that appears as a black circle in the captured image may be mistakenly detected as an anti-aircraft marker 10.

[0050] Here, the anti-aircraft sign 10 in FIG. 4 has one circle, and therefore can be called a single-circle sign.

[0051] FIG. 5 is a plan view showing a third example of the anti-aircraft sign 10. As shown in FIG.

[0052] The anti-aircraft sign 10 in FIG. 5 has a planar shape in which a plurality of circles with different radii are arranged concentrically, and adjacent circles among the plurality of circles have different hues.

[0053] Here, the planar shape means the shape of an object depicted in a plan view when the object is represented in the plan view.

[0054] The anti-aircraft sign 10 in FIG. 5 has multiple circles, and can therefore be called a multiple-circle sign.

[0055] According to the anti-aircraft sign 10 of multiple circular signs (similar to the single circular sign in FIG. 4), the anti-aircraft sign 10 can be detected without considering the orientation (rotation) of the anti-aircraft sign 10 shown in the captured image, and the load of the detection process for detecting the anti-aircraft sign 10 can be reduced on the cloud server 30. Furthermore, the center of the anti-aircraft sign 10 can be easily detected.

[0056] FIG. 5A is a plan view showing an example of a first multi-circular sign as the anti-aircraft sign 10. FIG.

[0057] The anti-aircraft sign 10 in Figure 5A has a planar shape in which three circles 11, 12, and 13 of different radii are arranged concentrically, and a rectangular frame area 14, for example, a square or rectangle, is arranged to encompass the three circles 11 to 13.

[0058] In FIG. 5, the radii of the circles 11 to 13 increase in this order.

[0059] Furthermore, in FIG. 5, adjacent circles among circles 11 to 13 have different hues.

[0060] 5, the color of the circle 11 with the smallest radius is, for example, blue, which is a chromatic color (a color with a hue), the color of the circle 12 with the second smallest radius is, for example, red, which is another chromatic color, and the color of the circle 13 with the third smallest (largest) radius is, for example, black, which is an achromatic color.

[0061] In addition, in a multiple-circle sign as an anti-aircraft sign 10, it is sufficient that the hues of adjacent circles are different, and therefore, as long as the hues of adjacent circles 11 and 12 are different and the hues of adjacent circles 12 and 13 are different, the hues of non-adjacent circles 11 and 13 may be the same.

[0062] That is, the colors of the circles 11 to 13 can be, for example, achromatic black, chromatic red, and achromatic black, respectively.

[0063] The frame area 14 can be made of, for example, a rectangular piece of paper or plastic.

[0064] When the frame area 14 is made of rectangular paper, plastic, or the like, the anti-aircraft sign 10 can be constructed, for example, by printing the circles 11 to 13 on the frame area 14 made of paper, plastic, or the like.

[0065] The circles 11 to 13 and the frame region 14 may be made of flat material such as plastic, rubber, etc. In this case, the anti-aircraft sign 10 may be made by stacking the flat material of the circles 11 to 13 and the frame region 14 from bottom to top in the order of the frame region 14, the circles 13, 12, and 11.

[0066] In addition, the anti-aircraft marker 10 can be configured with a display panel such as an LCD or organic EL display, and can function as an anti-aircraft marker 10 by displaying circles 11 to 13 and a frame area 14 on the display panel.

[0067] In addition, in the area of ​​the frame area 14 other than the circles 11 to 13, the date of installation of the anti-aircraft marker 10 and other comments can be written.

[0068] FIG. 5B is a plan view showing an example of a second multi-circular sign as the anti-aircraft sign 10. FIG.

[0069] The anti-aircraft sign 10 in Figure 5B is configured without a frame area 14, unlike the multi-circular sign in Figure 5A. Therefore, the anti-aircraft sign 10 in Figure 5B is configured with three circles 11 to 13 of different radii arranged concentrically.

[0070] FIG. 5C is a plan view showing a third example of a multi-circular sign as the anti-aircraft sign 10. In FIG.

[0071] The anti-aircraft sign 10 in Fig. 5C is configured without the circle 13 and frame area 14, unlike the multi-circular sign in Fig. 5A. Therefore, the anti-aircraft sign 10 in Fig. 5C is configured with two circles 11 and 12 of different radii arranged concentrically.

[0072] FIG. 5D is a plan view showing a fourth example of a multi-circular sign as the anti-aircraft sign 10. In FIG.

[0073] The anti-aircraft sign 10 in Figure 5D is configured without the circle 11 and frame area 14, unlike the multi-circular sign in Figure 5A. Therefore, the anti-aircraft sign 10 in Figure 5D is configured with two circles 12 and 13 of different radii arranged concentrically.

[0074] In addition, other configurations of the anti-aircraft sign 10 can be used, such as a multi-circular sign such as C or D in Figure 5 with a frame area 14, or a configuration in which four or more circles of different radii are arranged concentrically.

[0075] FIG. 6 is a perspective view showing a second example of a multi-circular sign as the anti-aircraft sign 10 of FIG. 5B.

[0076] Here, the second multi-circular sign has a planar shape made up of three circles 11 to 13, and therefore will hereinafter also be referred to as a three-circular sign.

[0077] The three-circular sign serving as the anti-aircraft sign 10 in Figure 6 is composed of a low-height cylindrical member that forms circle 11 (hereinafter also referred to as cylindrical member 11), a flat circular member that forms circle 12 (hereinafter also referred to as circular member 12), and a flat circular member that forms circle 13 (hereinafter also referred to as circular member 13).

[0078] That is, the anti-aircraft sign 10 in FIG. 6 is constructed by stacking a cylindrical member 11, circular members 12 and 13 from bottom to top in the order of circular members 13, 12 and cylindrical member 11.

[0079] The cylindrical member 11 can be made of, for example, plastic (ABS resin) or the like. Furthermore, the cylindrical member 11 can be hollow and can house an illuminance detection device including an illuminance sensor that detects the illuminance of the anti-aircraft beacon 10 (top), a communication device including an antenna and circuitry for wireless communication, and a recording device including a recording medium such as a semiconductor that records information detected by the illuminance detection device in chronological order (all of which are not shown). The anti-aircraft beacon 10 may have these illuminance detection devices and the like built into a part of the anti-aircraft beacon other than the cylindrical member 11. Furthermore, the anti-aircraft beacon 10 may have sensors other than the illuminance sensor built into the cylindrical member 11 or other parts, and data related to the anti-aircraft beacon detected by the sensors may be transmitted by a communication device or recorded by a recording device.

[0080] For example, if an illuminance detection device and a communication device are built into the cylindrical member 11, information on the illuminance detected by the illuminance detection device in the anti-aircraft sign 10 can be transmitted by the communication device.

[0081] Information such as illuminance transmitted from the anti-aircraft beacon 10 can be received by the cloud server 30 and used for processing in the cloud server 30.

[0082] When the columnar member 11 does not incorporate an illuminance detection device, a communication device, or the like, the columnar member 11 can be configured as a flat circular plate, similar to the circular members 12 and 13. Furthermore, the device incorporated in the columnar member 11 can be removed (disconnected) from the columnar member 11 for charging or the like.

[0083] The circular member 12 can be made of a material that is resistant to discoloration by ultraviolet rays, such as rubber. By making the circular member 12 of a material that is resistant to discoloration by ultraviolet rays, when the hue of the color applied to the circular member 12 is used to detect the anti-aircraft marker 10, it is possible to prevent the discoloration of the circular member 12 from reducing the detection accuracy of the anti-aircraft marker 10.

[0084] The circular member 13 can be made of an insulator such as polypropylene. By making the circular member 13 out of an insulator, it is possible to prevent the circular member 12, the cylindrical member 11, and even communication devices and the like built into the cylindrical member 11 from being electrically connected to the ground (earth).

[0085] As will be described later, at least the hue of the color of the circular member 12 is used to identify the anti-aircraft beacon 10 (and to extract candidate areas for the anti-aircraft beacon 10 from the captured image).

[0086] If the anti-aircraft beacon 10 is configured without the circular member 13, the circular member 12 comes into contact with the ground when the anti-aircraft beacon 10 is installed on the ground. Since various colors can exist as the color of the installation location of the anti-aircraft beacon 10, depending on the color of the installation location of the anti-aircraft beacon 10, a large degree of color mixing occurs between the color of the circular member 12 and the color of the installation location of the anti-aircraft beacon 10 in the captured image, and the identification of the anti-aircraft beacon 10 is affected according to the degree of color mixing.

[0087] Therefore, by configuring the anti-aircraft marker 10 with a circular member 13, it is possible to prevent the occurrence of color mixing between the color of the circular member 12 and the color of the location where the anti-aircraft marker 10 is installed.

[0088] In this case, the mixture of the colors of the circular members 12 and 13 affects the identification of the anti-aircraft sign 10.

[0089] However, when anti-aircraft beacon 10 is constructed without circular member 13, the degree of color mixing between the color of circular member 12 and the color of the location where anti-aircraft beacon 10 is installed varies depending on the color of the location where anti-aircraft beacon 10 is installed. Therefore, the degree to which the color mixing between the color of circular member 12 and the color of the location where anti-aircraft beacon 10 is installed affects the identification of anti-aircraft beacon 10 varies depending on the color of the location where anti-aircraft beacon 10 is installed.

[0090] In contrast, when the anti-aircraft sign 10 is configured by providing the circular member 13, the degree of color mixing between the colors of the circular members 12 and 13 does not vary depending on the color of the location where the anti-aircraft sign 10 is installed. Therefore, the degree to which the color mixing between the colors of the circular members 12 and 13 affects the identification of the anti-aircraft sign 10 does not vary depending on the color of the location where the anti-aircraft sign 10 is installed.

[0091] As described above, the circular member 13 can prevent the degree of color mixing that occurs between the color of the circular member 13 and the color of the circular member 12 from varying depending on the color of the location where the anti-aircraft sign 10 is installed.

[0092] Here, the size of the multiple circular signs as anti-aircraft signs 10 can be determined by taking into consideration the portability of the anti-aircraft signs 10 when they are installed by a person, and can be, for example, a size of approximately 30 cm in diameter, such as a square measuring 10 to 30 cm on each side, so that a person can carry a certain number of anti-aircraft signs 10.

[0093] FIG. 7 is a diagram illustrating the colors of the anti-aircraft marker 10.

[0094] Here, as described with reference to FIGS. 1 and 2, the cloud server 30 detects the anti-aircraft markers 10 appearing in the photographed images obtained by aerial photography.

[0095] The cloud server 30 detects the anti-aircraft marker 10, for example, using the hue of the circle (circular member) 12. That is, the cloud server 30 detects the anti-aircraft marker 10, for example, using the hue of the circle 12 itself, or the distance between the hue of the circle 12 and the hue of the circle 11 adjacent to the circle 12.

[0096] Considering that the detection of anti-aircraft marker 10 is performed using the hue of circle 12 itself or the distance between the hues of adjacent circles 11 and 12, it is effective for the colors of circles 11 and 12 to be colors that are unlikely to cause color mixing (colors with a small degree of color mixing) when photographed from a certain altitude, i.e., from the altitude at which aerial photography is planned, for example.

[0097] According to an experiment conducted by the inventor of the present invention, it has been confirmed that color mixing is suppressed when, for example, the color combination of circle 11 and circle 12 is such that circle 11 is black and circle 12 is a color with a different hue from black.

[0098] For example, if the color combination of circle 11 and circle 12 is such that circle 11 is black and circle 12 is red, it has been confirmed that the color mixture will be limited to the extent that the black of circle 11 and the red of circle 12 can be seen in an aerial photograph taken from an altitude of 65 m.

[0099] If the circle 11 is too large compared to the circle 12, the saturation of the circle 12 in the captured image will be low, making it difficult to distinguish the circle 12. On the other hand, if the circle 11 is too small compared to the circle 12, the brightness of the circle 11 in the captured image will be low, making it difficult to distinguish the circle 12.

[0100] Therefore, it is effective to set the sizes of the circles 11 and 12 to a size that makes the circle 12 highly distinguishable.

[0101] According to an experiment conducted by the inventor of the present invention, it has been confirmed that the distinguishability of circle 12 can be improved by making the area of ​​circle 12 excluding circle 11 approximately 1.0 to 3.0 times the area of ​​circle 11.

[0102] Considering that the detection of anti-aircraft marker 10 is performed using the distance between the hues of adjacent circles 11 and 12, it is effective to use a color combination of circles 11 and 12 that is as unlikely to exist in nature as possible.

[0103] Furthermore, it is effective that the color combinations of the circles 11 and 12 are as different in hue as possible.

[0104] Furthermore, it is effective to select a color combination for the circles 11 and 12 that results in as little color mixing as possible when photographed from a certain altitude, that is, a combination that results in as large a distance as possible between the hue of the circle 11 and the hue of the circle 12 obtained from the photographed image.

[0105] FIG. 7 shows an example of a histogram of the hues of the pixels of the circles 11 and 12 obtained from a photographed image of the anti-aircraft sign 10.

[0106] Here, unless otherwise specified, the circle 12 refers to the annular portion of the entire circle as the circle 12 excluding the circle 11 .

[0107] In the histogram of Figure 7, pixels of circle 11 (estimated area) and pixels of circle 12 (estimated area) are detected from the captured image, and the frequency (number of pixels) of pixels having each hue is shown for the pixels of circles 11 and 12.

[0108] In FIG. 7, the horizontal axis represents the hue, and the vertical axis represents the frequency.

[0109] A hue histogram (hereinafter also referred to as a hue histogram) for the pixels of circles 11 and 12 detected from the captured image has two distributions, one with a peak at the first hue and the other with a peak at the second hue, as shown in FIG. 7.

[0110] As the distance between the hues of the circles 11 and 12, for example, the distance between the peaks of the two distributions present in the hue histogram (the difference in hue between the peaks) can be used.

[0111] Furthermore, as the distance between the hues of the circles 11 and 12, for example, the difference between the integrated values ​​of the average hues of the pixels of the circles 11 and 12 detected from the photographed image can be used.

[0112] Now, if we use, for example, the difference in the average hue values ​​of the pixels of circles 11 and 12 detected from the captured image as the distance DF between the hues of circles 11 and 12, then the distance DF between the hues of circles 11 and 12 can be expressed by equation (1).

[0113]

number

[0114] In formula (1), H i,j represents the hue of the pixel at position (i, j) in the captured image. N1 and N2 represent the numbers of pixels in circles 11 and 12 detected from the captured image, respectively. The first term on the right-hand side (Σ) represents the summation of the pixels in circle 11 (pixels in (i, j)∈Area1) detected from the captured image, and the second term on the right-hand side (Σ) represents the summation of the pixels in circle 12 (pixels in (i, j)∈Area2) detected from the captured image.

[0115] In addition, when the pixel values ​​of pixels in the captured image are expressed as R (Red), G (Green), and B (Blue) values ​​in the RGB color space, the R, G, and B values ​​can be converted into hue H (Hue), saturation S (Saturation), and lightness L (Lightness) in the HLS space according to equation (2).

[0116]

number

[0117] In formula (2), max(A, B, C) represents the maximum value among A, B, and C, and min(A, B, C) represents the minimum value among A, B, and C. As shown in formula (2), for hue H, the conversion formula from RGB differs depending on which of the R value, G value, and B value is the minimum value m.

[0118] The distance DF between the hues of the circles 11 and 12 represents the degree of color mixing between the hues of the circles 11 and 12, and the greater the distance DF, the smaller the degree of color mixing.

[0119] Therefore, two predetermined colors whose hue distance DF is equal to or greater than a predetermined threshold value TH can be adopted as the colors of circles 11 and 12, respectively, as colors that are unlikely to cause color mixing (colors with a small degree of color mixing).

[0120] For ease of explanation, two colors whose hue distance DF is equal to or greater than a predetermined threshold value TH will be referred to as colors in which color mixing does not occur, and two colors whose hue distance DF is not equal to or greater than a predetermined threshold value TH will be referred to as colors in which color mixing occurs.

[0121] FIG. 8 is a diagram for explaining whether or not color mixing of two predetermined colors occurs.

[0122] As the distance DF of the hue, for example, the difference in the average value of the hue (absolute difference) in equation (1) is adopted.

[0123] As shown in FIG. 8, a sign of a size comparable to that of the air target sign 10, for example, attached to two adjacent regions where one color c1 and the other color c2 of two predetermined colors c1 and c2 having different hues are adjacent to each other is photographed with a camera to obtain a photographed image in which the sign is reflected. The photographing of the photographed image in which the sign is reflected can be performed, for example, at a distance comparable to the case of performing an aerial photographing of the air target sign 10.

[0124] Furthermore, from the photographed image in which the sign is reflected, the sign (region) is detected, and from the sign, a region A1 to which the color c1 is attached (estimated to be attached) and a region A2 to which the color c2 is attached are specified.

[0125] Then, the hue distance DF between each of the regions A1 and A2 is calculated according to Equation (1) using the pixel values of the pixels of each of the regions A1 and A2.

[0126] When the distance DF is less than the threshold TH (DF < TH), the colors c1 and c2 can be set as two colors in which color mixing occurs (is likely to occur), and these two colors can be excluded from being adopted as the colors of the circles 11 and 12.

[0127] On the other hand, when the distance DF is greater than or equal to the threshold TH (DF >= TH), the colors c1 and c2 can be adopted as the colors of the circles 11 and 12 as two colors in which color mixing does not occur (is unlikely to occur).

[0128] As the threshold TH for the distance DF, for example, the threshold TH represented by Equation (3) can be adopted.

[0129]

Equation

[0130] ​​​Similarly, H2 represents the average hue of pixels in the area assigned with color c2 that appears in a captured image obtained by close-up photography of color c2 alone.

[0131] The average hue values ​​of the pixels in the areas marked with colors c1 and c2 in the captured image obtained by close-up photography are expected to be, for example, the theoretical hues of colors c1 and c2, respectively. Therefore, the theoretical hues of colors c1 and c2 can also be used as H1 and H2.

[0132] According to the threshold TH in equation (3), if the hue distance DF is equal to or greater than 0.5 times the hue difference |H1-H2| between colors c1 and c2, colors c1 and c2 can be adopted as the hues (colors) of circles 11 and 12.

[0133] As described above, by adopting two colors for which the distance DF is equal to or greater than the threshold value TH as the colors of the circles 11 and 12, the decrease in the detection accuracy of the anti-aircraft marker 10 caused by the mixing of the colors of the adjacent circles 11 and 12 can be suppressed, and the anti-aircraft marker 10 can be detected with high accuracy.

[0134] The above points also apply to the colors of the adjacent circles 12 and 13, in addition to the colors of the adjacent circles 11 and 12. That is, by adopting two colors for the circles 11 and 12 that make the distance DF equal to or greater than the threshold value TH, and by adopting two colors for the circles 12 and 13 that make the distance DF equal to or greater than the threshold value TH, the detection accuracy of the anti-aircraft marking 10 can be further improved compared to the case where only two colors for the circles 11 and 12 that make the distance DF equal to or greater than the threshold value TH are adopted.

[0135] Here, in FIG. 8, rectangular regions are used as the regions A1 and A2, but other circular regions similar to the circles 11 and 12, for example, can also be used as the regions A1 and A2, respectively.

[0136] <Configuration example of cloud server 30>

[0137] FIG. 9 is a block diagram showing an example of the hardware configuration of a computer serving as the cloud server 30 in FIG.

[0138] The cloud server 30 includes a built-in CPU (Central Processing Unit) 32 , to which an input / output interface 40 is connected via a bus 31 .

[0139] When a command is input by a user (operator) or the like operating an input unit 37 via an input / output interface 40, the CPU 32 executes a program stored in a ROM (Read Only Memory) 33 in accordance with the command. Alternatively, the CPU 32 loads a program stored on a hard disk 35 into a RAM (Random Access Memory) 34 and executes the program. The CPU 32 is composed of one or more processing circuits.

[0140] As a result, the CPU 32 performs various processes and causes the cloud server 30 to function as a device having predetermined functions. Then, the CPU 32 outputs the processing results of the various processes from the output unit 36 ​​via the input / output interface 40, or transmits them from the communication unit 38, or further records them on the hard disk 35, as necessary.

[0141] The input unit 37 is made up of a keyboard, a mouse, a microphone, etc. The output unit 36 ​​is made up of an LCD, a speaker, etc.

[0142] Furthermore, the programs executed by the CPU 32 can be recorded in advance on the hard disk 35 or the ROM 33 as recording media built into the cloud server 30.

[0143] Alternatively, the program can be stored (recorded) on a removable recording medium 41. Such a removable recording medium 41 can be provided as a so-called package software. Here, examples of the removable recording medium 41 include a flexible disk, a CD-ROM (Compact Disc Read Only Memory), an MO (Magneto Optical) disk, a DVD (Digital Versatile Disc), a magnetic disk, and a semiconductor memory.

[0144] Furthermore, the program can be installed on cloud server 30 from removable recording medium 41 as described above, or can be downloaded to cloud server 30 via a communication network or broadcasting network and installed on built-in hard disk 35. That is, the program can be transferred wirelessly to cloud server 30 from a download site via an artificial satellite for digital satellite broadcasting, or transferred wired to cloud server 30 via a network such as a LAN (Local Area Network) or the Internet.

[0145] As described above, the CPU 32 executes the program to cause the cloud server 30 to function as a device having predetermined functions.

[0146] For example, CPU 32 causes cloud server 30 to function as an image processing device that performs image processing of the captured image from camera 21. In this case, cloud server 30 as an image processing device performs detection processing that detects anti-aircraft beacons 10 that appear in the captured image. Therefore, cloud server 30 can also be said to be a detection device that performs such detection processing.

[0147] FIG. 10 is a block diagram showing an example of the functional configuration of the cloud server 30 that functions as the image processing device (detection device) described above.

[0148] 10, cloud server 30 has a candidate area extraction unit 61, a feature amount extraction unit 62, and a classification unit 63. Candidate area extraction unit 61, feature amount extraction unit 62, and classification unit 63 are configured by, for example, CPU 32 in FIG.

[0149] The captured image from the camera is supplied to a candidate area extraction unit 61 and a classification unit 63 .

[0150] The candidate area extraction unit 61 extracts candidate areas that are candidates for the area in which the anti-aircraft beacon 10 (circle 12) appears from the image of the anti-aircraft beacon 10 captured by the camera 21, and supplies the candidate areas to the feature extraction unit 62.

[0151] The feature extraction unit 62 extracts feature amounts from the candidate regions from the candidate region extraction unit 61 and supplies the extracted feature amounts to the identification unit 63 .

[0152] The identification unit 63 identifies (the area in which) the anti-aircraft sign 10 (circle 12) is shown in the captured image based on the feature amount of the candidate area from the feature amount extraction unit 62.

[0153] That is, the identification unit 63 identifies whether or not a candidate area is an anti-aircraft sign 10 based on the feature amount of the candidate area.

[0154] Then, based on the identification result of the anti-aircraft sign 10, the identification unit 63 detects the anti-aircraft sign 10 from the image captured by the camera 21 and outputs the detection result (for example, an image of the anti-aircraft sign 10, the position of the anti-aircraft sign 10 in the captured image, etc.).

[0155] <Detection process>

[0156] FIG. 11 is a flowchart illustrating an example of a detection process for detecting an anti-aircraft beacon 10, which is performed by the CPU 32 of the cloud server 30 serving as the image processing device of FIG.

[0157] In step S31, the candidate area extraction unit 61 performs a candidate area extraction process to extract a candidate area from an image captured by the camera 21.

[0158] In the candidate area extraction process, in step S31-1, the candidate area extraction unit 61 binarizes each pixel (or its pixel value) of the captured image depending on whether the pixel is of the color assigned to the circle 12 of the anti-aircraft sign 10 or a color other than that color.

[0159] For example, if the color assigned to the circle 12 of the anti-aircraft sign 10 is red, the candidate area extraction unit 61 uses the hue H (Hue) of the red color in the HSV space, which is the color of the circle 12, and determines that pixels with a hue H in the range of 320 to 360 (degrees) that can be considered to be the red hue H are pixels of the color assigned to the circle 12, and sets the pixel value to one of 0 and 1, for example, 1.

[0160] In addition, the candidate area extraction unit 61 determines that pixels whose hue H is outside the range of 320 to 360 (pixels that are not determined to be pixels of the color assigned to circle 12) are pixels that are not pixels of the color assigned to circle 12, and sets the pixel value to 0, which is the other of 0 and 1.

[0161] The pixels of the captured image can be binarized using not only the hue H of the color of the circle 12 in the HSV space, but also the saturation S and the value (luminance) V (Value).

[0162] For example, if the color applied to the circle 12 of the anti-aircraft sign 10 is red, pixels whose hue H in the HSV space is in the range of 320 to 360 and whose saturation S is in the range of 30 to 255 can be determined to be pixels of the color applied to the circle 12.

[0163] Alternatively, pixels whose hue H in the HSV space is in the range of 320 to 360, whose saturation S is in the range of 30 to 255, and whose brightness V is in the range of 50 to 255 can be determined to be pixels of the color marked in circle 12.

[0164] As described above, in the candidate area extraction process, at least the hue of the hue, saturation, and brightness of the color of the circle 12 is used to perform binarization for extracting the candidate area.

[0165] Furthermore, in the candidate area extraction process, by using at least the hue of the circle 12 as well as the saturation and brightness to perform binarization to extract the candidate area, it is possible to extract a more likely candidate area as an area in which the anti-aircraft sign 10 is reflected, thereby improving the detection accuracy of the anti-aircraft sign 10.

[0166] In the candidate area extraction process, in step S31-2, the candidate area extraction unit 61 performs erosion processing on the binarized image obtained by binarizing the captured image, thereby suppressing noise in the binarized image.

[0167] Furthermore, in step S31-3 of the candidate region extraction process, the candidate region extraction unit 61 performs dilation processing (expansion processing) on ​​the binarized image after the erosion processing.

[0168] Then, in step S31-4 of the candidate area extraction process, the candidate area extraction unit 61 performs a contour detection process to detect the contour of the area of ​​pixels in the binary image after the dilation process where the pixel value is 1, i.e., the area of ​​pixels in the captured image where the circle 12 is estimated to be captured.

[0169] Then, in the candidate area extraction process, in step S31-5, the candidate area extraction unit 61 extracts an area corresponding to the smallest rectangle circumscribing the contour detected by the contour detection process from the captured image as a candidate area, and supplies it to the feature extraction unit 62.

[0170] If multiple contours are detected by the contour detection process, a candidate region is extracted for each of the multiple contours.

[0171] In step S32, the feature extraction unit 62 performs a feature extraction process for each candidate area from the candidate area extraction unit 61 to extract the features of that candidate area, and supplies the features of the candidate areas obtained by the feature extraction process to the identification unit 63.

[0172] In the feature extraction process, the feature extraction unit 62 can extract, for example, the following feature amounts of the candidate region.

[0173] That is, the feature extraction unit 62 can obtain, as a feature of the candidate area, for example, the ratio (hereinafter also referred to as the size ratio) between the size of the candidate area and the estimated size of the anti-aircraft sign 10 (circle 12) when the anti-aircraft sign 10 is captured in the captured image.

[0174] Here, the captured image captured by the camera 21 is recorded in a file in, for example, EXIF ​​(Exchangeable Image File Format) format. In the EXIF ​​format file, GPS information such as the date and time of capture, focal length, latitude, longitude, and altitude (altitude) of the capture location, etc. are recorded as metadata of the capture.

[0175] The feature extraction unit 62 estimates the size of the anti-aircraft beacon 10 when it appears in the captured image, for example, from the altitude of the shooting position and the focal length recorded in the EXIF ​​format file.

[0176] The size ratio can prevent candidate areas that are too large or too small from being identified as the anti-aircraft sign 10 (circle 12 area). For example, the closer the size ratio is to 1.0, the more likely the candidate area is to be identified as the anti-aircraft sign 10 (circle 12 area).

[0177] The feature amount extraction unit 62 can obtain, for example, the aspect ratio of the candidate region as the feature amount of the candidate region.

[0178] The aspect ratio of the candidate area can prevent a horizontally or vertically long candidate area from being identified as an anti-aircraft sign 10. For example, the closer the aspect ratio of the candidate area is to 1.0, the more likely the candidate area is to be identified as an anti-aircraft sign 10.

[0179] The feature extraction unit 62 can obtain, as the feature of the candidate area, for example, the correlation (similarity) between the candidate area and the template image of the anti-aircraft sign 10 (circles 11 and 12). For example, the greater the correlation (the more correlative) between the candidate area and the template image, the more likely the candidate area will be identified as the anti-aircraft sign 10.

[0180] The template image of the anti-aircraft beacon 10 is prepared in advance.

[0181] As the correlation, for example, a correlation coefficient or an average value of the squared sum of the differences can be used.

[0182] The feature extraction unit 62 can obtain, as the feature of the candidate area, for example, the correlation between the candidate area and a rotated image of the candidate area. The greater the correlation between the candidate area and the rotated image, the more likely the candidate area is to be identified as an anti-aircraft sign 10.

[0183] The anti-aircraft sign 10 has symmetry because the circles 11 to 13 are arranged concentrically. When identifying the anti-aircraft sign 10 using the correlation between the candidate area and a rotated image of the candidate area as a feature of the candidate area, the symmetry of the anti-aircraft sign 10 can be used to improve the accuracy of identifying the anti-aircraft sign 10.

[0184] When a rotated image is obtained, the candidate image is rotated by a predetermined angle other than an integer multiple of 2π.

[0185] The feature extraction unit 62 can apply, for example, a filter (function) that emphasizes the colors of the circles 11 and 12 to the candidate area and the template image, and determine the correlation between the candidate area and the template image after the filter has been applied as the feature of the candidate area. For example, the greater the correlation between the candidate area and the template image after the filter has been applied, the more likely the candidate area is to be identified as an anti-aircraft sign 10.

[0186] In addition, as a filter to be applied to the candidate area and the template image, in addition to a filter that emphasizes the colors assigned to circles 11 and 12, a filter that emphasizes only the colors assigned to either circles 11 or 12 can be used.

[0187] The feature extraction unit 62 can obtain the distance between the hues of the circles 11 and 12 as the feature of the candidate region.

[0188] That is, assuming that the candidate area is an area circumscribing the circle 12, the feature extraction unit 62 can use the hues of the pixels that reflect the circles 11 and 12 that are likely to be present in the candidate area to determine the distance between the hues of the circles 11 and 12 described in Figure 7, for example, the distance DF in equation (1), as a feature of the candidate area.

[0189] For example, if the distance DF between the hues of the circles 11 and 12 is equal to or greater than the threshold value TH in equation (3), the candidate area is likely to be identified as the anti-aircraft sign 10.

[0190] In step S33, the identification unit 63 identifies, for each candidate area, the anti-aircraft sign 10 (circle 12) (area in which the sign is shown) from the captured image based on the feature of the candidate area from the feature extraction unit 62.

[0191] That is, the identification unit 63 identifies whether or not a candidate area is an anti-aircraft sign 10 based on the feature amount of the candidate area.

[0192] Furthermore, when the candidate area is identified as an anti-aircraft sign 10, the identification unit 63 detects the anti-aircraft sign 10 from the image captured by the camera 21 based on the identification result, and outputs the detection result.

[0193] In the cloud server 30, as described in FIG. 2, a three-dimensional model of the ground is created using the detection results of the anti-aircraft beacons 10 obtained as described above.

[0194] Here, the identification unit 63 can employ any method as an identification method for identifying whether a candidate area is an anti-aircraft sign 10 based on the feature amounts of the candidate area. For example, it is possible to identify whether a candidate area is an anti-aircraft sign 10 by thresholding each feature amount of the candidate area and then using a majority vote of the thresholding processing results or weighted addition of scores representing the processing results. Alternatively, it is possible to input each feature amount of the candidate area into a classifier configured with a pre-trained neural network or the like, and identify whether a candidate area is an anti-aircraft sign 10 based on the output of the classifier in response to the input.

[0195] The feature amounts of the candidate regions extracted by the feature amount extracting section 62 are not limited to the feature amounts described above.

[0196] However, by including the distance DF of the hue of each of the circles 11 and 12 in the feature amount of the candidate area, the anti-aircraft marking 10 can be detected with higher accuracy.

[0197] That is, for example, if the color of circle 12 is red, candidate area extraction unit 61 performs (binarization for) candidate area detection using at least the hue of circle 12, so, for example, an area in which a red pylon is reflected may be extracted as a candidate area. In this case, if the feature amount of the candidate area does not include the distance DF between the hues of circles 11 and 12, there is a high possibility that the candidate area in which the pylon is reflected will be mistakenly identified as anti-aircraft beacon 10.

[0198] On the other hand, when the feature of the candidate area includes the distance DF of the hue of each of the circles 11 and 12, the possibility of mistakenly identifying a candidate area in which a pylon is reflected as an anti-aircraft sign 10 is reduced, thereby improving the detection accuracy of the anti-aircraft sign 10.

[0199] As explained in Figure 6, if the cylindrical member 11 of the anti-aircraft sign 10 has built-in illuminance detection devices that detect the illuminance of the anti-aircraft sign 10, communication devices that perform wireless communication, etc., the cloud server 30 can perform the detection processing of Figure 11 using illuminance information regarding the illuminance of the anti-aircraft sign 10 (distribution of illuminance (brightness) of the anti-aircraft sign 10) detected by the illuminance detection devices from the anti-aircraft sign 10.

[0200] For example, the candidate area extraction unit 61 can extract candidate areas using illuminance information.

[0201] For example, the candidate area extraction unit 61 can use illuminance information to estimate the range of hue, saturation, and brightness of the color of the circle 12 of the anti-aircraft sign 10 that appears in the captured image, and determine that pixels that have a hue, saturation, or brightness within that range are pixels that depict the circle 12, thereby extracting (and binarizing) the candidate area.

[0202] Furthermore, for example, the identification unit 63 can identify the anti-aircraft mark 10 by using illuminance information.

[0203] Specifically, for example, the identification unit 63 compares the distance DF of the hue of each of the circles 11 and 12, which is a feature of the candidate area, with the threshold value TH of equation (3), and based on the comparison result, if the distance DF is equal to or greater than the threshold value TH, it increases the likelihood that the candidate area will be identified as an anti-aircraft sign 10, thereby identifying the anti-aircraft sign 10.

[0204] The identification unit 63 can set the threshold value TH used to identify the anti-aircraft signs 10 as described above by using the illuminance information.

[0205] That is, under the illuminance condition represented by the illuminance information, the identification unit 63 estimates the hue of each pixel of the circles 11 and 12 obtained when photographing the air target sign 10, and uses the average value of the hue (estimated value) of each pixel of the circles 11 and 12 obtained by the estimation as H1 and H2 in Equation (3) to set the threshold TH in Equation (3).

[0206] As described above, by using the illuminance information of the air target sign 10 detected by the illuminance detection device to extract the candidate region and identify the air target sign 10, the detection accuracy of the air target sign 10 can be improved.

[0207] FIG. 12 is a flowchart for explaining an example of the detailed process of binarizing each pixel of the photographed image performed in step S31-1 of FIG. 11.

[0208] In step S51, the candidate region extraction unit 61 selects one of the pixels in the photographed image that has not yet been selected as the target pixel as the target pixel, and the process proceeds to step S52.

[0209] In step S52, the candidate region extraction unit 61 obtains the hue H of the target pixel, and the process proceeds to step S53.

[0210] In step S53, the candidate region extraction unit 61 determines whether the hue H of the target pixel can be regarded as the hue of the color of the circle 12, that is, whether the hue H of the target pixel satisfies the formula α < H and the formula H < β.

[0211] Here, α and β represent the minimum value and the maximum value of the range that can be regarded as the hue of the color of the circle 12, respectively.

[0212] In step S53, if it is determined that the hue H of the target pixel satisfies the formula α < H and the formula H < β, the process proceeds to step S54. In step S54, the candidate region extraction unit 61 sets the pixel value of the target pixel to 1 indicating that the target pixel is a pixel of the hue of the circle 12, and the process proceeds to step S56.

[0213] Also, in step S53, if it is determined that the hue H of the target pixel does not satisfy at least one of the formula α < H and the formula H < β, the process proceeds to step S55. In step S55, the candidate region extraction unit 61 sets the pixel value of the target pixel to 0, indicating that it is not a pixel of the hue of circle 12, assuming that the target pixel is not a pixel of the hue of circle 12, and the process proceeds to step S56.

[0214] In step S56, the candidate region extraction unit 61 determines whether all the pixels of the captured image have been selected as the target pixel.

[0215] In step S56, if it is determined that not all the pixels of the captured image have been selected as the target pixel yet, the process returns to step S51. In step S51, the candidate region extraction unit 61 newly selects one of the pixels of the captured image that have not been selected as the target pixel yet as the target pixel, and the following similar process is repeated.

[0216] Also, in step S56, if it is determined that all the pixels of the captured image have been selected as the target pixel, the binarization process ends.

[0217] FIG. 13 is a diagram showing an example of a template image of the air target sign 10 (circles 11 and 12) used for extracting the feature amount of the candidate region in the feature amount extraction unit 62.

[0218] Now, let the Gaussian function defined by the coefficients a, μ, and σ be represented as Gaussian(a, μ, σ) as shown in formula (4).

[0219]

Equation

[0220] When blue and red, for example, are used as the colors of the circles 11 and 12, respectively, an image defined by a Gaussian function, such as that shown in FIG. 13, can be used as the template image.

[0221] A in FIG. 13 shows a first example of a template image, and B in FIG. 13 shows a second example of a template image.

[0222] Now, the hue as a pixel value of the template image is represented as y, and the variable x of the Gaussian function Gaussian(a, μ, σ) in equation (4) represents the distance from the center of the template image.

[0223] In this case, the hue y of the template image A in Fig. 13 is expressed by the formula y = 360 - Gaussian(a = 50, μ = 0, σ = 0.3). Also, the hue y of the template image B in Fig. 13 is expressed by the formula y = 360 - Gaussian(a = 100, μ = 0, σ = 0.3).

[0224] FIG. 14 is a diagram showing an example of a filter used to enhance the colors of the circles 11 and 12 in the candidate area and the template image, respectively, in the feature extraction process in step S32 of FIG.

[0225] For example, if the colors assigned to circles 11 and 12 are blue and red, respectively, the filter that emphasizes the color assigned to circle 11 is a blue filter that emphasizes blue, and the filter that emphasizes the color assigned to circle 12 is a red filter that emphasizes red.

[0226] Now, the hue output from the filter is represented as y, and the variable x of the Gaussian function Gaussian(a, μ, σ) in equation (4) represents the hue input to the filter.

[0227] In this case, the red filter can be expressed as y=Gaussian(a=255, μ=10, σ=20) (when x is in the range of 10<=x<=180), y=Gaussian(a=255, μ=350, σ=20) (when x is in the range of 180<=x<=350), or y=255 (when x is in any other range).

[0228] The blue filter is expressed by the formula y=Gaussian(a=128, μ=270, σ=40).

[0229] In FIG. 14, the solid line represents the input / output characteristics of the red filter, and the dotted line represents the input / output characteristics of the blue filter.

[0230] 14, image P1 is a candidate area that includes the circle 12, and is an image obtained by resizing a candidate area that uses hue H as a pixel value to 50×50 pixels horizontally and vertically, and extracting the central 30×30 pixels. Image Q1 is a candidate area that does not include the circle 12, and is an image obtained by resizing a candidate area that uses hue H as a pixel value to 50×50 pixels, and extracting the central 30×30 pixels.

[0231] Images P2 and Q2 are images obtained by applying a blue filter to images P1 and Q1, respectively, and images P3 and Q3 are images obtained by applying a red filter to images P1 and Q1, respectively.

[0232] FIG. 15 is a flowchart illustrating an example of the process of extracting the distance DF of the hue of each of the circles 11 and 12 as a feature in the feature extraction process performed in step S32 of FIG.

[0233] In step S71, the feature extraction unit 62 assumes that the candidate area is an area circumscribing circle 12, and detects pixels that reflect (are expected to reflect) circles 11 and 12 in the candidate area (hereinafter referred to as pixels in the area of ​​circle 11 and pixels in the area of ​​circle 12, respectively), and the process proceeds to step S72.

[0234] In step S72, the feature extraction unit 62 obtains the hue H of each pixel in the area of ​​circle 11, and obtains the hue H of each pixel in the area of ​​circle 12, and then the process proceeds to step S73.

[0235] In step S73, the feature extraction unit 62 calculates the average value of the hue H of each pixel in the area of ​​the circle 11 (ΣH i,j / N1) and the average value of the hue H of each pixel in the circle 12 (ΣH in the second term on the right side of Equation (1) i,j / N2) is calculated as the distance DF between the hues of the circles 11 and 12, and the process ends.

[0236] As the anti-aircraft markers 10, for example, a mixture of the single circular marker of Figure 4 and the multiple circular markers of Figures 5 and 6 can be installed, and if the single circular marker can be detected with sufficient accuracy, the single circular marker can be detected without detecting the multiple circular markers, and if the single circular marker cannot be detected with sufficient accuracy, the multiple circular marker can be detected.

[0237] <Drone 20 configuration example>

[0238] FIG. 16 is a block diagram showing an example of the configuration of the drone 20 in FIG.

[0239] In FIG. 16, the drone 20 has a communication unit 111, a control unit 112, a drive control unit 113, and a flight mechanism 114.

[0240] The communication unit 111, under the control of the control unit 112, performs wireless or wired communication with the cloud server 30, a controller (proportional control system) (not shown) that controls the drone 20, and any other device.

[0241] The control unit 112 is composed of a CPU, a memory, and the like (not shown), and controls the communication unit 111, the drive control unit 113, and the camera 21.

[0242] Furthermore, the control unit 112 causes the communication unit 111 to transmit the images captured by the camera 21.

[0243] The drive control unit 113 controls the drive of the flight mechanism 114 according to the control of the control unit 112 .

[0244] The flight mechanism 114 is a mechanism for flying the drone 20, and includes, for example, a motor, a propeller, etc. (not shown). The flight mechanism 114 is driven under the control of the drive control unit 113, and causes the drone 20 to fly.

[0245] In the drone 20 configured as described above, the control unit 112 controls the drive control unit 113 in accordance with, for example, a signal from the proportional control system received by the communication unit 111, thereby driving the flight mechanism 114. As a result, the drone 20 flies in accordance with the operation of the proportional control system.

[0246] Furthermore, the control unit 112 controls the camera 21 to take a photograph in accordance with a signal from the proportional control system. The photographed image obtained by the camera 21 is transmitted from the communication unit 111 via the control unit 112.

[0247] <Another embodiment of the soil volume measurement system to which the present technology is applied>

[0248] FIG. 17 is a diagram illustrating an outline of another embodiment of the soil volume measurement system to which the present technology is applied.

[0249] In the figure, parts corresponding to those in FIG. 1 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0250] The soil volume measurement system of FIG. 17 includes an anti-aircraft beacon 10, a drone 20, a cloud server 30, and a control device 121.

[0251] Therefore, the soil volume measurement system in FIG. 17 differs from that in FIG. 1 in that a control device 121 is newly provided.

[0252] The control device 121 is configured as a dedicated device that functions as a GCS (Ground Control Station) (Ground Station), or alternatively, the control device 121 is configured by a device with a communication function, such as a PC (Personal Computer), a tablet, or a smartphone, that executes a program to cause such a device to function as a GCS.

[0253] The control device 121 communicates with the drone 20 in accordance with the operator's operations, controls the flight of the drone 20, acquires its position, commands the camera 21 mounted on the drone 20 to take pictures, and commands the acquisition of images taken by the camera 21.

[0254] The control device 121, in accordance with the operation of the operator, performs a detection process to detect (an image of) the anti-aircraft sign 10 from the photographed image acquired from the drone 20, and can display the detection result of the anti-aircraft sign 10 obtained by the detection process. From the detection result of the anti-aircraft sign 10, the operator can confirm whether the photograph of the anti-aircraft sign 10 was properly performed.

[0255] If the anti-aircraft sign 10 is not photographed properly, for example, if the anti-aircraft sign 10 cannot be detected during the detection process, the operator can operate the control device 121 to fly the drone 20 again and photograph the anti-aircraft sign 10.

[0256] The control device 121 can upload the captured images acquired from the drone 20 to the cloud server 30.

[0257] Also, for example, as explained in Figure 6, if the anti-aircraft sign 10 has an illuminance detection device or the like built in and transmits illuminance information detected by the illuminance detection device, the illuminance information can be received by the control device 121.

[0258] <Modification of the anti-aircraft sign 10 having multiple circular signs>

[0259] FIG. 18 is a plan view showing a first modified example of the anti-aircraft sign 10 which is a multi-circular sign.

[0260] The anti-aircraft marker 10 in Figure 18 is composed of circles 11 and 12 (or circles 12 and 13) and a frame area 14, and is configured such that, compared to the anti-aircraft marker 10 in Figure 5A, circle 13 (or circle 11) is not provided.

[0261] The anti-aircraft sign 10 in FIG. 18 has a configuration in which a frame area 14 is provided in comparison with the anti-aircraft sign 10 in FIG. 5C (or D).

[0262] In FIG. 18, the colors of the circles 11 and 12 (or circles 12 and 13) and the frame region 14 may be, for example, achromatic black, chromatic red, and achromatic black, respectively.

[0263] FIG. 19 is a perspective view showing a second modified example of the anti-aircraft sign 10 which is a multi-circular sign.

[0264] The anti-aircraft marker 10 in Figure 19 is composed of, for example, a cylindrical member 201 of a predetermined height (thickness) that forms circle 11, an approximately circular ring-shaped member 202 of a predetermined height that forms circle 12, and an approximately circular ring-shaped member 203 of a predetermined height that forms circle 13.

[0265] In FIG. 19, the members 201 to 203 have the same height.

[0266] The member 202 is a roughly circular ring-shaped cylinder of a predetermined height with the center portion hollowed out in a cylindrical shape, and the cylindrical member 201 is fitted into the hollow portion hollowed out in a cylindrical shape of the member 202.

[0267] Similarly, member 203 is an approximately circular ring-shaped cylinder of a predetermined height with the center portion hollowed out in a cylindrical shape, and approximately circular member 202 is fitted into the cylindrical hollow portion of member 203.

[0268] In the anti-aircraft sign 10 of FIG. 19, the inside of the member 201, 202 or 203 is configured to be hollow, and the illuminance detection device etc. described with reference to FIG.

[0269] Furthermore, the illuminance detection device or the like can be built into multiple members 201 to 203.

[0270] 6, the height (thickness) of the cylindrical member that forms circle 11 protrudes compared to the circular member that forms circle 12 and the circular member that forms circle 13. Therefore, depending on the direction of the sunlight, the shadow of the cylindrical member that forms circle 11 may be large on circle 12, which may degrade the detection accuracy of the anti-aircraft sign 10.

[0271] On the other hand, in the anti-aircraft sign 10 of Figure 19, the heights of components 201 to 203 are the same, so the shadow of component 201, which becomes circle 11, is not formed on circle 12 as in the case of Figure 6, and deterioration in the detection accuracy of the anti-aircraft sign 10 can be prevented.

[0272] In addition, the anti-aircraft sign 10 in Figure 19 can be composed of a cylindrical member 201 and approximately circular members 202 and 203, or it can be composed, for example, by coloring the upper surface of one cylindrical member of a predetermined height to form circles 11 to 13.

[0273] Alternatively, the anti-aircraft sign 10 in Figure 19 can be constructed, for example, by coloring a single cylindrical member of a predetermined height with circles 11 and 12 and fitting that member into an approximately annular member 203, or by coloring an approximately annular member with circles 12 and 13 and fitting member 201 into that member.

[0274] Hereinafter, the colors of the circles 11 to 13 will be, for example, achromatic black, chromatic red, and achromatic black, respectively.

[0275] FIG. 20 is a perspective view showing a third modified example of the anti-aircraft sign 10 which is a multi-circular sign.

[0276] In the figure, parts corresponding to those in FIG. 19 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0277] The anti-aircraft marker 10 in Figure 20 is composed of, for example, a cylindrical member 201 of a predetermined height that forms circle 11, an approximately circular ring-shaped member 202 of a predetermined height that forms circle 12, and an approximately circular ring-shaped member 213 of a predetermined height that forms circle 13.

[0278] 20 differs from that of FIG. 19 in that a member 213 is provided instead of the member 203. In FIG.

[0279] The member 213 is in the shape of a roughly circular ring, with the center part of a cylinder of a predetermined height hollowed out in a cylindrical shape while leaving the bottom plate 213A, or in the shape of a roughly circular ring, with the center part of a cylinder of a predetermined height hollowed out in a cylindrical shape and the bottom plate 213A provided.

[0280] The roughly annular member 202 is fitted into a cylindrical hollow portion of the member 203, and the cylindrical member 201 is configured to be detachable from the cylindrical hollow portion of the member 202.

[0281] In addition, the bottom plate 213A is the same color as the member 201, that is, in this case, achromatic black, so that when the cylindrical member 201 is removed from the anti-aircraft sign 10, the bottom plate 213A exposed from the hollow portion of the member 202 functions as the circle 11.

[0282] Furthermore, the depth of the cylindrical hollow portion of member 213 is the same as the height of members 201 and 202. Therefore, when member 202 (and member 201) are fitted into the hollow portion of member 213, the upper surface of anti-aircraft sign 10 becomes flat.

[0283] In the anti-aircraft sign 10 of FIG. 20, the inside of the member 201 is configured to be hollow, and the illuminance detection device and the like described with reference to FIG.

[0284] When illuminance information is required, the anti-aircraft sign 10 can be used by attaching the cylindrical member 201 to the hollow portion of the member 202 that has been hollowed out in a cylindrical shape.

[0285] On the other hand, when illuminance information is not required, the cylindrical member 201 can be removed from the anti-aircraft beacon 10 and the anti-aircraft beacon 10 can be used.

[0286] In the anti-aircraft sign 10 with the cylindrical member 201 removed, a shadow of the member 202 may be formed on the exposed bottom plate 213A, but in this case, since the color of the bottom plate 213A is black, the shadow of the member 202 that may be formed on the exposed bottom plate 213A does not (almost) affect the detection accuracy of the anti-aircraft sign 10.

[0287] The parts 202 and 213 in FIG. 20 can be constructed, for example, by hollowing out the center of a cylindrical member of a predetermined height, leaving the bottom plate 213A, so that the member 201 can be attached and detached, and then coloring the parts to form circles 11 to 13.

[0288] FIG. 21 is a perspective view showing a fourth modified example of the anti-aircraft sign 10 which is a multi-circular sign.

[0289] In the figure, parts corresponding to those in FIG. 20 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0290] The anti-aircraft sign 10 of FIG. 21 is composed of a member 202 and a member 213.

[0291] Therefore, the anti-aircraft sign 10 of FIG. 21 is configured in the same manner as that of FIG. 20, except that the detachable member 201 is not provided.

[0292] In the anti-aircraft sign 10 of FIG. 21, the inside of the member 202 or 213 is configured to be hollow, and the illuminance detection device and the like described with reference to FIG.

[0293] Furthermore, an illumination detection device or the like can be built into both members 202 and 213 .

[0294] In the anti-aircraft sign 10 of Figure 21, as in the anti-aircraft sign 10 of Figure 20 with the cylindrical member 201 removed, a shadow of member 202 may be formed on the exposed bottom plate 213A, but in this case, since the color of the bottom plate 213A is black, the shadow of member 202 that may be formed on the exposed bottom plate 213A does not affect the detection accuracy of the anti-aircraft sign 10.

[0295] FIG. 22 is a perspective view showing a fifth modified example of the anti-aircraft sign 10 which is a multi-circular sign.

[0296] In the figure, parts corresponding to those in FIG. 19 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0297] The anti-aircraft sign 10 in FIG. 22 is composed of members 201 and 202 and a flat circular member 223 that becomes the circle 13.

[0298] 22 is configured in the same manner as in FIG. 19, except that a member 223 is provided instead of the member 203.

[0299] The anti-aircraft sign 10 of Figure 22 is constructed, for example, by fitting member 201 into member 202, and then overlapping member 202 with member 201 fitted in (or a single cylindrical member constructed as circles 11 and 12) on member 223.

[0300] In the anti-aircraft sign 10 of FIG. 22, the inside of the member 201 or 202 is configured to be hollow, and the illuminance detection device and the like described with reference to FIG.

[0301] Furthermore, an illumination detection device or the like can be built into both the members 201 and 202 .

[0302] In the anti-aircraft sign 10 of Figure 22, the shadow of member 202 may be formed on member 223, but in this case, the color of member 223 that becomes circle 13 is black, so the shadow of member 202 that may be formed on member 223 does not affect the detection accuracy of the anti-aircraft sign 10.

[0303] FIG. 23 is a perspective view showing a sixth modified example of the anti-aircraft sign 10 which is a multi-circular sign.

[0304] In the figure, parts corresponding to those in FIG. 22 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0305] The anti-aircraft sign 10 of FIG. 23 is composed of members 201 and 202 and member 223.

[0306] However, the member 201 is configured so as to be detachable from the hollow portion of the member 202 that is hollowed out in a cylindrical shape.

[0307] Furthermore, when member 201 is removed from the hollow portion of member 202, circular portion 223A as part of member 223 is exposed from the hollow portion, and circular portion 223A is the same color as member 201, i.e., in this case, achromatic black, so that it functions as circle 11.

[0308] In the anti-aircraft sign 10 of FIG. 23, the inside of the member 201 is configured to be hollow, and the illuminance detection device and the like described with reference to FIG.

[0309] When illuminance information is required, the anti-aircraft sign 10 can be used by attaching the cylindrical member 201 to the hollow portion of the member 202 that has been hollowed out in a cylindrical shape.

[0310] On the other hand, when illuminance information is not required, the cylindrical member 201 can be removed from the anti-aircraft beacon 10 and the anti-aircraft beacon 10 can be used.

[0311] In the anti-aircraft sign 10 with the cylindrical member 201 removed, the shadow of the member 202 may be cast on the exposed circular portion 223A. Furthermore, regardless of whether the member 201 is attached or detached, the shadow of the member 202 may be cast on the member 223.

[0312] However, in this case, the color of the member 223 including the circular portion 223A is black, and therefore the shadow of the member 202 that may be cast on the member 223 including the circular portion 223A does not affect the detection accuracy of the anti-aircraft sign 10.

[0313] FIG. 24 is a perspective view showing a seventh modified example of the anti-aircraft sign 10, which is a multi-circular sign.

[0314] In the figure, parts corresponding to those in FIG. 23 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0315] The anti-aircraft sign 10 of FIG. 24 is configured in the same manner as that of FIG. 23, except that the detachable member 201 is not provided.

[0316] In the anti-aircraft sign 10 of FIG. 24, the inside of the member 202 is configured to be hollow, and the illuminance detection device and the like described with reference to FIG.

[0317] In the anti-aircraft sign 10 of Figure 24, as in the case of Figure 23, the shadow of member 202 may be formed on circular portion 223A and member 223, but since the color of member 223 including circular portion 223A is black, the shadow of member 202 does not affect the detection accuracy of the anti-aircraft sign 10.

[0318] FIG. 25 is a perspective view showing an eighth modified example of the anti-aircraft sign 10, which is a multi-circular sign.

[0319] In the figure, parts corresponding to those in FIG. 20 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0320] The anti-aircraft sign 10 of FIG.

[0321] As described in Figure 20, the member 213 is in the shape of a roughly circular ring, with the center part of a cylinder of a predetermined height hollowed out in a cylindrical shape while leaving the bottom plate 213A, or in the shape of a roughly circular ring, with the center part of a cylinder of a predetermined height hollowed out in a cylindrical shape and the bottom plate 213A provided.

[0322] 25, however, the bottom plate 213A of the member 213 is colored so that the bottom plate 213A functions as the circles 11 and 12. That is, here, the circular area in the center of the bottom plate 213A is colored black so as to function as the circle 11, and the area around the circle is colored red so as to function as the circle 12.

[0323] In the anti-aircraft sign 10 of FIG. 25, the inside of the member 213 (the part that functions as the circle 13) is configured to be hollow, and the illuminance detection device and the like described with reference to FIG. 6 and the like can be built into the member 213.

[0324] FIG. 26 is a perspective view showing a ninth modified example of the anti-aircraft sign 10, which is a multi-circular sign.

[0325] In the figure, parts corresponding to those in FIG. 25 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0326] The anti-aircraft sign 10 in FIG. 26 is composed of a cylindrical member 231 of a predetermined height that forms the circles 11 and 12, and a member 213.

[0327] 19. The member 231 has a shape (cylindrical shape) similar to that of the member 202 into which the member 201 in FIG. 19 is fitted. The member 231 is colored to resemble the circles 11 and 12 so that the member 231 functions as the circles 11 and 12.

[0328] In the anti-aircraft sign 10 of FIG. 26, the member 231 is detachable from the hollow portion of the member 213.

[0329] In the anti-aircraft sign 10 of FIG. 26, the inside of the member 231 is configured to be hollow, and the illuminance detection device and the like described with reference to FIG.

[0330] When illumination information is required, the member 231 can be mounted in the hollow portion of the member 213 and the anti-aircraft beacon 10 can be used.

[0331] On the other hand, when illuminance information is not required, the member 231 can be removed from the anti-aircraft beacon 10 and the anti-aircraft beacon 10 can be used.

[0332] The member 231 may be formed from a single cylindrical member, or may be formed from, for example, the members 201 and 202 shown in FIG.

[0333] FIG. 27 is a perspective view showing a tenth modified example of the anti-aircraft sign 10, which is a multi-circular sign.

[0334] In the figure, parts corresponding to those in FIG. 19 or FIG. 25 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0335] The anti-aircraft sign 10 in FIG. 27 is constructed by, for example, overlapping the member 201 on the area of ​​the bottom plate 213A of the member 213 that will become the circle 11.

[0336] In the anti-aircraft sign 10 of Figure 27, the inside of member 201 or member 213 (the part that functions as circle 13) is made hollow, and an illuminance detection device, etc., as described in Figure 6, etc., can be built into member 201 or member 213.

[0337] In addition, in the anti-aircraft sign 10 of FIG. 27, the members 201 and 213 are hollow, and the illuminance detection device and the like can be housed separately in the members 201 and 213.

[0338] 27, the anti-aircraft marker 10 in which the circles 11 and 13 have a certain thickness is not limited to the above-described configuration. That is, the anti-aircraft marker 10 in which the circles 11 and 13 have a certain thickness can be configured so that, for example, one or both of the portion that becomes the circle 11 and the portion that becomes the circle 13 are detachable.

[0339] FIG. 28 is a perspective view showing an eleventh modified example of the anti-aircraft sign 10, which is a multi-circular sign.

[0340] The anti-aircraft sign 10 of FIG. 28 is made up of a plate-shaped member 250 having a certain thickness.

[0341] On the top surface of the member 250, circles 11 to 13 are drawn by printing or the like.

[0342] The member 250 may be made of a semi-transparent material, such as white, and may be hollow inside.

[0343] The member 250 may have, for example, a built-in lighting device (not shown).

[0344] In this case, the anti-aircraft marker 10 can be made to emit light by turning on the lighting device.

[0345] By illuminating the anti-aircraft marker 10, the anti-aircraft marker 10 can be photographed in a detectable state even in dark conditions such as at night, and the anti-aircraft marker 10 can be used as a landmark when landing the drone 20.

[0346] FIG. 29 is a plan view showing a twelfth modified example of the anti-aircraft sign 10, which is a multi-circular sign.

[0347] In the anti-aircraft marker 10 of FIG. 29, for example, the red circle 12 and the white frame area 14 are configured with light emitting elements such as LEDs (Light Emitting Diodes).

[0348] By illuminating the red circle 12 and the white frame area 14, the anti-aircraft marker 10 can be photographed in a detectable state even in dark conditions such as at night, and the anti-aircraft marker 10 can be used as a landmark when landing the drone 20.

[0349] FIG. 30 is a perspective view showing a thirteenth modified example of the anti-aircraft sign 10, which is a multi-circular sign.

[0350] The anti-aircraft marker 10 in Figure 30 is a landing pad for drones with the design of the anti-aircraft marker 10 printed or otherwise depicted on it, and therefore functions as both an anti-aircraft marker and a landing pad.

[0351] Here, the landing pad is used to prevent sand and other particles from being kicked up from the ground and getting into the drone's motor when the drone takes off or lands, and to clearly indicate the drone's landing location.

[0352] According to the anti-aircraft marker 10 of FIG. 30, it is possible for the drone 20 to detect the position of the landing pad serving as the anti-aircraft marker 10 from the captured image.

[0353] Furthermore, according to the anti-aircraft marker 10 of Figure 30, by taking into consideration the mounting position of the camera 21 in the drone 20 and controlling the flight state so that the anti-aircraft marker 10 appears in a constant position in the images captured by the camera 21 at all times, it becomes possible to take off and land perpendicular to the anti-aircraft marker 10, thereby increasing the convenience of the landing pad that serves as the anti-aircraft marker 10.

[0354] 30, it is possible to recognize changes in the design of the anti-aircraft marker 10 in the captured image, as well as the takeoff and landing of the drone 20, and record the time of takeoff and landing. Such time can be used to automatically create reports on soil volume measurement, etc.

[0355] <Other embodiments>

[0356] In the above, the anti-aircraft marker 10 used is a marker having a planar shape in which multiple circles of different radii are arranged concentrically, and in which adjacent circles of the multiple circles have different hues.However, the anti-aircraft marker 10 can also be a marker having a planar shape in which multiple circles of different radii are arranged concentrically, and in which adjacent circles of the multiple circles have different brightness or hues.

[0357] That is, in the embodiments of FIGS. 1 to 30, "hue" can be read as "luminance or hue."

[0358] For example, in FIG. 5 and the like, circles 11 to 13 may be circles with adjacent circles having different brightness or hue.

[0359] In addition, in the anti-aircraft sign 10, it is sufficient that the brightness or hue of adjacent circles is different, and therefore, as long as the brightness or hue of adjacent circles 11 and 12 is different and the brightness or hue of adjacent circles 12 and 13 is different, the brightness or hue of non-adjacent circles 11 and 13 may be the same.

[0360] Furthermore, in the anti-aircraft sign 10, adjacent circles may differ in brightness or hue only, or may differ in both brightness and hue.

[0361] When detecting anti-aircraft markers 10 using the luminance distance of adjacent circles 11 and 12, and further, if necessary, the hue distance, it is effective to use a color combination of circles 11 and 12 that is as unlikely to exist in nature as possible.

[0362] Furthermore, it is effective that the combination of colors of the circles 11 and 12 is such that the brightness or hue of each color is as different as possible.

[0363] Furthermore, it is effective to select a combination of the colors of the circles 11 and 12 that results in as little color mixing as possible when photographed from a certain altitude, that is, a combination that results in as large a distance as possible between the brightness or hue of the circle 11 and the brightness or hue of the circle 12 obtained from the photographed image.

[0364] Here, as the hue distance between the circles 11 and 12, the distance between the peaks of the two distributions present in the hue histogram (the difference in hue between the peaks) can be used, as explained in FIG.

[0365] Similarly, the brightness distance between each of the circles 11 and 12 can be the distance between the peaks of two distributions (difference in brightness between the peaks) that appear in a brightness histogram targeting the pixels of the circles 11 and 12 detected from the captured image: a distribution with a peak at the first brightness and a distribution with a peak at the second brightness.

[0366] In addition, as the distance between the hues of the circles 11 and 12, for example, as explained in Figure 7, the difference in the integrated value of the average hue of each pixel of the circles 11 and 12 detected from the captured image (for example, DF in equation (1)) can be used, and similarly, as the distance between the luminance of the circles 11 and 12, the difference in the integrated value of the average luminance of each pixel of the circles 11 and 12 detected from the captured image can also be used.

[0367] The detection of the anti-aircraft mark 10 using brightness and, if necessary, hue will be described below.

[0368] FIG. 31 is a diagram illustrating the HLS color space.

[0369] In the HLS color space 300, the vertical axis represents luminance L, and the distance from the luminance axis on a two-dimensional plane perpendicular to the luminance L axis (hereinafter also referred to as the luminance axis) represents saturation S. The angle around the luminance axis represents hue H. Points on the luminance axis represent achromatic colors.

[0370] FIG. 32 is a diagram for explaining an outline of detection of the anti-aircraft marking 10 using brightness.

[0371] The image processing device of Figure 10 can distinguish between areas that are the anti-aircraft marker 10 and other areas from candidate areas by using the brightness distance (brightness difference) between the circles 11 and 12 (areas assumed (estimated) to be the areas of the anti-aircraft marker 10) of the anti-aircraft marker 10 that appear in the captured image.

[0372] For example, if circle 11 is black and circle 12 is red, the brightness distance between circles 11 and 12 can be used to distinguish relatively accurately between areas that are anti-aircraft markers 10 and areas that are not from the candidate area.

[0373] Furthermore, when the brightness distance between the circles 11 and 12 is small, the image processing device of Figure 10 can distinguish between areas of the anti-aircraft sign 10 and other areas from the candidate area by using the hue distance (hue difference) between the circles 11 and 12 of the anti-aircraft sign 10 shown in the captured image.

[0374] For example, if circle 11 is a chromatic color such as blue and circle 12 is another chromatic color such as red, and the distance between the brightness of circles 11 and 12 is small, the image processing device can use the distance between the hues of circles 11 and 12 to distinguish between areas that are anti-aircraft markers 10 and areas that are not from the candidate area.

[0375] Detection of anti-aircraft markers 10 using brightness can be performed using the brightness distance between adjacent circles 11 and 12, as well as the brightness distance between adjacent circles 12 and 13, and the brightness distance between non-adjacent circles 11 and 13.

[0376] FIG. 33 is a diagram for explaining an outline of detection of an anti-aircraft sign 10 using brightness when the anti-aircraft sign 10 has circles 11 to 13.

[0377] Here, black, red and black circles can be used as the circles 11 to 13, respectively.

[0378] If the anti-aircraft sign 10 has circles 11 to 13, the anti-aircraft sign 10 can be detected using the brightness distance A of each of the circles 11 and 12, the brightness distance B of each of the circles 11 and 13, and the brightness distance C of each of the circles 12 and 13.

[0379] Then, when one or both of the distances A to C, for example, distances A and C, are small, the anti-aircraft sign 10 can be detected using the distance of the hue of each of the circles 11 and 12, the distance of the hue of each of the circles 11 and 13, and the distance of the hue of each of the circles 12 and 13.

[0380] FIG. 34 is a flowchart illustrating another example of the detection process for detecting the anti-aircraft beacon 10, which is performed by the CPU 32 of the cloud server 30 serving as the image processing device of FIG.

[0381] In step S131, the candidate area extraction unit 61 performs a candidate area extraction process to extract a candidate area from an image captured by the camera 21.

[0382] In the candidate area extraction process, in step S131-1, the candidate area extraction unit 61 binarizes each pixel (the pixel value) of the captured image to 1 or 0 depending on whether the pixel is a pixel of the circle 12 of the anti-aircraft beacon 10.

[0383] The binarization in step S131-1 can be performed by, for example, threshold processing of the luminance and hue of the pixels.

[0384] In the candidate area extraction process, in step S131-2, candidate area extraction section 61 performs erosion processing on the binarized image obtained by binarizing the captured image, thereby suppressing noise in the binarized image.

[0385] Furthermore, in step S131-3 of the candidate region extraction process, the candidate region extraction unit 61 performs dilation processing (expansion processing) on ​​the binarized image after the erosion processing.

[0386] Then, in step S131-4 of the candidate area extraction process, the candidate area extraction unit 61 performs a contour detection process to detect the contour of the area of ​​pixels in the binary image after the dilation process where the pixel value is, for example, 1, i.e., the area of ​​pixels in the captured image where the circle 12 is estimated to be captured.

[0387] Then, in the candidate area extraction process, in step S131-5, the candidate area extraction unit 61 extracts an area corresponding to the smallest rectangle circumscribing the contour detected by the contour detection process from the captured image as a candidate area, and supplies it to the feature extraction unit 62.

[0388] If multiple contours are detected by the contour detection process, a candidate region is extracted for each of the multiple contours.

[0389] In step S132, the feature extraction unit 62 performs a feature extraction process for each candidate area from the candidate area extraction unit 61 to extract the features of that candidate area, and supplies the features of the candidate areas obtained by the feature extraction process to the identification unit 63.

[0390] In the feature extraction process of step S132, the feature extraction unit 62 obtains the same feature as in step S32 of FIG. 11, as well as the luminance distance between the circles 11 and 12, for example.

[0391] That is, in the feature extraction process of step S132, the feature extraction unit 62 calculates the luminance distance of each of the circles 11 and 12 instead of the hue distance of each of the circles 11 and 12, and if the luminance distance is small, it calculates the hue distance of each of the circles 11 and 12.

[0392] Here, for example, if the brightness distance in each of FIGS. 11 and 12 is equal to or greater than the brightness distance threshold value calculated in the same manner as the threshold value TH in equation (3), the candidate area is likely to be identified as the anti-aircraft sign 10.

[0393] In step S133, the identification unit 63 identifies, for each candidate area, the anti-aircraft sign 10 (circle 12) (area in which the sign is shown) from the captured image based on the feature of the candidate area from the feature extraction unit 62.

[0394] That is, the identification unit 63 identifies whether or not the candidate area is an anti-aircraft sign 10 based on the feature amount of the candidate area, in the same manner as in step S33 of FIG.

[0395] Furthermore, when the candidate area is identified as an anti-aircraft sign 10, the identification unit 63 detects the anti-aircraft sign 10 from the image captured by the camera 21 based on the identification result, and outputs the detection result.

[0396] In step S133, if the distance between each of the circles 11 and 12 is large (greater than or equal to the threshold value), the identification unit 63 can identify whether the candidate area is an anti-aircraft sign 10 without using the distance between the hues of each of the circles 11 and 12.

[0397] Also, in step S133, if the brightness distance between the circles 11 and 12 is small (not large), the identification unit 63 can use the color distance between the circles 11 and 12 to identify whether the candidate area is an anti-aircraft sign 10.

[0398] As described above, by including the brightness and hue distance of each of the circles 11 and 12 in the feature quantities of the candidate area, the anti-aircraft marking 10 can be detected with higher accuracy.

[0399] FIG. 35 is a flowchart illustrating an example of detailed processing for binarizing each pixel of the captured image performed in step S131-1 of FIG.

[0400] Here, the color of the circle 12 of the anti-aircraft beacon 10 is a chromatic color (for example, red) that has both brightness L and hue H, in order to make it easier to distinguish it from natural colors.

[0401] In step S151, the candidate region extraction unit 61 selects one of the pixels in the captured image that has not yet been selected as the target pixel as the target pixel, and the process proceeds to step S152.

[0402] In step S152, the candidate region extraction unit 61 obtains the luminance L and hue H of the target pixel, and the process proceeds to step S153.

[0403] In step S153, the candidate region extraction unit 61 determines whether the hue H of the target pixel can be regarded as the hue of the color of circle 12, that is, whether the hue H of the target pixel satisfies the formula α < H and the formula H < β.

[0404] Here, α and β respectively represent the minimum value and the maximum value of the range that can be regarded as the hue of the color of circle 12, and are set in advance.

[0405] Furthermore, in step S153, the candidate region extraction unit 61 determines whether the luminance L of the target pixel can be regarded as the luminance of circle 12, that is, whether the luminance L of the target pixel satisfies the formula γ < H and the formula H < δ.

[0406] Here, γ and δ respectively represent the minimum value and the maximum value of the range that can be regarded as the luminance of circle 12, and are set in advance.

[0407] In step S153, if it is determined that the hue H of the target pixel satisfies the formula α < H and the formula H < β, and the luminance L of the target pixel satisfies the formula γ < H and the formula H < δ, the process proceeds to step S154.

[0408] In step S154, the candidate region extraction unit 61 sets the pixel value of the target pixel to 1, which represents that the target pixel is a pixel with the luminance and hue of circle 12, and the process proceeds to step S156.

[0409] Also, in step S153, if it is determined that the hue H of the target pixel does not satisfy at least one of the expressions α < H and H < β, or the luminance L of the target pixel does not satisfy at least one of the expressions γ < H and H < δ, the process proceeds to step S155.

[0410] In step S155, the candidate region extraction unit 61 sets the pixel value of the target pixel to 0, indicating that it is not a pixel of the luminance and hue of circle 12, and the process proceeds to step S156.

[0411] In step S156, the candidate region extraction unit 61 determines whether all pixels of the captured image have been selected as the target pixel.

[0412] In step S156, if it is determined that not all pixels of the captured image have been selected as the target pixel, the process returns to step S151. In step S151, the candidate region extraction unit 61 newly selects one of the pixels in the captured image that have not yet been selected as the target pixel as the target pixel, and the following similar processing is repeated.

[0413] Also, in step S156, if it is determined that all pixels of the captured image have been selected as the target pixel, the binarization process ends.

[0414] FIG. 36 is a flowchart for explaining an example of a process of extracting the distance of the luminance of each of circles 11 and 12 as a feature amount in the feature amount extraction process performed in step S132 of FIG. 34.

[0415] In step S171, assuming that the candidate region is an area circumscribing circle 12, the feature amount extraction unit 62 detects pixels (pixels that should be reflected) in which each of circles 11 and 12 existing in the candidate region is reflected (pixels in the region of circle 11 and pixels in the region of circle 12), and the process proceeds to step S172.

[0416] In step S172, the feature extraction unit 62 obtains the brightness of each pixel in the area of ​​the circle 11 and obtains the brightness of each pixel in the area of ​​the circle 12, and the process proceeds to step S173.

[0417] In step S173, the feature extraction unit 62 calculates the absolute difference between the average brightness value of each pixel in the area of ​​circle 11 and the average brightness value of each pixel in the area of ​​circle 12 as the brightness distance between each of circles 11 and 12, and the processing then ends.

[0418] As described above, the detection of the anti-aircraft sign 10 from the captured image can be performed using one or both of the brightness and hue distances between adjacent circles of the anti-aircraft sign 10.

[0419] Here, in this specification, the processing performed by a computer such as cloud server 30 according to a program does not necessarily have to be performed chronologically in the order described in the flowchart. In other words, the processing performed by a computer according to a program also includes processing executed in parallel or individually (for example, parallel processing or processing by objects).

[0420] The program may be processed by a single computer (processor), or may be distributed among multiple computers. Furthermore, the program may be transferred to and executed on a remote computer.

[0421] Furthermore, in this specification, a system refers to a collection of multiple components (devices, modules (components), etc.), regardless of whether all the components are contained in the same housing. Therefore, multiple devices housed in separate housings and connected via a network, and a single device housed in a single housing with multiple modules, are both systems.

[0422] It should be noted that the embodiments of the present technology are not limited to the above-described embodiments, and various modifications are possible within the scope of the present technology.

[0423] That is, in this embodiment, the present technology has been described as being applied to a soil volume measurement system, but the present technology can be applied to systems other than soil volume measurement systems, for example, systems that perform any measurement using aerial photography of buildings and other anti-aircraft markers.

[0424] Furthermore, this technology can be configured as a cloud computing system in which a single function is shared and processed collaboratively by multiple devices via a network.

[0425] Furthermore, each step described in the above flowchart can be executed by one device, or can be shared and executed by multiple devices.

[0426] Furthermore, when one step includes multiple processes, the multiple processes included in that one step can be executed by one device or can be shared and executed by multiple devices.

[0427] Furthermore, the effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0428] The present technology can have the following configurations.

[0429] <1> It has a planar shape in which a plurality of circles are concentrically arranged, Adjacent circles among the plurality of circles have different luminance or hue a candidate area extraction unit that extracts a candidate area that is a candidate for an area in which the anti-aircraft sign is captured from a captured image of the anti-aircraft sign; a feature extraction unit that extracts features of the candidate region; an identification unit that identifies the anti-aircraft sign based on the feature amount; An image processing device comprising: <2> The candidate area extraction unit extracts the candidate area by using at least the hue of the hue, saturation, and brightness of the circle with the second smallest radius among the plurality of circles. <1> The image processing device according to claim 1. <3> The feature extraction unit extracts, as the feature, a distance between the luminance or hue of a circle having a smallest radius among the plurality of circles and the luminance or hue of a circle having a second smallest radius. <1> or <2> The image processing device according to claim 1. <4> The feature extraction unit extracts, as the feature, a correlation between the candidate region and a rotated image obtained by rotating the candidate region by a predetermined angle other than an integer multiple of 2π. <1> Or <3> 10. The image processing device according to claim 9, wherein <5> The feature extraction unit applies a filter that emphasizes the color of the circle to the candidate area and the template image of the anti-aircraft sign, and extracts a correlation between the candidate area and the template image after the application of the filter as the feature. <1> Or <4> 10. The image processing device according to claim 9, wherein <6> The anti-aircraft marker has a built-in detection device that acquires information about the anti-aircraft marker; The candidate area extraction unit extracts the candidate area by utilizing information about the anti-aircraft signs detected by the detection device. <1> Or <5> 10. The image processing device according to claim 9, wherein <7> The anti-aircraft sign has a built-in illuminance detection device that detects illuminance, the feature extraction unit extracts, as the feature, a distance between a luminance or a hue of a circle having a smallest radius among the plurality of circles and a luminance or a hue of a circle having a second smallest radius; The identification unit compares the distance with a predetermined threshold, and based on the comparison result, sets the predetermined threshold used to identify whether the candidate area is the anti-aircraft sign by utilizing the illuminance of the anti-aircraft sign detected by the illuminance detection device. <1> Or <6> 10. The image processing device according to claim 9, wherein <8> Using the results of the anti-aircraft marking identification, a 3D model is created. <1> Or <7> 10. The image processing device according to claim 9, wherein <9> Measure the soil volume from the 3D model <8> The image processing device according to claim 1. <10> It has a planar shape in which a plurality of circles are concentrically arranged, Adjacent circles among the plurality of circles have different luminance or hue Extracting a candidate area that is a candidate area in which the anti-aircraft sign is captured from a photographed image of the anti-aircraft sign; extracting features of the candidate region; Identifying the anti-aircraft sign based on the feature amount; An image processing method comprising: <11> It has a planar shape in which a plurality of circles are concentrically arranged, Adjacent circles among the plurality of circles have different luminance or hue a candidate area extraction unit that extracts a candidate area that is a candidate for an area in which the anti-aircraft sign is captured from a captured image of the anti-aircraft sign; a feature extraction unit that extracts features of the candidate region; an identification unit that identifies the anti-aircraft sign based on the feature amount; A program that makes a computer function. <12> It has a planar shape in which a plurality of circles with different radii are concentrically arranged, Adjacent circles among the plurality of circles have different luminance or hue Anti-aircraft sign. <13> The plurality of circles includes two circles. <12> The anti-aircraft sign described in. <14> The plurality of circles includes three circles. <12> The anti-aircraft sign described in. <15> The colors of two adjacent circles among the plurality of circles are two predetermined colors such that the distance between the brightness or hue of each of the two areas obtained from a photographed image of a sign in which the colors of the two circles are attached to two adjacent areas is equal to or greater than a predetermined threshold. <12> Or <14> An anti-aircraft sign as described in any of the above. <16> Among the plurality of circles, the circle with the smallest radius and the circle with the second smallest radius are colored in the two predetermined colors. <15> The anti-aircraft sign described in. <17> The area of ​​the second smallest radius circle excluding the smallest radius circle is approximately 1.0 to 3.0 times the area of ​​the smallest radius circle. <16> The anti-aircraft sign described in. <18> The plurality of circles are arranged concentrically, and the plane shape is such that a rectangle encompassing the plurality of circles is arranged. <12> Or <17> An anti-aircraft sign as described in any of the above. <19> An illuminance detection device for detecting illuminance is built into the circle with the smallest radius among the plurality of circles. <12> Or <18> An anti-aircraft sign as described in any of the above. [Explanation of symbols]

[0430] 10 anti-aircraft sign, 11 circle (cylindrical member), 12, 13 circle (circular member), 14 frame area, 20 drone, 21 camera, 30 cloud server, 31 bus, 32 CPU, 33 ROM, 34 RAM, 35 hard disk, 36 output unit, 37 input unit, 38 communication unit, 39 drive, 40 input / output interface, 41 removable recording medium, 61 candidate area extraction unit, 62 feature extraction unit, 63 recognition unit, 111 communication unit, 112 control unit, 113 drive control unit, 114 flight mechanism, 121 control device, 201 to 203, 213, 223, 231, 250 components, 300 HLS color space

Claims

1. a control unit that controls the flight of the aircraft based on a predetermined flight path including a flight path of the aircraft and a marker position where an anti-aircraft marker having an illuminance detection device built in for detecting illuminance is placed; an imaging unit provided in the flying object, which captures at least one photographed image based on the flight path and the marker position; a detection unit that detects the anti-aircraft sign included in the photographed image based on the illuminance of the anti-aircraft sign detected by the illuminance detection device, and outputs an image of the detected anti-aircraft sign and a position of the anti-aircraft sign within the photographed image; and If the detection unit cannot detect the anti-aircraft sign, the control unit controls the flight of the aircraft again, and the imaging unit captures the captured image again, The anti-aircraft sign included in the captured image has a planar shape in which each of a plurality of shapes is arranged adjacent to one or more other shapes, and the brightness or hue of adjacent shapes among the plurality of shapes is different. Image processing device.

2. The detection unit is provided on the flying object. The image processing device according to claim 1 .

3. The detection unit a candidate area extraction unit that extracts a candidate area that is a candidate for an area in which the anti-aircraft sign appears from the captured image; a feature extraction unit that extracts features of the candidate region; an identification unit that identifies the anti-aircraft sign based on the feature amount; The image processing device according to claim 1 , further comprising:

4. The feature extraction unit extracts a correlation between the candidate area and a template image of the anti-aircraft sign as a feature of the candidate area. The image processing device according to claim 3 .

5. The anti-aircraft sign has a planar shape in which a plurality of circles are concentrically arranged, and adjacent circles among the plurality of circles have different brightness or hue. The candidate area extraction unit extracts the candidate area by using at least the hue of the hue, saturation, and brightness of the circle with the second smallest radius among the plurality of circles. The image processing device according to claim 3 .

6. The anti-aircraft sign has a planar shape in which a plurality of circles are concentrically arranged, and adjacent circles among the plurality of circles have different brightness or hue. The feature extraction unit extracts, as the feature, a distance between the luminance or hue of a circle having a smallest radius among the plurality of circles and the luminance or hue of a circle having a second smallest radius. The image processing device according to claim 3 .

7. The anti-aircraft sign has a planar shape in which a plurality of circles are concentrically arranged, and adjacent circles among the plurality of circles have different brightness or hue. The feature extraction unit extracts, as the feature, a correlation between the candidate region and a rotated image obtained by rotating the candidate region by a predetermined angle other than an integer multiple of 2π. The image processing device according to claim 3 .

8. The anti-aircraft sign has a planar shape in which a plurality of circles are concentrically arranged, and adjacent circles among the plurality of circles have different brightness or hue. The feature extraction unit applies a filter that emphasizes the color of the circle to the candidate area and the template image of the anti-aircraft sign, and extracts a correlation between the candidate area and the template image after the application of the filter as the feature. The image processing device according to claim 3 .

9. The anti-aircraft marker has a built-in detection device that acquires information about the anti-aircraft marker; The candidate area extraction unit extracts the candidate area by utilizing information about the anti-aircraft signs detected by the detection device. The image processing device according to claim 3 .

10. The anti-aircraft sign has a planar shape in which a plurality of circles are concentrically arranged, and adjacent circles among the plurality of circles have different brightness or hue. the feature extraction unit extracts, as the feature, a distance between a luminance or a hue of a circle having a smallest radius among the plurality of circles and a luminance or a hue of a circle having a second smallest radius; The identification unit compares the distance with a predetermined threshold, and based on the comparison result, sets the predetermined threshold used to identify whether the candidate area is the anti-aircraft sign by utilizing the illuminance of the anti-aircraft sign detected by the illuminance detection device. The image processing device according to claim 3 .

11. Using the results of the anti-aircraft marking identification, a 3D model is created. The image processing device according to claim 3 .

12. Measure the soil volume from the 3D model The image processing device according to claim 11 .

13. A control unit; an imaging unit provided in the aircraft; Detection unit and An image processing device having The control unit controls the flight of the aircraft based on a predetermined flight path including a flight path of the aircraft and a marker position where an anti-aircraft marker having a planar shape in which each of a plurality of shapes is arranged adjacent to one or more other shapes, adjacent shapes among the plurality of shapes have different brightness or hue, and an illuminance detection device that detects illuminance is built in is arranged; The imaging unit captures at least one photographed image based on the flight path and the marker position; the detection unit detects the anti-aircraft sign included in the photographed image based on the illuminance of the anti-aircraft sign detected by the illuminance detection device, and outputs an image of the detected anti-aircraft sign and a position of the anti-aircraft sign within the photographed image; If the detection unit is unable to detect the anti-aircraft marker, the control unit controls the flight of the flying object again, and the imaging unit captures the photographed image again. An image processing method comprising:

Images