KR101578822B1 - Recovering apparatus using the coordinated aerial oblique image for 3d-texture on the 2d-image - Google Patents

Abstract

The present invention relates to a three-dimensional texture recovering apparatus of a two-dimensional video image through a GIS-based aviation image registration which displays a three-dimensional video prepared before an entity such as an object on the ground, or the like is changed through a two-dimensional novel video image. The apparatus of the present invention comprises: an aviation photographing unit (200) including a collection module (210), an image check information DB (230), an image check module (220), an image control module (260), and an image transmission module (250); and a recovery unit (100) including a collection image treatment module (110), a collection image DB (130), an entity analysis module (120), an entity change check module (140), a video section search module (150), an image information editorial module (170), a link information editorial module (170′), a texture recovery module (170″), and a video image updating module (180).

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a three-dimensional texture restoration apparatus for a two-

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a three-dimensional texture restoration apparatus for a two-dimensional image image through GIS-based aerial image matching, which expresses a three-dimensional image produced before an individual change of ground water or the like through a two-

Since the image of the digital map produced on the basis of data such as the shot image is burdened with a cost / work burden for collection, the collection and update of the image image does not exceed once or twice a year. Furthermore, in the case of a three-dimensional image, since the three-dimensional object must be directly shown or expressed using texture technology, the update of the digital map based on the three-dimensional image is inevitably longer. Therefore, even if there is a change in the terrain of an arbitrary region, the section corresponding to the region in the existing image maintains the shape and the information before the change, so that the users can not utilize the digital map based on the image .

In order to solve such a problem, a technique has been proposed in which a worker visits an area in which a worker has changed, collects information, and edits a corresponding section of the image based on the collected information.

However, the prior art may require expensive collection such as frequent aerial photographing, and a worker must directly visit the area where the change has occurred and perform the collection work such as the confirmation process. Thus, in reality, There was a limit to the impossibility.

Prior Art Document 1. Patent Registration No. 10-1128411 (published on Mar. 27, 2012)

Accordingly, the present invention has been made to solve the above-mentioned problems, and it is an object of the present invention to provide a GIS Dimensional texture image reconstruction apparatus using a three-dimensional texture image reconstruction method.

According to an aspect of the present invention,

When the panoramic image is classified into a predetermined horizontal interval and the pixels of the specified range or more are designated by the constituent pixels on the left or right vertical axis YA of the newly collected image, A collection module 210 for setting an identification mark of an image; An image check information DB (230) storing check information composed of a check mark of a horizontal axis (XA) specified in a previous acquisition image; If the pixels of the specified number of pixels or more in the pixels of the specified horizontal axis (XA) are successively displayed in the designated similar area in the new collection image, the pixels are set as a new check mark. In the image check information DB 230, And checks whether or not the output color, the color position, and the color length of the pixels of the new check mark and the pixels of the check information coincide with each other, by comparing the new check mark with the check information And if the new check mark and the check information match the specified ratio or more, the new collected image is regarded as having no entity change, and if the new check image matches the specified rate, the new collected image is estimated as having an entity change An image check module 220 for checking the image; Before comparing the new check and the check information for comparison of the image check module 220, the difference between the identification mark position of the previous acquisition image and the identification mark position of the new acquisition image is checked, An image adjustment module 260 for adjusting the position; An image generation module (250) for generating a new collection image in which an individual variation is estimated, as image data;

An acquisition image processing module 110 for confirming the basic information of the image data and confirming the ID of the aerial photographing unit 200 and the identification information of the newly acquired image; An acquisition image DB 130 for storing an existing acquisition image; And a step of classifying the group of color pixels in a similar range specified in the new collection image as one entity and classifying the new collection image into an existing group stored in the collection image DB 130 An object analysis module 120 for storing and linking the collected images; A new collection image and an existing collection image linked to each other are retrieved from the collection image DB 130, a plurality of check points are set within the range of the objects classified in the existing collection image, Determining whether there is a change in the entity if it is determined that the number of checkpoint colors does not coincide with the number of checkpoints, The pixel cluster in which the colors of the pixels in the newly collected image are continuously output is identified as a result of the comparison of the colors, and the cluster is designated as the change range (NB) An entity change confirmation module 140 for transferring the newly collected image to the input / output module 190 and outputting the same; An input / output module (190) for editing the change range (NB) displayed in the existing collection image to generate image synthesis data, and inputting a determination signal for the change range (NB); A video image DB 160 for storing a two-dimensional video image and a three-dimensional video image; An image segment search module 150 for confirming the determination signal and searching for a corresponding two-dimensional image and a three-dimensional image image in the image image DB 160; An image information editing module 170 that identifies an editing subject area corresponding to the change range NB in the two-dimensional image and synthesizes the corresponding image in the change range NB in accordance with the image synthesis data, ; A link information editing module 170 'for deleting the text linked to the editing subject area and linking the new text input from the input / output module 190 to the editing subject area; The polygon and the texture of the editing subject area object image edited by the image information editing module 170 in the three-dimensional image image are deleted, and the corresponding color of the change range NB is inserted at the bottom point of the object image, And a video image update module 180 for updating the edited two-dimensional video image and the three-dimensional video image in the video image DB 160,

Dimensional image based on GIS based aerial image matching.

According to the present invention, an area having an object change in an aerial image is searched and registered to complete a changed two-dimensional image image, and a three-dimensional texture for editing a three-dimensional image image is completed based on the search result, Therefore, it is possible to easily process the three-dimensional image without editing the three-dimensional image according to the individual change.

1 is a block diagram showing a restoration apparatus according to the present invention,
FIG. 2 is a view schematically showing a state in which editing processing of a restoration apparatus according to the present invention is performed,
FIG. 3 is a view schematically showing a three-dimensional image image displayed through the texture restoration module according to the present invention,
FIG. 4 is a block diagram showing an aerial photographing unit implementing the restoration method according to the present invention,
5 is an exploded perspective view and an operation view of the aerial photographing unit,
FIG. 6 is a flowchart showing a procedure of a restoration method according to the present invention,
FIG. 7 is an image schematically showing a state in which the aerial photographing unit performs primary analysis of the collected image,
8 is a view schematically showing the identification information setting of the collected image,
FIG. 9 is a view schematically showing a state where the collected image of FIG. 7 is adjusted to a pixel position of a reference value,
10 is an image showing an object classification process in which a collection image forming the basis of a video image is processed,
11 is an image showing a variation of an existing collection image and a new collection image,
FIG. 12 is a view schematically illustrating a method of modifying a video image according to a restoration method according to an embodiment of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS The above and other features and advantages of the present invention will become more apparent from the following detailed description of the present invention when taken in conjunction with the accompanying drawings, It will be possible. The present invention is capable of various modifications and various forms, and specific embodiments are illustrated in the drawings and described in detail in the text. It should be understood, however, that the invention is not intended to be limited to the particular forms disclosed, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a block diagram showing a restoration apparatus according to the present invention. Referring to FIG.

The restoration apparatus according to the present invention includes an aerial photographing unit 200 installed on an aircraft A for photographing a ground designated according to GIS information, a restoration unit 200 for receiving and processing the collected images taken by the aerial photographing unit 200 100).

The aerial photographing unit 200 is a mobile camera type, and can continuously collect images of various regions at various angles while rotating.

The restoration unit 100 compares the image collected from the aerial photographing unit 200 with an existing image and corrects the image, thereby producing information for restoration of a three-dimensional texture from a two-dimensional image. The restoration unit 100 includes a collection image processing module 110 that receives collected images from the aerial photographing unit 200, an object analysis module 120 that generates individual information by classifying the objects included in the collected images, An object change DB 130 for storing and managing the collected image and object information, an object change checking module 140 for comparing the new collected image with the existing collected image to check whether the object is changed, A video image DB 160 for storing and managing a corresponding video image including link information, and a video image DB 160 for storing image information of a video image corresponding to the variation target object A link information editing module 170 'for editing link information of a video image corresponding to a target object to be changed, and a link information editing module 170' for editing an existing three- A texture restoration module 170 'for restoring a three-dimensional texture of the displayed object image based on image information editing and completing a three-dimensional image image, and a modified three-dimensional image image 170''based on the edited image information and the link information. An input / output module 190 for allowing a worker to manually check whether the object is changed, a camera control unit 160 for controlling the aerial photographing unit 200, Module 190 '.

FIG. 2 is a view schematically showing an editing process of the restoration apparatus according to the present invention. FIG. 3 is a view schematically showing a three-dimensional image image displayed through the texture restoration module according to the present invention. , And will be explained with reference to this.

2 (a) is a two-dimensional collection image obtained by photographing a specific area before a change, and FIG. 2 (b) shows a texture restoration module 170 '' according to the present invention. Dimensional captured image, the B8 object of the object is changed due to demolition, and the captured image is confirmed as a change range (NB) in the newly collected collected image. Therefore, if it is confirmed that there is a change in the object, additional correction work is required to express the three-dimensional image.

The texture restoration module 170 'deletes both the polygon and the texture information of the portion identified by the change range NB in the existing three-dimensional texture, and inserts only the color information of the change range NB as texture information on the floor. That is, the polygon type stereoscopic image of the B8 object shown in FIG. 3 (a) is firstly deleted as shown in (b), leaving only the B7 object image and the B9 object image, The texture restoration module 170 " applies only to deletion of the B8 object image, which is the target of the change range (NB) in the 3D image, and to insertion of the color information, It is possible to complete a new three-dimensional image image.

FIG. 4 is a block diagram illustrating an aerial photographing unit implementing the restoration method according to the present invention, and FIG. 5 is an exploded perspective view and operational views of the aerial photographing unit.

On the other hand, the aerial photographing unit 200 takes an image of the designated area and collects the image, and sends the collected image to the restoration unit 100 where the variation of the individual is estimated.

The aerial photographing unit 200 includes a collection module 210 for taking an image of a designated area and collecting images, an image check module 220 for firstly checking whether an individual in the collected image is a collected image, An image check information DB 230 for storing and managing reference information that is an object, an image adjustment module 260 for adjusting the collected image in accordance with the reference information, a rotation module 240 for rotating the collection module 210, And an image sending module 250 for sending the collected image estimated to be changed to the restoring unit 100.

The aerial photographing unit 200 is installed in a state where the collecting module 210 performing the collecting function such as photographing is suspended in the rotating module 240. Of course, the rotation module 240 is installed on the bottom surface of the aircraft A. Generally, the collecting module 210 is connected to the rotating module 240 via the rotating shaft 211, and is rotated by the power of the rotating module 240. The rotation range can be variously set without limitation depending on the installation position of the aerial photographing unit 200 and the like.

The collection module 210 and the rotation module 240 are supported by the camera case 201 installed in the aircraft A. The camera case 201 includes an image check module 220 and an image check information DB 230, an image adjustment module 260, and an image transmission module 250 may be installed.

FIG. 6 is a flow chart showing the procedure of the restoration method according to the present invention, FIG. 7 is an image schematically showing a state in which the aerial photographing unit firstly analyzes the collected image, FIG. And a restoration method according to the present invention based on the restoration apparatus will be sequentially described with reference to the drawings.

S10; Image information collection stage

The aerial photographing unit 200 is installed on the aircraft A and photographs the ground according to a general aerial photographing method. In the present embodiment, the aerial photographing unit 200 collects an image of a designated area in a panoramic form while rotating in a designated rotation range. Since the collection module 210 of the aerial photographing unit 200 rotates continuously to photograph the designated area, the image collected by the collection module 210 is not an acquired image captured in a predetermined photographing unit, Is a moving image taken continuously while rotating.

Subsequently, as shown in FIG. 7 (a), a vertical pixel axis (hereinafter referred to as 'vertical axis YA') located at the rotation direction front end of the collection module 210 is checked. For example, when the collection module 210 horizontally rotates to the left as shown in FIG. 7 (a), the left vertical axis YA of the collected image is checked.

As described above, since the collection module 210 photographs the image of the designated area in real time in a panoramic form while rotating at a constant speed, it can not confirm the photographing angle of each collected image. Furthermore, it is virtually impossible to track and completely re-collect the same collected image since the suspending type aerial photographing unit 200 may be shaken by the wind or the like and the collection image of the same photographing angle may be different due to aging of the main body . Accordingly, the collection module 210 checks the pixels on the vertical axis YA in real time, sets them as identification information of the collected images, and stores them in the image check information DB 230.

On the other hand, the identification information of the collection image is set in units of the shooting range of the collection module 210. More specifically, when the collection module 210 photographs a designated area once, it collects images of one screen as shown in FIG. 7 (a). Accordingly, the left vertical axis YA at the left end and the right vertical axis (not shown) at the right end can be confirmed at once from the image, and the collection module 210 can collect the horizontal horizontal axis from the left vertical axis YA Determine the range of the image. Therefore, the collection module 210 confirms the vertical axis YA in units of the horizontal intervals, and as shown in FIG. 8, the vertical axis YA of the first collection image P1 and the vertical axis YA of the second collection image P2 '), And sets the identification information of the first and second collection images P1 and P2 on the basis thereof.

On the other hand, a pixel check of the vertical axis YA will be described. As shown in FIG. 7 (b), if the colors in the similar range in which more than the specified number of pixels are designated are successively displayed, the pixels are set as one identification mark. 7B shows the longitudinal axis YA of FIG. 7A. The blue series Y1, the gray series Y2, and the gray series Y3, More than a certain number of pixels were output continuously. Accordingly, the blue series Y1, the gray series Y2, and the gray series Y3 are set as identification marks that form identification information of the corresponding collection image. For reference, the identification mark includes information such as the color, the position of the pixel, the number of pixels, etc., and if the number of different colors is less than or equal to the designated number of pixels during the confirmation of continuity of the similar color, the identification mark is set to the identification mark of the similar color series group. Here, the color similarity range, the number of pixels to be set as the identification mark, the number of pixels of other colors to be ignored in the similar color series group, and the like can be variously changed according to the shooting resolution of the collection module 210, have.

S20; Steps to check

The image check module 220 checks the check mark while checking the horizontal axis XA of the designated position in the collected image collected by the collecting module 210. [

The check mark, like the identification mark on the vertical axis YA, checks the color of each pixel on the horizontal axis XA and checks the similar color outputted continuously over a specified number of pixels, and sets the corresponding color series group as a check mark.

For example, if a specific horizontal axis XA is selected in the collection image as shown in Figures 7 (a) and 7 (c), then the image check module 220 checks the pixels of the horizontal axis XA And a color series group in which the color of the specified similar range is continuously output for a specified number of pixels or more is checked. The specific horizontal axis (XA) of the collected image identifies the gray series X1, the red series X2, the green series X3, the white series X4 and the gray series X5. The image check module 220 sets the checked color series as a check mark of the collected image, and stores the check information composed of the check mark in the image check information DB 230.

As a result, the image check module 220 compares the vertical axis YA of the image collected by the collection module 210 with the identification information stored in the image check information DB 230 to check the collected image to be checked, The check information of the corresponding collection image is searched in the image check information DB 230.

FIG. 9 is a view schematically showing a state in which the collected image of FIG. 7 is adjusted to a pixel position of a reference value.

S30; Collection image check step

The image check module 220 compares the check information with the specified transverse axis (XA) of the collected image to be checked. That is, the check mark of the check information is compared with the color series group of the corresponding horizontal axis XA to check whether or not the color series group matches the check mark. Of course, checking whether the check mark and the color series are matched is checking whether the color, the position of the color, and the length of the color match.

On the other hand, since the aviation photographing unit 200 is installed in the airplane A being operated, there may be a change in the photographing color due to weather or the like. Therefore, if all the collected images and check information do not match in all the collected image checks of the aerial photographing unit 200 rotated in one cycle, or if the matching rate is less than a certain value, the check is stopped and the check is repeated after the specified date.

On the other hand, there may be a change in the collected image due to the shaking of the aerial photographing unit 200. Therefore, as a result of comparing the collected image with the identification information, the image adjustment module 260 determines whether or not the color series group of the collected vertical axis YA in the collected image and the identification mark of the identification information When the position is confirmed as a difference of one pixel, the check information is checked by comparing the position of the collecting abscissa axis XA by one pixel as shown in the drawing of FIG. 9 (b). Of course, as shown in the embodiment, if the positions of the color group and the identification mark are identified by a plurality of pixel differences, the check information is compared with an operation adjusted by the corresponding pixel difference.

S40; Object Change Estimation Collection Image Transfer Phase

As a result of checking the collected image check information of the image check module 220, if the color series group of the horizontal axis (XA) matches the check mark of the check information by more than a specified ratio, the collected image is regarded as having no object change, The image generation module 250 estimates that there is a change in the object in the collection image, and transmits the image generation module 250 to the restoration unit 100. Here, if the collection image of the object to be shipped is the image adjusted by the image adjustment module 260 on a pixel basis, the image transmission module 250 transmits data on the adjusted image.

The start and end of the image data can be performed in real time by wirelessly communicating with the airplane A in a flight on a dedicated frequency band. After the end of the aerial photographing, the photographer inputs the image data storage module (not shown) Or by connecting them.

S50; Collected image verification steps

The acquisition image processing module 110 of the reconstruction unit 100 receiving the image data from the aerial photographing unit 200 acquires the ID of the aerial photographing unit 200 and the identification information of the collected image through the basic information of the received image data Check. In the present embodiment, since the aerial photographing unit 200 photographs various regions, the number of the aerial photographing units 200 must be plural. Therefore, an ID is set for each aerial photographing unit 200, and the collected image processing module 110 identifies the ID, and identifies and classifies the originating camera and the photographing region of the image data.

FIG. 10 is an image showing a classification of objects obtained by processing a collection image forming the basis of a video image, FIG. 11 is an image showing a variation of an existing collection image and a new collection image, and FIG. FIG. 3 is a view schematically showing a manner in which a video image is modified for each section. Referring to FIG.

S60; Steps to Understand Color Range

delete

S70; Object classification step

The object analysis module 120 confirms the output colors in units of pixels, and grasps and classifies the objects output to the collection images. Here, the object classification is based on the color and the pixel position of the corresponding color, and the specific shape of the object is not confirmed. Therefore, the object analysis module 120 classifies the clusters of color pixels in the specified similar range as one object.

The objects such as buildings, bridges, structures, rivers, etc. displayed by the video images have already been identified in their locations, colors and ranges. In other words, after the object is identified in the acquired image as the basis of the image, the image is processed as an image. The existing collection image for this is stored in the collection image DB 130 and the new collection image in which the object analysis module 120 grasps and classifies the object is linked with the existing collection image stored in the collection image DB 130 and stored .

S80; Identification of individual changes

The individual change confirmation module 140 searches existing collection images and new collection images linked to each other in the collection image DB 130 to check whether the individual is changed.

11 (b) is an existing collection image of the image image, and (a) the drawing is a new collection image linked to the existing collection image. In this embodiment, among the pieces of entity information stored in linkage with the existing collection image are B1, B2, B3, B4, B5, and B6. As described above, since the object information includes information on the color of each pixel, the position and range of the object, and the like, it is utilized as a standard for checking whether an object of a newly collected image has changed.

delete

The entity change confirmation module 140 identifies pixels in the same position as the checkpoints B11 and B31 or pixels in the specified range in the new collection image shown in the drawing of FIG. Here, the color of the B11 checkpoint is the green-brown group, and the color of the B31 checkpoint is the dark-brown group. As a result of the check of the entity change checking module 140, the pixels at the same positions as the checkpoints B11 and B31 are in the group of the yellowish brown group and do not match the colors of the four B11 checkpoints and the B31 checkpoint, respectively. As a result, the entity change confirmation module 140 confirms that there is a change in the target entity B11 of the check point B11 and the target entity B3 of the checkpoint B31, and the group of the tan group, which is the color identified in the newly collected image, And the cluster is identified as the range in which the change is made.

In the present embodiment, the individual change confirmation module 140 identifies and specifies the change range NB, which is the pixel range of the tan group, as shown in Figs. 11 (a) and 12 , And the change range (NB) to the input / output module (190) and outputs it. The operator checks whether the change range NB is correctly specified by confirming the designated change range NB in the new collected image output to the input / output module 190, inputs the confirmation signal by correcting or confirming the contents, (140). Here, as shown in FIG. 12 (b), the operator composes the change range NB to the corresponding point of the existing acquired image through the input / output module 190, confirms whether or not there is interference with the invariant object, The final image synthesis data is generated and included in the determination signal.

S90; Target image image search step

Upon receiving the confirmation signal from the entity change confirmation module 140, the video segment search module 150 searches the video image DB 160 for a corresponding two-dimensional video image and a three-dimensional video image.

S100; Edit information step

The image information editing module 170 and the link information editing module 170 'check the section corresponding to the change range NB in the two-dimensional image image searched by the image section search module 150 and output image information and link information Respectively.

The image information editing module 170 checks the position, size, color, and the like of the change range NB and determines a corresponding interval of the two-dimensional image image as the change range NB Edit in color and size. For reference, the image information editing module 170 checks image synthesis data obtained by synthesizing a change range NB on an existing acquired image, which is the background of a two-dimensional image, from the synthesized signal, and sets the determined change range NB to 2 Composite edit to the subject area of the 3D image.

On the other hand, the link information editing module 170 'deletes all the link information such as the text linked to the editing subject area, receives the new text inputted by the operator from the input / output module 190, and links it to the editing subject area. That is, the user deletes text such as a building name, a park name, a bridge name, and the like linked to a pre-editing area and inputs text such as a building name, a park name, and a bridge name of a newly edited conversion range (NB).

S110; Texture restore steps

The texture restoration module 170 'checks the target object of the three-dimensional video image with reference to the section in the two-dimensional video image edited by the image information editing module 170 based on the change range NB, Delete the texture and polygons applied to the image.

Next, the texture restoration module 170 'checks the color range of change (NB) for the corresponding collection image of the two-dimensional image and applies the identified color information to the polygon removal point of the three- (NB) color information at the bottom NB 'of the object image formed in the 3D image.

3 (b), the corresponding object image is deleted through the polygon deletion in the three-dimensional image image, and the change range (NB) to the deletion point bottom NB ' The range NB is displayed on the three-dimensional image.

S120; Information update phase

The video image update module 180 updates and stores the two-dimensional video image and the three-dimensional video image edited by the image information editing module 170 and the link information editing module 170 'in the video image DB 160.

Meanwhile, the collected image DB 130 updates the collected image, which is the background of the newly updated image image, with the existing collected image, .

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

100; Restoring unit 110; Collection image processing module
120; An object analysis module 130; Collected image DB
140; An entity change confirmation module 150; Video segment search module
160; A video image DB 170; Image information editing module
170 '; Link information editing module 170 ", a texture restoration module
180; A video image update module 190; I / O module
190 '; Camera control module 200; Aerial photographing department
210; Collection module 220; Image check module
230; Image check information DB 240; Rotation module
250; Image sending module 260; Image adjustment module

Claims (1)

When the panoramic image is classified into a predetermined horizontal interval and the pixels of the specified range or more are designated by the constituent pixels on the left or right vertical axis YA of the newly collected image, A collection module 210 for setting an identification mark of an image; An image check information DB (230) storing check information composed of a check mark of a horizontal axis (XA) specified in a previous acquisition image; If the pixels of the specified number of pixels or more in the pixels of the specified horizontal axis (XA) are successively displayed in the designated similar area in the new collection image, the pixels are set as a new check mark. In the image check information DB 230, And checks whether or not the output color, color position, and color length of the pixels of the new check mark and the pixels of the check information coincide with each other by checking the check information corresponding to the specified horizontal axis XA of the new check mark And if the new check mark and the check information match the specified ratio or more, the new collected image is regarded as having no entity change, and if the new check image matches the specified rate, the new collected image is estimated as having an entity change An image check module 220 for checking the image; Before comparing the new check and the check information for comparison of the image check module 220, the difference between the identification mark position of the previous acquisition image and the identification mark position of the new acquisition image is checked, An image adjustment module 260 for adjusting the position; An image generation module (250) for generating a new collection image in which an individual variation is estimated, as image data;
An acquisition image processing module 110 for confirming the basic information of the image data and confirming the ID of the aerial photographing unit 200 and the identification information of the newly acquired image; An acquisition image DB 130 for storing an existing acquisition image; And a step of classifying the group of color pixels in a similar range specified in the new collection image as one entity and classifying the new collection image into an existing group stored in the collection image DB 130 An object analysis module 120 for storing and linking the collected images; A new collection image and an existing collection image linked to each other are retrieved from the collection image DB 130, a plurality of check points are set within the range of the objects classified in the existing collection image, Determining whether there is a change in the entity if it is determined that the number of checkpoint colors does not coincide with the number of checkpoints, The pixel cluster in which the colors of the pixels in the newly collected image are continuously output is identified as a result of the comparison of the colors, and the cluster is designated as the change range (NB) An entity change confirmation module 140 for transferring the newly collected image to the input / output module 190 and outputting the same; An input / output module (190) for editing the change range (NB) displayed in the existing collection image to generate image synthesis data, and inputting a determination signal for the change range (NB); A video image DB 160 for storing a two-dimensional video image and a three-dimensional video image; An image segment search module 150 for confirming the determination signal and searching for a corresponding two-dimensional image and a three-dimensional image image in the image image DB 160; An image information editing module 170 that identifies an editing subject area corresponding to the change range NB in the two-dimensional image and synthesizes the corresponding image in the change range NB in accordance with the image synthesis data, ; A link information editing module 170 'for deleting the text linked to the editing subject area and linking the new text input from the input / output module 190 to the editing subject area; The polygon and the texture of the editing subject area object image edited by the image information editing module 170 in the three-dimensional image image are deleted, and the corresponding color of the change range NB is inserted at the bottom point of the object image, And a video image update module 180 for updating the edited two-dimensional video image and the three-dimensional video image in the video image DB 160,
Dimensional image by using a GIS-based aerial image matching.

Images