KR102467870B1 - Spatial image drawing system for editing drawing image by synthesizing part-by-part images - Google Patents

Abstract

The present invention relates to a spatial video drawing processing system of a precise synthesis function of spatial video drawing images for each part. A drawing processing device based on an operating system (OS) having a video drawing module may include: a collection image storage device; an altitude information storage device; a drawing image storage device; a drawing target designation module; a search module; an image synthesis module, a restoration target selection module, an image correction module, and a video drawing module.

Description

Spatial image drawing processing system with precise synthesis function of spatial image drawing image for each part

The present invention relates to a spatial image drawing processing system having a function of precisely synthesizing spatial image drawing images for each part.

As is well known, space image painting is performed manually by a painting worker. Therefore, the operator visually checks the drawing target image and various numerical information, and performs graphic work using a graphics program or device dedicated to drawing.

However, the drawing target image, which is important information for image drawing, includes the feature shadow (SE) for each feature image (BE1, BE2) as shown in FIG. While covering (BE2), there was a problem of making the shape of the corresponding feature image (BE2), that is, the boundary line of the feature image (BE2) for mapping unclear.

As a result, in the prior art, there was the inconvenience and inconvenience of having to confirm the actual location and shape of a feature in the field for the spatial image drawing work and applying the confirmed information to the drawing work.

Prior art literature 1. Patent Registration No. 10-2210445 (2021.02.02 announcement)

Therefore, the present invention is to solve the above problems, and to reduce the feature image with ambiguous boundaries by removing the feature shadow, which is the cause of the shadow in the drawing target image, for the spatial image drawing work, the space for each part to enable accurate drawing work. It is a task to solve the provision of a spatial image drawing processing system with a precise synthesis function of video drawing images.

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

a collection image storage device for storing and managing collection images for each ground area having a feature image with a designated GPS value;

a drawing object image storage device that classifies, stores, and manages drawing object images selected from the collected images by version;

an altitude information storage device that stores and manages altitude information about the sun's altitude by time zone;

a drawing image storage device for storing and managing drawing images based on corrected main video images by version;

When the search module retrieves a plurality of collected images including a feature image designated as a reference target for feature shadow removal from the collected image storage device, it is collected at the time of the highest altitude of the sun according to the altitude information retrieved from the altitude information storage device. One collected image is extracted by first filtering, and collected images collected on the date of the highest altitude of the sun are extracted by second filtering from the collected images extracted by first filtering to obtain a collected image with the narrowest feature shadow of the reference target feature image. A drawing target designation module that designates as a main video image; The feature image of the GPS value input by the user is designated as the reference target, the reference target is detected from the main video image designated by the drawing target designation module, and a plurality of collected images including the reference target are stored in the collected image storage device. Search, and collect images composed of feature shadows of the reference target included in the main video image and non-overlapping feature shadows of the reference target included in the main video image are stored in the collected image storage device based on the position of the feature shadow of the reference target included in the main video image. A search module for searching and specifying a restored image; an image synthesizing module that unifies the RGB combination ratio of each pixel of the reconstructed image based on the RGB combination ratio of each pixel of the main video image; a restoration target selection module that identifies an intersection area image between the main video image and the restoration image and designates it as a restoration target; In the cross section image selected by the restoration target selection module, a restoration section image corresponding to the position of the feature shadow of the reference object is detected from the restored image, and the corresponding point within the feature shadow is the same as the RGB combination ratio for each point in the restoration section image. an image correction module that adjusts the RGB combination ratio for each; The boundary line of the reference object, in which the RGB combination ratio of each point of the feature shadow is adjusted to be the same as the RGB combination ratio of each point of the restoration section image, is automatically detected based on the chromaticity difference for the set color for each pixel, and the drawing image is imaged. OS (Operating System)-based drawing processing device equipped with;

It is a spatial image drawing processing system with a function of precise synthesis of spatial image drawing images for each part including.

The present invention described above has an effect of reducing feature images with ambiguous boundaries and performing accurate drawing work by removing feature shadows, which are the cause of shadows, in the drawing target image for the spatial image drawing work.

1 is an image showing drawing target images collected for spatial image drawing,
2 is a block diagram showing the configuration of a painting processing system according to the present invention;
3 is an image showing a drawing image processed by the drawing processing system according to the present invention based on a spatial image image;
4 is a diagram schematically showing the shape of a feature shadow for each time zone for designating a drawing image target drawing target image in the drawing processing system according to the present invention;
5 is a diagram showing a drawing target image for a main image image in a drawing processing system according to the present invention;
6 is a flowchart sequentially showing the operation process of the drawing processing system according to the present invention;
7 is a diagram schematically showing a main video image selected in the drawing processing system according to the present invention;
8 is a diagram showing the main video image in which GPS coordinates are set;
9 is a diagram schematically showing collected images searched for by the drawing processing system according to the present invention for comparison with the main video image;
10 is a diagram showing a state in which a drawing processing system according to the present invention overlaps a main video image and a collected image;
11 is a view showing an example image in which the feature shadow of the reference target does not overlap each other in the main video image and the collection image in which the drawing processing system according to the present invention overlaps;
12 is a diagram schematically showing how the feature shadows of the reference target do not overlap each other in the overlapping main video image and collection image of the drawing processing system according to the present invention;
13 is a diagram schematically showing how the drawing processing system according to the present invention replaces the shadow of a feature of a reference target with a restoration section image.

The terms used in the embodiments have been selected from general terms that are currently widely used as much as possible while considering the functions in the present invention, but they may vary according to the intention of a person skilled in the art or precedent, the emergence of new technologies, and the like. In addition, in a specific case, there is also a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the invention. Therefore, the term used in the present invention should be defined based on the meaning of the term and the overall content of the present invention, not simply the name of the term.

In the entire specification, when a part is said to "include" a certain component, it means that it may further include other components, not excluding other components unless otherwise stated. In addition, as described in the specification, "... A term such as “module” refers to a unit that processes at least one function or operation, and may be implemented as hardware or software or a combination of hardware and software.

Hereinafter, with reference to the accompanying drawings, embodiments of the present invention will be described in detail so that those skilled in the art can easily carry out the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein.

Hereinafter, the present invention will be described in detail based on the accompanying drawings.

2 is a block diagram showing the configuration of a drawing processing system according to the present invention, FIG. 3 is an image showing a drawing image processed by the drawing processing system according to the present invention based on a spatial image, and FIG. 4 is an image showing the present invention. A diagram schematically showing the shape of a feature shadow for each time period for designating a drawing target image as a drawing image target by the drawing processing system according to the present invention, and FIG. it is a drawing

2 to 5, the drawing processing system according to the present invention includes a collection image storage device 10 for storing and managing a collection image AI for each ground area having a feature image B with a designated GPS value; A drawing object image storage device 20 that classifies and stores and manages drawing object images selected from the collected images (AI) by version; Altitude information storage device 30 for storing and managing altitude information on the sun's altitude by time zone; A drawing image storage device 50 for storing and managing drawing images based on corrected main video images by version; It consists of a drawing processing device 40 that performs correction work for precise synthesis of drawing images for each part.

The painting processing device 40 according to the present invention is a device that performs image correction during space image drawing work, and can be installed in an OS (Operating System)-based computer in the form of an application. The drawing processing device 40 consists of a drawing target designation module 41, a search module 42, a restoration target selection module 43, an image synthesizing module 44, an image correction module 45, and an image drawing module 46. It consists of

In the drawing target designation module 41, when the search module 42 searches the collected image storage device 10 for a plurality of collected images AI including the feature image B designated as a reference target for feature shadow removal, According to the altitude information retrieved from the altitude information storage device 30, the collected images (AI) collected at the time of the highest altitude of the sun are firstly filtered and extracted, and the highest altitude of the sun is extracted from the collected images (AI) extracted by the first filtering. The collected images (AI) collected on the date are filtered and extracted secondarily, and the collected images (AI) with the narrowest feature shadows (SE, SE3) of the reference target feature image (B) are selected as the main image image (UI; see FIG. 7). ) is an algorithm programmed to specify The drawing processing device 40 according to the present invention designates and corrects the main video image (UI), which is a drawing target, based on the area of the feature shadows SE and SE3, and the drawing target designation module 41 collects Check the altitude of the sun at the time the image was collected and select one of the plurality of collected images. As described above, the altitude information storage device 30 stores and manages altitude information about the altitude of the sun for each time period, and the drawing target designation module 41 designates a feature image from which the feature shadow is to be removed as a reference target, Based on the collection time point for each of the plurality of collected images (AI) including the reference target, the main video image (UI) to be drawn is extracted and designated by filtering in multiple stages according to the altitude information.

The search module 42 designates the feature image B of the GPS value input by the user as the reference target, detects the reference target from the main video image UI designated by the drawing target designation module 41, A plurality of collected images (AI) including the reference target are searched in the collected image storage device 10, and the feature shadow (SE3) of the reference target included in the main video image (UI) and the feature shadow of the reference target that do not overlap each other A program to designate a collected image composed of as a restored image (R; see FIG. 13) by searching the collected image from the collected image storage device 10 based on the position of the feature shadow (SE3) of the reference object included in the main video image (UI). It is an algorithm made Therefore, the search module 42 transfers images corresponding to keywords such as GPS values input by the user to the collection image storage device 10 and the drawing target to designate the reference target of the feature image B for correcting the feature shadow SE3. Each search is performed in the image storage device 20. For reference, the search module 42 filters the drawing target image and the collected image AI based on the altitude information so that the corresponding feature shadow SE does not overlap with each other by referring to the position of the reference target in the designated main video image UI. Search for collected images (AI) that do not exist and designate them as restored images (R).

The image composition module 43 is an algorithm programmed to unify the RGB combination ratio of each pixel of the restored image based on the RGB combination ratio of each pixel of the main video image UI. Collection that is advantageous for correcting the drawing target image through a precise overlap (composite) method between the main video image (UI; part) and the collected image (AI3 to AI6; see Fig. 9; part), which is one part of the collected image including the reference target. Detect image (AI).

The reconstruction target selection module 44 is an algorithm programmed to identify an intersection image (CI; see FIG. 10) between the main video image UI and the restored image and designate it as a restoration target. Since the correction range for the feature shadow (S3; see FIG. 12) is limited through the designation of the cross section image (CI1) to be restored, the collected images (AI3 to AI6) corresponding to the restoration section image (RZ; see FIG. 13) to be replaced search is advantageous.

The image correction module 45 converts the restoration section image RZ corresponding to the feature shadow S3 (see FIG. 12) of the reference object into the cross section image CI1 selected by the restoration target selection module 44 from the restored image. It is an algorithm programmed to detect and adjust the RGB combination ratio of each corresponding point in the feature shadow to be the same as the RGB combination ratio of each point in the restoration section image (RZ). Eventually, the main video image (UI) in the drawing target image to be used as the background of the drawing is stored and updated in the drawing object image storage device 20 as a clear drawing object image with the feature shadow of the target section removed.

The image drawing module 46 converts the boundary line of the reference object, in which the RGB combination ratio of each point of the feature shadow S3 is adjusted to be the same as the RGB combination ratio of each point of the restoration section image RZ, to the chromaticity of the set color for each pixel. It is an algorithm programmed to convert a drawing image into a drawing image by automatically detecting the difference based on the difference, and to store the created drawing image in a drawing image storage device. The feature shadow (S3) of the video image that causes visual uncertainty obscures the boundary line of the feature image (B), but the RGB combination ratio of the feature shadow (S3) of the reference target is the RGB combination ratio of the restoration section image (RZ) Since the boundary line of the feature image (B) becomes clear by adjusting in the same way as, the difference in chromaticity of the color set for each pixel becomes clear. Therefore, if the difference in chromaticity per pixel, more specifically, the rate of change in chromaticity per pixel exceeds the reference value, the image drawing module 46 automatically recognizes the corresponding section as a boundary line, automatically displays it, and proceeds with the image drawing process.

For reference, the rate of change in chromaticity per pixel refers to the degree of change in chromaticity set in neighboring pixels. That is, when a red wavelength is set to one of the pixels adjacent to each other and a black wavelength is set to the other, it is determined that the chromaticities respectively set for the two pixels rapidly change with a difference of one pixel, and the rate of change is considered high. The image drawing module 46 determines that the corresponding pixel position is a point of the boundary line when the set wavelength between adjacent pixels exceeds a reference value.

Based on the drawing processing system of the configuration according to the present invention described above, the drawing processing process for the main video image (UI) will be sequentially described.

6 is a flow chart sequentially showing the operation process of the drawing processing system according to the present invention, FIG. 7 is a diagram schematically showing the main video image selected in the drawing processing system according to the present invention, and FIG. 8 is a GPS coordinate It is a diagram showing the main video image in which is set.

2 to 8, the drawing target image processing method based on the drawing processing system according to the present invention includes a reference target selection step (S10), a collection image search step (S20), a main image image designation step (S30), and an image It consists of a color adjustment step (S40), a restored image designation step (S50), a restoration target selection step (S60), a feature shadow editing step (S70), and an image drawing step (S80). The operation of each step will be explained based on the drawing processing system.

S10; Standard target selection stage

The user selects a feature image (B) from which feature shadows (SE1 to SE5; hereinafter referred to as 'S') are to be removed from the drawing object image stored in the drawing object image storage device 20 as shown in FIG. ), the GPS value of the feature image (B), which is a search keyword, is checked.

S20; Collection image search step

When the user inputs the GPS value of the feature image (B) into the search module 42, the corresponding feature image (B) is designated as a reference target. Thereafter, the search module 42 searches the drawing object image storage device 20 and the collected image storage device 10 for the collected image AI including the feature image B of the GPS value. In general, the number of collected images AI searched by the search module 42 is plural.

S30; Main video image designation step

The drawing object designation module 41 detects a reference object from the plurality of collected images AI searched by the search module 42 . The drawing target designation module 41 compares the collection point of the plurality of collected images AI searched in this way with the altitude information retrieved from the altitude information storage device 30 to filter the collected images AI.

More specifically, the higher the altitude of the sun, the narrower the range of the feature shadow (S). That is, the range to be corrected is reduced. Therefore, the drawing target designation module 41 first filters and extracts the collected images (AI) collected at the time of the highest peak of the sun among the plurality of collected images (AI), and extracts the collected images (AI) extracted by the first filtering. ), the collected images (AI) collected on the date of the highest altitude of the sun are extracted by secondary filtering, and the collected images (AI) with the narrowest feature shadow (S) of the reference target feature image (B) are selected as the main image image (UI). ) is specified. In this embodiment, as shown in (a) of FIG. 4, the feature image (B) has various feature shadows (SE1 to SE5) according to the altitude of the sun. A collection image (AI) having a feature shadow (SE3) is selected and designated as a main video image (UI).

For reference, the drawing object image and the collected image AI stored in the drawing object image storage device 20 and the collected image storage device 10 may not be collected at the time of the year when the sun is at its highest altitude. Therefore, the drawing target designation module 41 selects the image collected at the time when the sun is relatively at its highest in the collected images (AI) retrieved from the drawing target image storage device 20 and the collected image storage device 10, and selects the main image image. (UI).

9 is a diagram schematically showing collected images retrieved by the painting processing system according to the present invention for comparison with the main video image, and FIG. 10 is a drawing processing system according to the present invention overlapping the main video image and the collected image. It is a drawing that shows

A processing method based on a drawing processing system according to the present invention will be described with reference to FIGS. 2 to 10 .

S40; image color adjustment steps

The image synthesizing module 43 unifies the RGB combination ratio for each pixel of the main video image UI and the RGB combination ratio for each pixel of the plurality of collected images AI searched by the search module 42.

The collected images (AI3 to AI6) of the same ground area, as well as the main video image (UI), have different applied colors because there are differences in the collection location, collection time, and shooting angle. Accordingly, the image synthesis module 43 unifies the image color by making the RGB combination ratio of the plurality of collected images AI3 to AI6 searched by the search module 42 the same as that of the main video image UI.

As a result, the main video image (UI) and the collected images (AI3 to AI6) including the reference object can accurately detect and edit the feature shadow (S) without error due to color due to the color unification of the component pixels.

S50; Restoration image designation step

When the RGB combination ratio of the main video image (UI) and the collection image (AI) is unified, the search module 42 determines the location of the reference target that does not overlap with the feature shadow (S3) of the reference target included in the main video image (UI). The collected image (AI3) composed of the feature shadow (S) is retrieved from the collected image storage device 10 based on the position of the feature shadow (S3) of the reference object included in the main video image (UI) and restored image (R) designate as

In this embodiment, the image synthesis module 43 overlaps the main video image (UI) and the collection image (AI) of the unified RGB combination ratio based on the GPS coordinates to create the feature shadow (S3) of the main video image (UI). A collected image (AI3) consisting of a feature shadow (S3) of the reference target that does not overlap with is selected.

S60; Restoration target selection stage

The restoration target selection module 44 is an intersection area with the smallest shadow area of the feature shadows (S, S3) belonging to the range of the main image image (UI) and the intersection area image (CI) for each collected image (AI3 to AI6). An image (CI1; see FIG. 13) is designated as a restoration target. That is, among the cross-section images (CI) belonging to the main video image (UI) and the collected images (AI3 to AI6), the cross-section image (S, S3) constituting the smallest feature shadow (S3) CI1) is designated as a restoration target.

To explain the cross section image (CI) in more detail, since a cross section is formed between the main video image (UI) overlapped by the image synthesis module 43 and the collection images (AI3 to AI6), the cross section is crossed. Check the zone image (CI). Here, the intersection image CI is an image of a section where the main video image UI and the collected images AI3 to AI6 overlap each other, as shown in FIG. 10 . In the intersection area image (CI), not only the feature image (B) of the reference target, but also the feature image of the feature around the reference target, and the feature shadows (S, S3) for each feature are composed.

The restoration target selection module 44 selects the feature target feature shadow S3 with the smallest shadow area and restores only the section of the feature shadow S3, so the image restoration burden can be drastically reduced as well as restoration It is possible to maintain the realism of the drawing target image even in editing for the purpose of drawing.

Since the selection process of the intersection area image (CI1) with the smallest shadow area of the feature shadow (S, S3) of the feature object is performed in a unified state of RGB combination ratio, the selection error is reduced to increase accuracy and the restoration target is selected in the selection process. The computational load of module 44 can be reduced.

11 is a view showing an example image in which the shadow of a feature of a reference object does not overlap each other in a main video image and a collection image in which a drawing processing system according to the present invention overlaps, and FIG. It is a diagram schematically showing how the feature shadows of the reference target do not overlap each other in the video image and the collected image, and FIG. It is a drawing shown as

A processing method based on a drawing processing system according to the present invention will be described with reference to FIGS. 2 to 3, 6, and 11 to 13.

S70; Steps to Edit Feature Shadows

In the image correction module 45, the search module 42 searches for the restoration section image RZ corresponding to the feature shadows S3 and S4 in the cross section image CI1 selected by the restoration target selection module 44. It is detected in the restored image (R).

As described above, the restoration target selection module 44 selects the intersection area image CI1 based on the reference target feature shadow S3 in the intersection area image CI1 to confirm the section to be restored. In correction, all feature shadows (S3, S4) within the cross section image (CI1) are collectively processed. Meanwhile, the image correction module 45 searches the restoration section image RZ through the search module 42 . Here, the restored image (R) is a collection image (AI) composed of the feature shadow (S3) with the smallest shadow area among the feature shadows (S, S3) of the reference target and the feature shadow (S) of the reference target that does not overlap with each other as shown in FIG. ) means The restored section image RZ means an image of a section belonging to the position of the feature shadow S3 having the smallest shadow area among the reference target feature shadows S and S3 in the restored image R. Therefore, the image correction module 45 analyzes the restored image R searched by the search module 42 and detects the restored section image RZ corresponding to the feature shadows S3 and S4 in the cross section image CI1. do.

Subsequently, the image correction module 45 checks the RGB combination ratio for each point in the restoration section image RZ detected from the restoration image R, and converts the RGB combination ratio for each point in the feature shadow S3 of the reference target into the restoration section Adjust to be the same as the RGB combination ratio for each point in the image. That is, the RGB of the feature shadow S3 of the reference target matches the RGB of the restoration section image RZ.

For reference, as shown in FIG. 13, in the case of some feature shadows (S4) among the feature shadows (S3, S4) in the cross section image (CI1), the image correction module 45 restores the section image corresponding to the corresponding feature shadow (S4). may not be detected in the restored image R. In this case, the image correction module 45 re-searches the restored image (not shown) corresponding to the corresponding feature shadow S4 from the collected image AI through the search module 42, and when the restored image is retrieved, it is retrieved. By analyzing, a restoration section image corresponding to the corresponding feature shadow S4 is detected and the above-described replacement process is executed. Therefore, each of the feature shadows S3 and S4 configured in one cross section image CI1 selected by the restoration target selection module 44 can be replaced with a restoration section image RZ configured in a plurality of collected images AI. have.

S80; image drawing stage

The image drawing module 46 calculates the chromaticity difference for the set color for each pixel of the boundary line (F) of the feature image (B) within the cross section image (CI1) in which the feature shadow (S3) is replaced with the restoration section image (RZ). It is automatically detected as a standard and converts the drawing image draft into a video drawing. The first image drawing by the above-described image drawing module 46 is that the image drawing module 46 automatically detects and draws the boundary line F of the feature image B, and then the drawing operator draws the automatically drawn drawing. Based on the image, the final drawing image shown in FIG. 4 is completed by performing secondary drawing work tailored to the location and shape of the bottom surface (G) of the feature on the ground. The drawing image completed in this way is stored in the drawing image storage device 50 by the image drawing module 46 .

Although the detailed description of the present invention described above has been described with reference to preferred embodiments of the present invention, those skilled in the art or those having ordinary knowledge in the art will find the spirit of the present invention described in the claims to be described later. And it will be understood that the present invention can be variously modified and changed within a range that does not deviate from the technical scope.

AI, AI3 to AI6; collected images B, B1, B2; feature image
B', B1', B2'; feature display BE1, BE2; feature image
CI; CI1; cross section image R; restoration image
RZ; Restoration section images S, S3 to S4; feature shadow
SE, SE1, SE2, SE3, SE4, SE5; feature shadow
UI; Main video image 40; Paint processing device

Claims (1)

A collection image storage device that stores and manages a collection image for each area of the ground having a feature image with a specified GPS value and a feature shadow forming various formation directions and ranges according to the position and altitude of the sun when collecting the feature image for the same feature ;
an altitude information storage device that stores and manages altitude information about the sun's altitude by time zone;
Drawing images extracted by the image drawing module based on the cross-section image background in which the RGB combination ratio for each point of the feature shadow of the reference target is adjusted to be the same as the RGB combination ratio for each point of the restoration section image by the image correction module, A drawing image storage device that stores and manages by classifying by version;
When the search module retrieves a plurality of collected images including a feature image designated as a reference target for feature shadow removal from the collected image storage device, it is collected at the time of the highest altitude of the sun according to the altitude information retrieved from the altitude information storage device. One collected image is extracted by first filtering, and collected images collected on the date of the highest altitude of the sun are extracted by second filtering from the collected images extracted by first filtering to obtain a collected image with the narrowest feature shadow of the reference target feature image. A drawing target designation module that designates as a main video image;
The feature image of the GPS value input by the user is designated as the reference target, the reference target is detected from the main video image designated by the drawing target designation module, and a plurality of collected images including the reference target are stored in the collected image storage device. When the feature image is collected, due to the difference in the position and altitude of the sun, the formation direction and range of the feature shadow of the reference object included in the main video image are different, so that the collection image composed of the feature shadow of the reference object that does not overlap each other is selected as the main image. a search module for designating a restored image by searching in a collected image storage device based on the position of a feature shadow of a reference target included in a video image; an image synthesizing module that unifies the RGB combination ratio of each pixel of the reconstructed image based on the RGB combination ratio of each pixel of the main video image; a restoration target selection module that identifies an intersection area image between the main video image and the restoration image and designates it as a restoration target; In the cross-section image selected by the restoration target selection module, a restoration section image corresponding to the position of the feature shadow of the reference object is detected from the restored image, and the corresponding point in the feature shadow is the same as the RGB combination ratio for each point in the restoration section image. an image correction module that adjusts the RGB combination ratio for each; The boundary line of the reference object, in which the RGB combination ratio of each point of the feature shadow is adjusted to be the same as the RGB combination ratio of each point of the restoration section image, is automatically detected based on the chromaticity difference for the set color for each pixel, and the drawing image is imaged. OS (Operating System) based drawing processing device equipped with;
A spatial image drawing processing system with a function of precise synthesis of spatial image drawing images for each part, characterized in that it comprises a.

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