KR102204040B1 - Image processing system for unifying collecting images by altitude - Google Patents

Abstract

The present invention relates to an image processing apparatus for correction for unifying images collected at different altitudes. According to the present invention, the image processing apparatus for correction for unifying images collected at different altitudes comprises: an information DB; a correction target detection module; an image analysis module; an object image extraction module for designating an object image as a correction target; an editing module for generating an image map image; a shadow section search module; a resolution adjustment module; and an altitude image designation module. According to the present invention, a complete collected image can be generated.

Description

Image processing device for correction for unification of collected images by altitude {IMAGE PROCESSING SYSTEM FOR UNIFYING COLLECTING IMAGES BY ALTITUDE}

The present invention is a method of expanding or reducing the unified image map image to adjust the height of the viewpoint and to increase the visual effect, the unification of the collected image by elevation by adjusting the output resolution of the image map image and the dark section for each ground image It relates to an image processing apparatus for correction for.

In the conventional video map image, one image is enlarged or reduced to correspond to the user's viewpoint altitude. However, since this output method simply enlarges or reduces the image map image and outputs it to the monitor, the visual realism felt by the user was low, and the artificiality of the artificially produced image map image was doubled through the editing process over several times.

Therefore, an image processing technology is required to increase the visual realism felt when the image map image is enlarged or reduced through height adjustment of the viewpoint.

Meanwhile, an image, which is a reference image of a drawing for making an image map or a digital map, is collected through aerial photography. The collected images are classified based on the reference point, overlapped, and edited to create a collection image. In the collected images, blind spots (a2; see Fig. 1) and shaded zones (hereinafter referred to as'blind spots') are generated by topographical structures and ground objects such as buildings or various vegetation, and even the same ground objects are blind spots according to the shooting angle. The scope of (a2) can be varied.

However, since the blind spot (a2) makes it impossible to accurately identify a specific area visually or visually in the collected image, the collected image having the blind spot (a2) could not be used as it is for the production of an image map or digital map. Eventually, a field survey was conducted on the blind spot (a2) separately, and the location coordinates of the blind spot (a2) and the shape and occupied range of ground objects were identified and utilized in the production of image maps or digital maps.

However, this production method was burdensome in terms of cost and business, and the burden was not small in terms of time as a number of blind spots (a2) had to be inspected on-site.

In the end, there is an urgent need for a technology capable of quickly identifying, restoring and correcting the blind spot (a2).

Prior Art Document 1. Patent Registration No. 10-1938402 (announced on January 15, 2019)

Accordingly, the present invention is to solve the above problem, and the collected image for each elevation can be unified into one image map image and output in a realistic sense according to the viewpoint of each elevation, and the blind spot is identified from the collected image and restored to its original shape. And it is a task to solve the provision of an image processing device for correction for unification of collected images by elevation that can generate complete collection images as basic data for map generation.

In order to achieve the above object, the present invention,

An information DB for storing collected images, cadastral map information in which parcels are classified according to GPS coordinates, and GPS coordinate values and specification data of ground objects;

A correction target detection module for designating a correction target range of the collected image in proportion to the collection altitude of the collected image retrieved from the information DB;

In the collected image, the RGB values of pixels within the range to be corrected are checked, and the RGB values of the pixels of the chromaticity belonging to the designated representative chromaticity group are unified with the corresponding representative chromaticity, and the position values of the pixels unified with the representative chromaticity are checked. The cluster shape of pixels having RGB values is standardized through deep learning, the standardized cluster shape is set as an independent shape image, a collection of three or more shape images in contact with each other is designated as an object image, and the shape of the object image An image analysis module that designates a shape image having the largest area among the images as a flat shape, and designates another shape image as a side shape;

If the outline of the object that is not in contact with the planar shape among the side shapes of the object image is located at a reference ratio or more in the range to be corrected, and the width of one side shape relative to the total width of the flat shape and one side shape is within the reference value, the object image is corrected. An object image extraction module designated as a target;

A first edited image is created in which the plane shape is aligned with the object outline and the side shape is deleted, and the data of the ground object corresponding to the GPS coordinate value of the object image is retrieved from the information DB, and the distance between the ground object and the shooting point Value, shooting altitude, height of the ground object, GPS coordinate value of the shooting point, and GPS coordinate value of the ground object are checked, and the distance value, shooting altitude and height value, and the GPS coordinate value of the shooting point and the GPS coordinate value of the ground object are proportional Then, the first edited image is enlarged at the ratio of the vector amount to generate a second edited image, and the cadastral map information corresponding to the correction target range of the collected image is retrieved from the information DB, and the cadastral map image is overlapped with the correction target range, and the cadastral map An editing module for generating an edited video image by deleting the collected image for each lot according to the parcel boundary of the image, and synthesizing the second edited image with a corresponding deletion area of the edited video image to generate an image map image;

A dark section search module for setting a range of a dark section around the ground object visually displayed according to the height and width of the ground object of the second edited image and the photographing altitude from the specification data checked by the editing module in the second edited image;

A resolution adjustment module configured to set the resolution for each elevation of the viewpoint so that the elevation adjustment effect of the viewpoint is visually expressed by expanding or reducing the image map image; And

An elevation image designation module for visually adjusting and outputting a range of dark regions set for each second edited image and a resolution of the image map image as the image map image is enlarged or reduced;

It is an image processing device for correction for unification of the collected images by altitude including a.

In the present invention, the collected image for each elevation can be unified into one image map image and output in a realistic way according to the viewpoint of each elevation, and the blind spot in the collected image is identified and restored to its original shape, and basic data for map generation It has the effect of generating a complete collection image.

1 is a diagram schematically showing a collection of collected images corrected by an image processing apparatus according to the present invention,
2 is a block diagram showing an embodiment of a module configured in the image processing apparatus according to the present invention,
3 and 4 are views showing a state in which the image processing apparatus according to the present invention searches for a dark section around a second edited image based on the specification data of the ground object,
5 is a diagram showing a state in which a dark area is displayed around a second edited image in accordance with the dark area searched in FIGS. 3 and 4;
6 is a flowchart sequentially showing the operation process of the image processing apparatus according to the present invention.
7 is a diagram showing a criterion for detecting whether an object image is to be corrected by an image processing apparatus according to the present invention;
8 is a diagram showing an cadastral view of a collected image area searched by an image processing apparatus according to the present invention;
9 is a diagram schematically illustrating a case of synthesizing an cadastral map to a collected image before editing,
10 is an image showing the image processing apparatus according to the present invention deleting the parcel where the object image to be corrected is located from the collected image,
11 and 12 are diagrams schematically showing a change in the planar shape of the object image for each photographing angle,
13 is a diagram schematically showing a state in which an image processing apparatus according to the present invention corrects a planar shape according to a specified ratio,
14 is a diagram schematically showing a state in which the image processing apparatus according to the present invention synthesizes the planar shape of object images for each cadastral area,
15 is an image showing FIG. 14 as a collection image.

The features and effects of the present invention described above will become apparent through the following detailed description in connection with the accompanying drawings, whereby those of ordinary skill in the technical field to which the present invention pertains can easily implement the technical idea of the present invention. There will be. Since the present invention can apply various changes and have various forms, specific embodiments will be illustrated in the drawings and described in detail in the text. However, this is not intended to limit the present invention to a specific disclosed form, and it should be understood to include all changes, equivalents, and substitutes included in the spirit and scope of the present invention. The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram schematically showing a collection of collected images corrected by an image processing apparatus according to the present invention, and FIG. 2 is a block diagram showing an embodiment of a module configured in the image processing apparatus according to the present invention.

1 and 2, the image processing apparatus of the present invention stores a collected image (M1; see FIG. 8), cadastral map information where parcels are classified according to GPS coordinates, and GPS coordinate values and specification data of features. Information DB 11; A correction target detection module 14 for designating a correction target range proportional to the collection altitude of the collected image M1 retrieved from the information DB 11 in the collected image M1; In the collected image (M1), the RGB values of the pixels within the range to be corrected are checked, and the RGB values of the pixels of the chromaticity belonging to the designated representative chromaticity group are unified with the corresponding representative chromaticity, and the location values of the pixels unified with the representative chromaticity are checked. Thus, a cluster shape of pixels having the same RGB value is standardized through deep learning, the standardized cluster shape is set as an independent shape image, and a collection of three or more shape images in contact with each other is an object image (BM, BM'; 7), and the shape image with the largest area among the shape images of the object images (BM, BM') is designated as the flat shape (P1, P1'; see Fig. 7), and the other shape images are the side shape (P2). , An image analysis module 15 designated as P2', P3, P3'); Of the side shapes (P2, P2', P3, P3') of the object image (BM, BM'), the object outlines (UL1, UL2; see Fig. 7) that are not in contact with the flat shapes (P1, P1') are within the range to be corrected. An object image extraction module 16 for designating a corresponding object image (BM, BM') as a correction target if it is positioned above the reference ratio; Create a first edited image in which the flat shape (P1, P1') is aligned with the object outline (UL1, UL2) and the side shape (P2, P2', P3, P3') is deleted, and the object image (BM, BM') ) Of the ground object (B1 to B3) corresponding to the GPS coordinate value of) is searched in the information DB 11, and the distance value between the corresponding ground object (B1 to B3) and the shooting point and the height value of the ground object are checked, In proportion to the distance value and the height value, a second edited image MM' in which the first edited image MM is enlarged in proportion to the vector amount is generated, and cadastral map information corresponding to the correction target range of the collected image M1 is generated. By searching in the information DB 11, the cadastral map image (M2; see Fig. 8) is overlapped with the correction target range, and the collected image M1 is placed in accordance with the parcel boundary line BL (see Fig. 8) of the cadastral map image M2. An editing module 17a that deletes images for each Z1 and Z2) and combines the second edited image MM' into a corresponding deletion area; Ground objects B1 to B3 visually displayed according to the height (e1) and width of the ground objects (B1 to B3) of the second edit image (MM') and the photographing height (e2) from the specification data checked by the editing module (17a) ) A dark section search module 18 for setting the range of the surrounding dark section (t2, t2', t3, t3') to the corresponding second edited image (MM'); A resolution adjustment module 19 for setting a resolution for each elevation of the viewpoint so that the elevation adjustment effect of the viewpoint is visually expressed by expanding or reducing the image map image M4; According to the enlargement or reduction of the image map image M4, the range of the dark zone (t2, t2', t3, t3') set for each second edit image (MM') and the resolution of the image map image (M4) visually It includes; an altitude image designation module 17b that adjusts and outputs.

In more detail, the constituent elements of the image processing apparatus according to the present invention will be described in more detail. The information DB 11 stores a conventional collected image M1 that forms the background of the image map. Collected image (M1) is a composite and edited according to the GPS coordinates according to the known image editing process a number of photographed images collected by the aircraft (D) such as drones aerial photography. Since the collected image (MI) generation technology based on the photographed image is a known technology, a detailed description thereof will be omitted here. The information DB 11 stores cadastral map information on which parcels (Z1, Z2; see FIG. 8) are divided and displayed according to GPS coordinates. Since the cadastral map information includes the GPS coordinate value and the cadastral map image (M2), the parcels (Z1, Z2) of the corresponding section can be searched using the GPS coordinate value and displayed through the monitor. In addition, the information DB 11 stores the GPS coordinate values and specification data of the ground objects B1 to B3. Since the ground object image posted in the collected image (M1) is ground objects (B1 to B3) such as buildings and structures that exist on the ground, the GPS coordinate value, which is the actual position value, and the height, number of floors, width, name, etc. Compose specification data. Accordingly, the GPS coordinate value and the specification data are linked for each corresponding ground object image posted in the collected image M1, and the GPS coordinate value and the specification data are stored in the information DB 11.

The correction object detection module 14 designates a correction object range of the collected image M1 in proportion to the collection altitude of the collected image M1 retrieved from the information DB 11. As shown in FIG. 1, the camera is limited in the shooting range according to the angle of view, and the shooting range is limited according to the altitude of the shooting aircraft D. In other words, the larger the angle of view or the higher the photographing altitude, the greater the photographing range. However, since the deformation and distortion of the image increases toward the edge of the shooting range, the effective range of the collected image M1 is limited to the center, and among the ground object images located at the center, the ground object image that can be corrected is extremely limited. Therefore, the correction target detection module 14 sets the correction target range according to a specified ratio according to the collection altitude of the photographed image, which is the basis for the generation of the collected image M1. When the range to be corrected is set, the target to be processed in the subsequent process is limited to the range to be corrected, and the target to be processed is limited to an image of a ground object located within the range to be corrected.

The image analysis module 15 checks the RGB values of pixels within the range to be corrected in the collected image M1 and unifies the RGB values of the pixels of the chromaticity belonging to the designated representative chromaticity group with the corresponding representative chromaticity. By checking the position values of unified pixels, the cluster form of pixels having the same RGB value is formalized through deep learning, the standardized cluster form is set as an independent shape image, and a collection of three or more shape images in contact with each other is an object. It is designated as an image (BM, BM'; see Fig. 7), and the shape image with the largest area among the shape images of the object image (BM, BM') is designated as a flat shape (P1, P1'; see Fig. 7), Other shape images are designated as side shapes (P2, P2', P3, P3'). The image analysis module 15 analyzes the pixels located in the range to be corrected according to the position and RGB value, and an object image (P1, P1') and side shape (P2, P2', P3, P3') BM, BM') are classified and confirmed. A detailed description of this will be described in detail by describing the pro chart.

The object image extraction module 16 includes object outlines (UL1, UL2) that are not in contact with the planar shapes (P1, P1') of the side shapes (P2, P2', P3, P3') of the object images (BM, BM'); 7) is positioned above the reference ratio in the range to be corrected, a corresponding object image (BM, BM') is designated as a correction target. The entire object images BM and BM' may be located in the range of the target to be corrected detected by the target detection module 14, but only a part of the image may be located. Accordingly, the object image extraction module 16 reads whether or not to be corrected based on the degree of position of the object outlines UL1 and UL2 with respect to the range to be corrected. A detailed description of this will be described in detail by describing the pro chart.

The editing module 17a generates a first edited image in which flat shapes (P1, P1') are matched to object outlines (UL1, UL2) and side shapes (P2, P2', P3, P3') are deleted, The data of the ground objects (B1 to B3) corresponding to the GPS coordinate values of the object images (BM, BM') are retrieved from the information DB 11, and the distance between the corresponding ground objects (B1 to B3) and the shooting point and the ground Check the height value of the water, generate a second edited image (MM') in which the first edited image (MM) is enlarged at a ratio of the vector amount in proportion to the distance value and the height value, and corrected the collected image (M1). The cadastral map information corresponding to the range is retrieved from the information DB 11, and the cadastral map image (M2; see Fig. 8) is overlapped with the correction target range, and matches the parcel boundary (BL; see Fig. 8) of the cadastral map image M2). The collected image M1 is deleted for each parcel Z1 and Z2, and the second edited image MM' is combined in the corresponding deletion area. The editing module 17a is a technology that allows the collection image to be edited by removing the blind spot (a2) generated by the shooting angle from the ground object image without additional work such as collecting field information and re-taking information. To this end, the editing module 17a deletes the surrounding image of the ground object image, that is, the parked vehicle image, the tree image, the bench image, the park image, etc. from the collected image M1, and edits the obliquely photographed ground object image. A detailed description of this will be described in detail by describing the pro chart.

The dark section search module 18, the resolution adjustment module 19, and the elevation image designation module 17b will be described in more detail below.

3 and 4 are diagrams showing a state in which an image processing apparatus according to the present invention searches for a dark section around a second edited image based on the specification data of a ground object, and FIG. 5 is a view showing the search in FIGS. 3 and 4 It is a diagram showing a state in which a dark area is displayed around a second edited image in accordance with one dark area.

2 to 5, the dark section search module 18 includes the height e1 of the ground objects B1 to B3 of the second edited image MM' from the specification data checked by the editing module 17a. A range of dark sections (t2, t2', t3, t3') around the ground objects (B1 to B3) visually indicated according to the width and photographing altitude (e2) is set in the second edited image (MM').

The aircraft (D) is symbolically an observer or a camera, so it is a position to see the ground or take a picture. Therefore, the altitude e2 of the aircraft D is the altitude e2 or the shooting altitude e2 of the viewpoint. However, as the photographing altitude e2 increases, the difference between the height e1 of the ground objects B1 to B3 and the photographing altitude e2 increases geometrically, and the viewing angles q1 and q2 narrow as shown in FIGS. 3 and 4. It also narrows the range of dark sections (t2, t2', t3, t3') that are covered by the above-ground water (B1 to B3). Of course, since the data regarding the width (t1) and the height (e1) of the ground objects (B1 to B3) are constant, the dark section search module 18 based on this relationship is used for the dark section (t2, t2', t3, t3). ') Check the range by calculating it according to the shooting altitude (e2).

The resolution adjustment module 19 sets the resolution for each elevation of the viewpoint so that the elevation adjustment effect of the viewpoint is visually expressed by expanding or reducing the image map image M4. In general, as the distance from the target increases, the field of view becomes wider, but the shape of the target becomes unclear. In other words, the visual resolution is greatly reduced. Therefore, in order to increase the visual realism of the user through the adjustment of the viewpoint altitude, the resolution adjustment module 19 of the present embodiment decreases the resolution so that the field of view on the ground becomes wider as the viewpoint altitude increases, but the ground object image becomes unclear. .

The elevation image designation module 17b includes a range of dark sections (t2, t2', t3, t3') set for each second edited image (MM') according to the enlargement or reduction of the image map image (M4), and the image map The resolution of the image M4 is visually adjusted and output. The video map image (M4) to be described later is a cluster of second edited images (MM') generated by recombining the collected image (M1) by pixel by the editing module (17a), so the user enlarges the video map image (M4) When the elevation of the viewpoint is increased, the elevation image designation module 17b lowers the resolution to increase the realistic expression of the image map image M4, and adjusts the range of the dark sections (t3, t3') of the second edited image (MM'). Narrow. Conversely, when the user reduces the elevation of the viewpoint by reducing the image map image (M4), the elevation image designation module (17b) increases the resolution, and the range of dark sections (t2, t2') of the second edited image (MM') Widens

6 is a flowchart sequentially showing the operation process of the image processing apparatus according to the present invention, FIG. 7 is a diagram showing the criteria for detecting whether an object image is to be corrected by the image processing apparatus according to the present invention, and FIG. It is a diagram showing the state of the cadastral map of the collected image area searched by the image processing apparatus according to the present invention, FIG. 9 is a diagram schematically illustrating a case of synthesizing the cadastral map to the collected image before editing, and FIG. 10 The image processing apparatus according to the image processing apparatus is an image showing a state in which the parcel where the object image to be corrected is located has been deleted from the collected image, and FIGS. 11 and 12 are diagrams schematically showing a change in the planar shape of the object image according to the photographing angle, and FIG. 13 Is a diagram schematically showing a state in which the image processing apparatus according to the present invention corrects the planar shape according to a specified ratio, and FIG. 14 is a view in which the image processing apparatus according to the present invention synthesizes the planar shape of object images for each intellectual area. Is a schematic diagram, and FIG. 15 is an image showing FIG. 14 as a collection image.

1 to 15, the image processing apparatus of the present invention generates an image map image M4 by operating in the following process.

S10; Steps to specify the range to be corrected

When the operator searches the collected image M1 in the information DB 11, the correction target detection module 14 checks the collection altitude of the photographed image constituting the collected image M1, and at a specified ratio in proportion to the collection altitude. According to this, the range to be corrected is designated in the collected image (M1).

The range to be corrected is a circular section centered on the point where the aircraft D is located at the time of photographing the photographed image forming the corresponding collection image M1.

Consequently, the higher the altitude of the aircraft D, the wider the range to be corrected. However, the effective shooting image for the production of the collected image (M1) is limited to the captured image collected while the aircraft (D) is located at a limited altitude, so the correction target detection module 14 designated by the collected image (M1) The range does not show much difference for each collection image (M1).

S11; Steps to analyze collected images

The image analysis module 15 analyzes the position value and RGB value of the pixels on the ground object image posted within the range of the object to be corrected detected by the detection module 14 to be corrected to form a planar shape (P1, P1') ; See Fig. 7) and side shapes (P2, P2', P3, P3') are extracted.

The photographed image collected by the digital camera in the aircraft D is corrected and edited with the collected image M1, and then output to the monitor through the pixel with the RGB value set. Therefore, the image analysis module 15 checks the position value and corresponding RGB value for each pixel for outputting the collected image M1 to the monitor. Ground objects are painted with a unique color on their surface, so they have a different chromaticity than other adjacent ground objects. However, even if the surface is painted in the same color, the image of the ground object may show a difference in chromaticity due to the surface curvature of the ground object and the difference in contrast by location. That is, even with the same surface of the same ground object image, there may be a slight difference in the RGB value set for the corresponding pixel.

Accordingly, the image analysis module 15 unifies the RGB values of pixels set as chromaticities belonging to the designated representative chromaticity group with the corresponding representative chromaticity. For example, if red, pale red, and bright red form a group in an arbitrary representative chromaticity group, and the representative chromaticity is red, if the RGB value set in a random pixel is confirmed as bright red, the set RGB value of the pixel is determined. The RGB value is changed to red, which is the representative chromaticity of the corresponding chromaticity.

When the RGB values are unified by the representative chromaticity as described above, the image analysis module 15 checks the position values of the pixels and formalizes the cluster form of pixels having the same RGB value through deep learning. However, even if a subject has been stereotyped in a specific shape, the boundary line may become unclear or distorted in the image of the ground object collected by photographing. In other words, even if the subject is a square, the sides that form the boundary of the subject may form a curved shape rather than a straight line. Therefore, even if the ground object image is a somewhat curved square, the image analysis module 15 generates an independent shape image by forming the ground object image into a square shape through deep learning technology.

Subsequently, the image analysis module 15 analyzes the collected image M1, extracts an aggregate of three or more shape images (P1, P2, P3) in contact with each other among the standardized shape images, and converts the aggregate into an object image (BM, P3). BM'). As can be seen from the collected image M1, the building is photographed slightly inclined during aerial photography, and thus the plane and at least two or more sides are collected in a contact with each other. Therefore, an aggregate of three or more shape images (P1, P2, P3) in contact with each other is regarded as a ground object image and is designated as an object image (BM, BM').

S12; Step of extracting object image to be corrected

The image analysis module 15 designates the shape image with the largest area from three or more shape images (P1, P2, P3) designated as object images (BM, BM') as flat shapes (P1, P1'), and The shape image is designated as the side shape (P2, P2', P3, P3').

Subsequently, the object image extraction module 16, compared to the total width of the planar shape (P1, P1') and one side shape (P2, P2', P3, P3'), one side shape (P2, P2', P3, P3). The width of') is within the standard value, and the outline of the object (UL1, UL2) not in contact with the planar shape (P1, P1') of the side shapes (P2, P2', P3, P3') of the object image (BM, BM') If it is located above the reference ratio in the range to be corrected, the object image (BM, BM') is designated as the target to be corrected.

In more detail, when the ground object image is collected in an excessively inclined state, the overall width d1, P1' and one side shape P2, P2', P3, P3' Compared to d1'), the widths d2, d2' of one side shape (P2, P2', P3, P3') increase. In other words, it is unreasonable as a correction target because the target ground object is photographed too sideways during the shooting process. Therefore, object images (BM, BM') collected in this way are excluded from correction. For reference, the drawing (a) of FIG. 7 shows that the width (d2) of one side shape (P2) compared to the total width (d1) of the plan shape (P1) and one side shape (P2) is more than the reference value, so the object image extraction module (16) is excluded from correction.

Also, among the side shapes (P2, P2', P3, P3') of the object image (BM, BM'), the object outlines (UL1, UL2) that are not in contact with the planar shape (P1, P1') are This is where it is actually located. Consequently, even if the planar shapes P1 and P1' are out of the range to be corrected, the object outlines UL1 and UL2 must be located within the range to be corrected. Therefore, if the object outline (UL1, UL2) is located within the range to be corrected above the reference ratio, that is, more than 90%, the ground object of the object image (BM, BM') is considered to be located within the range to be corrected and designated as the target for correction. . Since the reference ratio is changed as necessary, it is not limited to the illustrated 90%.

S13; Cadastral Map Search Step

The editing module 17a checks the GPS coordinates of the range to be corrected, searches for corresponding cadastral map information from the information DB 11, and extracts a cadastral map image M2 from the cadastral map information.

S14; Deletion and Editing Stage of Collected Images

The editing module 17a overlaps the previously extracted cadastral map image M2 with the correction target range, and deletes the collected image M1 for each parcel (Z1, Z2) in accordance with the parcel boundary BL of the cadastral map image M2. . That is, the editing module 17a overlaps the boundary line BL of the cadastral map image M2 as shown in FIG. 8(b) with the collected image M1 to create a composite image M12 as shown in FIG. The edited video image M3 as shown in FIG. 10 is created by deleting the section (Z1, Z2).

S15; Plane shape correction step

The editing module 17a moves the flat shape (P1, P1') from the object image (BM, BM') to fit the object outline (UL1, UL2), and adjusts the side shape (P2, P2', P3, P3'). After deletion, the first edited image (MM) is created.

However, even if the planar shapes P1 and P1' constituting the first edited image MM are the same ground object, the shooting distances L1, L2, h1, h2, the shooting angle, and the distance value 37, 37', 38, 38') and photographing altitudes h1, h2, etc., the photographing areas 31 to 36 of the corresponding object images BM3 to BM8 vary.

Therefore, the editing module 17a uses the shooting distance (L1, L2), the shooting altitude (h1, h2), the shooting angle, and the distance (37, 37', 38, 38') between the first edited image (MM) and the aircraft (D). Regardless of variable factors such as ), etc., it is corrected as if the aircraft D accurately photographed the plane in the vertical direction from the ground object. To this end, the editing module 17a checks the GPS coordinate values of the corresponding object images (BM, BM') and searches the data of the corresponding ground objects B1 to B3 in the information DB 11, and the corresponding ground objects ( B1 to B3) and the distance values (37, 37', 38, 38') between the photographing points and the height value of the ground object are checked to confirm the amount of change in the photographing areas (31 to 36). That is, as shown in FIG. 11, the plane D is taken as a standard image of the object image (BM4) collected by photographing the ground object at the corresponding shooting altitude h1 and the shooting distance of'L1'. ), and the shooting area (31, 33 to 36) changed by the shooting angle and shooting distance (L2), the height of the corresponding ground object identified in the specification data, and the distance values between shooting points (37, 37', 38, 38'), etc. ) To the size of the reference area 32.

Eventually, the editing module 17a is the first in proportion to the distance values 37, 37', 38, 38', the height values, the shooting altitudes (h1, h2), the GPS coordinate values of the shooting point and the GPS coordinate values of the ground object. As shown in (c) of FIG. 13, the edited image MM is enlarged at a ratio of the vector amount to generate a second edited image MM'. For reference, the distance values 37, 37', 38, 38' are the difference between the GPS coordinate values of the aircraft D and the GPS coordinate values of the corresponding ground objects B1 to B3.

S16; Planar shape synthesis step

14 and 15, the editing module 17a synthesizes the second edited images MM1 and MM2 corresponding to the deletion areas of the parcels Z1 and Z2 configured in the edited video image M3, thereby synthesizing the image map image M4. ). Since the edited video image M3 is composed of a GPS coordinate system (not shown), the second edited images MM1 and MM2 linked to the corresponding coordinate values of the ground object are combined into the edited video image M3 according to the coordinate values. .

In the image map image M4 shown in FIG. 15, only the section Z21 in which the second edited images MM1 and MM2 are combined in the parcel Z2 is deleted, and the other section retains the existing image.

S17; The dark section search phase

Ground objects B1 to B3 visually displayed according to the height (e1) and width of the ground objects (B1 to B3) of the second edit image (MM') and the photographing height (e2) from the specification data checked by the editing module (17a) ) Set the range of the surrounding dark sections (t2, t2', t3, t3') to the second edited image (MM').

The aircraft (D) is symbolically an observer or a camera, so it is a position to see the ground or take a picture. Therefore, the altitude e2 of the aircraft D is the altitude e2 or the shooting altitude e2 of the viewpoint. However, as the photographing altitude e2 increases, the difference between the height e1 of the ground objects B1 to B3 and the photographing altitude e2 increases geometrically, and the viewing angles q1 and q2 narrow as shown in FIGS. 3 and 4. It also narrows the range of dark sections (t2, t2', t3, t3') that are covered by the above-ground water (B1 to B3). Of course, since the data regarding the width (t1) and the height (e1) of the ground objects (B1 to B3) are constant, the dark section search module 18 based on this relationship is used for the dark section (t2, t2', t3, t3). ') Check the range by calculating it according to the shooting altitude (e2). Of course, as the photographing altitude e2 decreases, the opposite effect to the above-described effect occurs.

S18; Resolution adjustment steps

The resolution for each elevation of the viewpoint is set so that the elevation adjustment effect of the viewpoint is visually expressed by expanding or reducing the image map image M4. Consequently, when the image map image M4 is enlarged, the image resolution decreases, and when the image map image M4 is enlarged, the image resolution increases.

In more detail, the resolution adjustment module 19 decreases the resolution so that the ground object image becomes unclear, although the field of view on the ground becomes wider as the viewpoint altitude increases.

As a result, the elevation image designation module 17b is set by the dark section search module 18 and the resolution adjustment module 19 for each second edited image MM' according to the enlargement or reduction of the image map image M4. The range of the dark section (t2, t2', t3, t3') and the resolution of the image map image (M4) are visually adjusted and output.

In the detailed description of the present invention described above, it has been described with reference to preferred embodiments of the present invention, but those skilled in the art or those of ordinary skill in the relevant technical field, the spirit of the present invention described in the claims to be described later. And it will be understood that various modifications and changes can be made to the present invention within a range not departing from the technical field.

a2; Blind spots B1 to B3; Ground water BL; boundary
BM, BM', BM1 to BM8; Object image D; aircraft
d1, d2; Width M1; Collected image M12; Composite image
M2; Cadastral map image M3; Edited video image M4; Video map image
MM; The first edited image MM'; Second edited images P1, P1'; Plane shape
P2, P2', P3, P3'; Side name shape UL1, UL2; Object outline

Claims (1)

An information DB for storing collected images, cadastral map information in which parcels are classified according to GPS coordinates, and GPS coordinate values and specification data of ground objects;
A correction target detection module for designating a correction target range of the collected image in proportion to the collection altitude of the collected image retrieved from the information DB;
A group is formed by designating one representative chromaticity to a plurality of chromaticities, and by checking the RGB values of pixels within the range to be corrected in the collected image, unify the RGB values of the pixels with the representative chromaticity of the group to which the chromaticity of the corresponding RGB value belongs. , By checking the position values of pixels unified by the representative chromaticity, the cluster shape of pixels having the same RGB value is formalized through deep learning, the standardized cluster shape is set as an independent shape image, and three or more shapes in contact with each other An image analysis module that designates a collection of images as an object image, designates a shape image having the largest area among the shape images of the object image as a flat shape, and designates another shape image as a side shape;
Among the side shapes of the object image, the ratio between the total length of the object outline that is not in contact with the flat shape and the length of the object outline located within the range to be corrected is greater than or equal to the reference ratio, and one side shape compared to the total width of the flat shape and the side shape An object image extraction module that designates a corresponding object image as a correction target if the width of is within the reference value;
A first edited image is created in which the plane shape is aligned with the object outline and the side shape is deleted, and the data of the ground object corresponding to the GPS coordinate value of the object image is retrieved from the information DB, and the distance between the ground object and the shooting point The value, the shooting altitude, the height of the ground object, the GPS coordinate value of the shooting point, and the GPS coordinate value of the ground object are checked, and the first edited image is compared with the GPS coordinate value of the shooting point in proportion to the distance value and the shooting altitude and height value. A second edited image is created by expanding at the ratio of the amount of vector according to the direction identified through the GPS coordinate value of the ground object, and the cadastral map information corresponding to the correction target range of the collected image is searched in the information DB to convert the cadastral map image to the corrected range. An editing module that overlaps and creates an edited video image by deleting the collected image for each lot in accordance with the parcel boundary of the cadastral map image, and synthesizing the second edited image to the corresponding deletion area of the edited video image to create a video map image ;
A dark section search module for setting a range of a dark section around the ground object visually displayed according to the height and width of the ground object of the second edited image and the photographing altitude from the specification data checked by the editing module in the second edited image;
A resolution adjustment module configured to set the resolution for each elevation of the viewpoint so that the elevation adjustment effect of the viewpoint is visually expressed by expanding or reducing the image map image; And
An elevation image designation module for visually adjusting and outputting a range of a dark area set for each second edited image and a resolution of the image map image as the image map image is enlarged or reduced;
An image processing apparatus for correction for unification of collected images by elevation, comprising: a.

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