KR101720761B1 - system for building three-dimensional space information using MMS and multi-directional tilt aerial photos - Google Patents

Abstract

The present invention relates to a system for building three-dimensional space information using an MMS and a multi-directional tilt aerial photo and, more specifically, to a system for building three-dimensional space information using the MMS and the multi-directional tilt aerial photo, wherein ground topography feature information are more accurately and efficiently obtained through a mobile mapping device (MMS) and the ground topography feature is combined with the multi-directional tilt aerial photo, thereby accurately building three-dimensional space information.

Description

[0001] The present invention relates to a system for building three-dimensional spatial information using MMS and multi-directional oblique aerial photographs,

The present invention relates to a three-dimensional spatial information construction system using MMS and a multidirectional oblique aerial photograph, more specifically, to more accurately and efficiently acquire terrain topographical information through a mobile mapping device (MMS) The present invention relates to a three-dimensional spatial information construction system using an MMS and a multi-directional oblique aerial photograph so as to precisely construct three-dimensional spatial information in combination with directional inclined aerial photographs.

In general, the 3D space modeling method using existing aerial surveying is available only up to the photographed part of the acquired building, and the process has been forcibly extended to the end of the building.

Since the image has been forcibly expanded, not only the visibility is significantly lowered but also the accurate coordinate information about the object can not be obtained, and it is difficult to provide more realistic image data to the user even after completing the modeling work.

In addition, the conventional space modeling method has a disadvantage in that an excessive labor cost is generated by utilizing data constructed manually by field investigation, and errors of geographical information are frequently generated due to such manual operation, and it is difficult to correct and update .

To overcome these drawbacks, geographic information data on buildings and road facilities are being constructed using the latest surveying equipment such as Mobile Mapping System (MMS).

However, it is difficult to acquire precise coordinate information due to distortion of the measured image, and the like. In addition, since the accuracy of the information is lacking in the urban area, there are many problems in building a geographic information database .

Korean Patent Registration No. 10-1234961 (Feb. 23, 2013) 'Automatic 3D space modeling method and system using aerial photograph and MMS (Mobile Mapping System)

SUMMARY OF THE INVENTION The present invention has been made in view of the above-described problems in the prior art, and it is an object of the present invention to provide a three- The coordinate information is obtained and filtering is performed using the weighted threshold value in extracting parameters for image correction to perform finer image correction and error components are redundantly removed in parameter extraction for image correction There is provided a three-dimensional spatial information construction system using MMS and a multidirectional oblique aerial photograph capable of performing more detailed image correction.

(여기서, am 은 영상 중심점에서 곡선의 현에 내린 수선의 길이를 나타내고, R은 영상 대각선의 길이를 나타내고, m = 1~M , M은 선의 개수를 나타내며, ψ는 사용자 파라미터를 나타냄)에 의해 획득되는 필터링 모듈; 상기 제1보정 그룹과 상기 제2보정 그룹이 제거된 영상 정보에 기초하여, 영상의 휘어짐 정도를 나타내는 매개변수를 추출하는 매개변수 추출 모듈; 상기 매개변수를 이용하여 상기 영상 정보의 보정을 수행하는 영상보정 모듈을 구비한 3차원 공간정보 구축시스템에 있어서;
상기 모바일 매핑 장치를 차량(1)에 탑재하되, 차량(1)의 운전석(DRV)에는 주제어기인 컨트롤 모듈(150)과 통신하여 제어되는 제어패널(CTR)이 설치되고, 상기 제어패널(CTR)은 구동유닛(10)을 제어하도록 구성되며, 구동유닛(10)은 차량(1)의 상면을 관통하여 차량(1) 내부에 형성된 수납챔버(CHM)로 수납될 수 있도록 승강 가능하게 설치되고; 차량(1)의 천정에서 차량 내부의 수납챔버(CHM)에 매립되어 승하강 가능하게 설치되는 받침플레이트(12)와, 상기 받침플레이트(12) 상에 베어링고정된 메인축(22)과, 상기 메인축(22)과 일체를 이루면서 상기 메인축(22) 보다 더 큰 직경을 갖는 원형단면을 갖는 원형상의 서브축(24)과, 상기 서브축(24)의 원주방향으로 형성된 래크(26)와, 상기 래크(26)에 치결합된 피니언(28)과, 상기 피니언(28)이 고정되고 상기 받침플레이트(12) 상에 고정된 회동모터(30)와, 상기 서브축(24)의 상단에 고정된 상판(32)과, 상기 상판(32)에 안착된 사각프레임(34)과, 상기 사각프레임(34)을 관통하여 양단이 각각 자회전가능하게 베어링고정되되 길이 중앙을 기준으로 좌우 양측이 반대방향으로 스크류 가공된 볼스크류(36)와, 상기 볼스크류(36)의 사각프레임(34)을 관통한 일단에 고정된 종동기어(38)와, 상기 종동기어(38)에 기어결합하는 구동기어(40)와, 상기 구동기어(40)가 고정되고 상기 사각프레임(34)의 일측 외면에 고정된 구동모터(42)와, 상기 볼스크류(36)에 치결합된 상태로 끼워져 볼스크류(36)의 회전방향에 따라 모아지거나 벌어지는 형태로 유동하는 제1,2유동블럭(44a,44b)과, 상기 사각프레임(34)의 마주보는 내측면에 일정길이 형성된 가이드홈(46)과, 일단은 상기 가이드홈(46)에 끼워지고 타단은 상기 제1,2유동블럭(44a,44b)의 양측면에 나사조립되는 가이드바(48)와, 상기 제1,2유동블럭(44a,44b)의 각 외측면에 설치된 회전봉기동모터(50)와, 상기 제1,2유동블럭(44a,44b)의 상부에 설치되고 상기 회전봉기동모터(50)에 의해 회전제어되며 상단에는 각각 좌안 영상카메라(CAM1)와 우안 영상카메라(CAM2)가 설치된 회전봉(48)을 포함하는 것을 특징으로 하는 엠엠에스 및 다방향 경사 항공사진을 이용한 3차원 공간정보 구축시스템을 제공한다.An object of the present invention is to provide an image capture module for acquiring image information from a plurality of cameras when constructing three-dimensional spatial information using aerial photographs and a mobile mapping system. A GPS receiving module for receiving GPS information from a satellite and obtaining current position information of the camera; An inertia measurement module for obtaining horizontal information of the camera using a plurality of sensors; An image processing module for correcting the image information based on the image information, the current position information, and the horizontal information; A control module for controlling the image information, current position information and horizontal information to be transmitted to the image processing module; And a buffer for storing image information; An aerial photograph database for receiving and storing the image information from the mobile mapping device or receiving and storing aerial photograph data from an external database; A data processing module for determining a target object by comparing the image information obtained from the mobile mapping device with the aerial photograph data obtained from the aerial photograph database, and performing three-dimensional space modeling using the determined target object information; And a communication module for receiving request information for a spatial modeling service from a user, transmitting the request information to the mobile mapping device, the aerial photograph database, and the data processing module, and transmitting the three-dimensional spatial data obtained from the data processing module to a user; Wherein the image processing module detects a curve from the image information received from the captured image acquisition module to set a first correction group, removes the first correction group from the image information, Sets the lines out of the threshold value from the center point on the three-dimensional coordinates as the second correction group from the image information from which the group is removed, removes the second correction group from the image information from which the first correction group is removed, silver

(Where am denotes the length of the waterline at the center of the curve at the center of the image, R denotes the length of the image diagonal, m = 1 to M, M denotes the number of lines, and ψ denotes the user parameter) A filtering module to be obtained; A parameter extracting module for extracting a parameter indicating a degree of warping of the image based on the image information from which the first correction group and the second correction group have been removed; And an image correction module for performing correction of the image information using the parameters, the system comprising:
A control panel CTR is installed in the driver's seat DRV of the vehicle 1 in communication with the control module 150 which is a main controller and the control panel CTR is installed in the driver's seat DRV of the vehicle 1, And the drive unit 10 is elevably installed so as to be housed in a storage chamber CHM formed inside the vehicle 1 through the upper surface of the vehicle 1; A main shaft 22 fixed to the bearing plate 12 by bearings, a support shaft 12 fixedly mounted on the support plate 12, A circular sub shaft 24 integrally formed with the main shaft 22 and having a circular cross section and having a diameter larger than that of the main shaft 22 and a rack 26 formed in the circumferential direction of the sub shaft 24 A pinion 28 coupled to the rack 26 and a rotary motor 30 fixed to the pinion 28 and fixed to the support plate 12; A rectangular frame 34 seated on the upper plate 32 and fixed to the frame so that both ends of the rectangular frame 34 are rotatable through the square frame 34, A ball screw 36 which is screwed in an opposite direction and a ball screw 36 which is fixed to one end of the square frame 34 of the ball screw 36 A drive gear 40 fixed to the outer surface of one side of the rectangular frame 34 and fixed to the drive gear 40; First and second flow blocks 44a and 44b that are inserted into the ball screw 36 in a state of being engaged with the ball screw 36 and flow in a manner of gathering or spreading according to the rotation direction of the ball screw 36, A guide groove 46 having one end fixed to the guide groove 46 and the other end screwed on both sides of the first and second flow blocks 44a and 44b; A rotary bar start motor 50 provided on each of the outer surfaces of the first and second flow blocks 44a and 44b and a second rotary block 44 installed on the first and second flow blocks 44a and 44b, And a rotation bar 48 which is rotatably controlled by a starter motor 50 and has upper left and lower right image cameras CAM1 and CAM2, And a three-dimensional spatial information construction system using multi-directional oblique aerial photographs.

According to the present invention, it is possible to acquire more accurate three-dimensional space coordinate information by correcting the warping phenomenon of an image through filtering after acquiring an image acquired through MMS.

Fig. 1 shows a schematic block diagram of a three-dimensional spatial information construction system to which the present invention is applied.
2 is a schematic block diagram of an image processing module constituting a three-dimensional spatial information construction system according to an embodiment of the present invention.
FIG. 3 shows a coordinate system for explaining a method of performing image correction by defining a first correction group and a second correction group constituting a three-dimensional spatial information construction system according to an embodiment of the present invention.
FIG. 4 shows a coordinate system for explaining a weighted threshold calculation process for image correction according to an embodiment of the present invention. Referring to FIG.
5 is a schematic internal block diagram of a data processing module constituting a three-dimensional spatial information construction system according to an embodiment of the present invention.
FIG. 6 is a diagram illustrating a method of modeling three-dimensional coordinate information using coordinate information of a target object according to an embodiment of the present invention. Referring to FIG.
FIG. 7 is a flowchart for explaining a three-dimensional space modeling method according to an embodiment to which the present invention is applied.
8 is a flowchart for explaining a method of correcting an image obtained from a camera for three-dimensional space modeling according to an embodiment of the present invention.
9 is a flowchart for explaining a method for acquiring coordinate information of a target object from a corrected image for three-dimensional space modeling according to an embodiment of the present invention.
10 is an exemplary diagram illustrating a driving unit in a mobile mapping apparatus constituting a three-dimensional spatial information construction system according to an embodiment of the present invention.
FIG. 11 is an exemplary view showing the rotation drive unit of the drive unit of FIG. 10; FIG.

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

Before describing the present invention, the following specific structural or functional descriptions are merely illustrative for the purpose of describing an embodiment according to the concept of the present invention, and embodiments according to the concept of the present invention may be embodied in various forms, And should not be construed as limited to the embodiments described herein.

In addition, since the embodiments according to the concept of the present invention can make various changes and have various forms, specific embodiments are illustrated in the drawings and described in detail herein. However, it should be understood that the embodiments according to the concept of the present invention are not intended to limit the present invention to specific modes of operation, but include all modifications, equivalents and alternatives falling within the spirit and scope of the present invention.

Prior to the detailed description of the present invention, a space modeling system is an information system that integrates geographical data occupying a spatial position and attribute data related thereto, and efficiently collects and stores various types of geographical information Software, geographical data, and human resources used to update, process, analyze, and output data. This makes it easier to use various kinds of spatial information. However, in order to provide clear and realistic geographical information in a rapidly changing city center, it is necessary to use the mobile surveying data efficiently.

It should be noted that the present invention will be described in further detail with the main feature that most of the techniques of the prior art No. 10-1234961 are used as it is, . However, in the registered patent, the term described as the three-dimensional space modeling system is referred to as a three-dimensional spatial information construction system only.

1, a three-dimensional spatial information construction system to which the present invention is applied includes a mobile mapping apparatus 100, a communication module 200, an update module 300, an aerial photograph database 400, and a data processing module 500 The mobile mapping device 100 includes an image pickup module 110, an image processing module 120, an inertia measurement module 130, a GPS reception module 140, a control module 150, 160).

Here, the spatial model may mean an object occupying a space in a three-dimensional image, for example, a road facility, a building, a road facility, and an auxiliary facility.

The spatial model information may refer to the location, distance, area, and property information of the object, i.e., a road facility, a building, a road facility, and an auxiliary facility.

The mobile mapping apparatus 100 can measure a road facility, a building, a road-use facility, and an auxiliary facility in a target area while moving the route in the target area.

The mobile mapping device 100 refers to a moving and measurable device, for example, a car or a plane equipped with a measurable camera.

The photographed image acquisition module 110 may include a left-eye image camera and a right-eye image camera. The photographed image acquisition module 110 may acquire stereo images by photographing the road facilities, buildings, road facilities, and auxiliary facilities using a left- can do.

In this case, the captured image acquisition module 110 needs to correct the acquired image due to the camera shake at the time of shooting due to the shake of the mobile mapping device 100, or a bending problem of the camera lens itself.

Therefore, in the embodiment to which the present invention is applied, a method of estimating a correction parameter for correcting such an image and a new threshold value calculating method using weighting are proposed.

This will be described in more detail in Fig. 3 and Fig.

The captured image acquisition module 110 acquires the left eye image and the right eye image acquired from the camera mounted in the mobile mapping device 100 and acquires the left eye image and the right eye image from the GPS receiving module 140, The current position information of the left eye image and the right eye image can be obtained using the position information.

The moving path of the mobile mapping apparatus 100 can be generated from the current position information of the left eye image and the right eye image.

That is, the movement path may be determined from the position information of the mobile mapping apparatus 100, and the left eye image and the right eye image acquired from the camera may be matched for each movement path.

The inertia measurement module 130 can acquire the horizontal information of the mobile mapping apparatus 100 by receiving sensing information using multiple sensors, and can perform more detailed image correction using the horizontal information.

In an embodiment to which the present invention is applied, the inertia measurement module 130 logs data at intervals of 100 Hz.

The GPS receiving module 140 may receive the GPS information from the satellites and obtain the current position information of the mobile mapping device 100. [

The mobile mapping device 100 acquires location information of a vehicle in a city center through the GPS receiving module 140 and transmits the location information of the vehicle through an IMU (Inertial Measurement Unit) By obtaining horizontal information, more accurate 3D space modeling can be performed.

In an embodiment to which the present invention is applied, the GPS receiving module 140 logs data at intervals of 1 Hz.

The image processing module 120 calculates parameters by using the horizontal information obtained from the inertia measurement module 130 and the position information obtained from the GPS receiving module 140 for correction of the acquired image.

The parameter calculation method to which the present invention is applied is that a straight line in a 3D image is a straight line even if it is converted into a 2D image.

That is, more accurate 3D space modeling can be performed by detecting lines that are not straight lines of the 3D image, excluding them, and then performing image correction.

In addition, in the process of calculating the parameters, faster 3D space modeling can be performed by excluding lines out of the threshold.

A detailed description of these embodiments is given in Figs. 3 and 4. Fig.

The control module 150 outputs the left eye image and the right eye image obtained from the captured image acquisition module 110, the horizontal information obtained from the inertia measurement module 130, and the position information obtained from the GPS reception module 140, respectively To the image processing module 120, and controls the image processing module 120 to calculate parameters using the image information, the horizontal information, the position information, and the like.

The control module 150 controls the synchronization between the sensed image acquisition module 110, the inertia measurement module 130 and the GPS reception module 140. In an embodiment to which the present invention is applied, The inertial measurement module 130, and the GPS reception module 140, respectively, based on the GPS time obtained from the GPS receiver 140, have.

The buffer 160 stores the image information of the left eye image and the right eye image obtained from the sensed image acquisition module 110 in a buffer and provides the requested image information when the image information is requested from the outside.

The buffer 160 may be composed of a memory and a memory control module. The memory 160 may be rearranged through a log analysis or the like to provide a faster spatial data service.

For example, it is possible to determine the received request information through the log analysis, that is, frequently requested video information, and process the video information in a different manner accordingly.

If the received request information is frequently requested video information, the video information may be cached in a memory in units of layers and updated automatically.

On the other hand, if the image information is not frequently requested, the corresponding image information is deleted from the memory, or if the image information is not previously requested, the corresponding image information is updated to the table information and a corresponding code is generated and stored have.

The communication module 200 transmits the request information to the mobile mapping apparatus 100, the update module 300, the aerial photograph database 400, and the data processing module 500 when receiving the request information for the spatial modeling service from the user.

If the received request information requires video information of the mobile mapping apparatus 100, the mobile mapping apparatus 100 transmits the request information to the mobile mapping apparatus 100, and transmits the request information from the mobile mapping apparatus 100 It is possible to receive corresponding spatial data.

The communication module 200 manages communication between a user terminal (not shown) and an external terminal (not shown) and between the mobile mapping apparatus 100 and the data processing module 500, May support a variety of communication standards such as local area network (LAN), wireless LAN (WLAN), wireless broadband (WIBRO), world interoperability for microwave access (WIMAX), high speed downlink packet access (HSDPA)

The update module 300 may update the data stored in the buffer 160 in the mobile mapping apparatus 100 with the modified data through the image processing module 120 or the data processing module 500 or the like.

Also, the data stored in the aerial photograph database 400 can be updated with the modified data through the image processing module 120 or the data processing module 500. [

The aerial photograph database 400 includes information on the area, length, and location of the road facilities, buildings, road facilities, and other facilities. The aerial photograph database 400 receives data from the mobile mapping device 100, And can receive the aerial photograph data from the database.

The aerial photograph database 400 may include a memory and a memory control module. The aerial photograph database 400 may provide spatial data service more rapidly by rearranging memories through log analysis and the like.

For example, it is possible to determine through the log analysis whether the received request information is frequently requested aerial photograph data, and to process the aerial photograph data accordingly.

If the received request information is frequently requested aerial photograph data, the aerial photograph data may be cached in a memory in units of layers and automatically updated.

On the other hand, if the data is not the frequently requested aerial photograph data, the corresponding aerial photograph data is deleted from the memory, or if the aerial photograph data is not previously requested, the corresponding aerial photograph data is updated to the table information, Can be created and stored.

The data processing module 500 generates 3D space modeling information using the data obtained from the mobile mapping apparatus 100 and the aerial photographing database 400.

The data processing module 500 may include an object extraction module 501, an aerial photograph extraction module 502, an object positioning module 503, a coordinate comparison module 504, and a three-dimensional modeling module 505 .

This will be described in more detail in FIG.

2, the image processing module 120 may include a parameter extraction module 121, a filtering module 123, and an image correction module 125.

Most cameras using a lens have a problem that a straight line is bent into a curved line, and a phenomenon occurs in which the image is expanded or contracted radially from the bent center.

If the deflection phenomenon is not properly corrected, serious problems may occur in viewing 3D images or in digital image analysis.

In order to solve this problem, it is possible to perform mathematical modeling of the bending phenomenon and to perform compensation by estimating parameters for determining the degree of bending and inversely converting the parameters.

Then, curves in the image are detected, and non-straight lines on the 3D coordinates are defined as a first correction group, and correction is performed.

Furthermore, in one embodiment of the present invention, lines that are not a curve on the 3D coordinates and that interfere with parameter estimation can be defined and removed as a second correction group.

3, assuming that the base image is R, the convex warped image is V, and the concave warped image is C, the coordinates of a point that is not bent with respect to the center point A is O = (X, Y) , And the coordinate of the bent point is Oc = (Xc, Yc), the relationship between the two coordinates can be expressed by the following equations (1) and (2).

Gi denotes a parameter reflecting the degree of warping of the image, and when Gi > 0, it indicates convex warpage, and Gi < 0 indicates concave warpage.

[Equation 1]

&Quot; (2) &quot;

Here, a represents the distance from the center point A of the image to the coordinate Oc of the convex curved image, and a is represented by the following equation (3).

&Quot; (3) &quot;

As an embodiment to which the present invention is applied, a method of calculating the parameter will be described.

The parameter extraction module 121 first searches for a segment existing in the image, and calculates the rate of change and angle of each pixel in the segment.

The segment can be detected by grouping the pixels of the same straight line into one group.

A pixel having a rate of change higher than a given threshold value is set as a starting point and a pixel having the largest rate of change in a predetermined window is set as a group and the next pixel is searched again through the window using the pixel as a starting point.

At this time, the window of the predetermined size may use 3x3, 4x4 or 5x5 window.

The curve may be formed by connecting the segments from the group consisting of the detected pixels through the above process.

At this time, the distance between the end points of the two segments, the angle between the two segments, and the vertical distance of the two segments are calculated. If the calculated values are smaller than the preset threshold value, the segments are regarded as one line have.

A line that is connected to the segments and is regarded as a curve on a 3D coordinate may be set as a first correction group, and the first correction group may be removed in an image.

For example, if one target line of the F curves is referred to as Lm (m = 1 to M) and Nm pixels constituting Lm are denoted by Pn = (Xn, Yn) (n = 1 to Nm) The parameter Gi when the Nm number of pixels are maximally straight can be obtained.

The calculated Gi can also be applied to other curves to obtain Pn.

Pn is defined as an error En of each pixel, and when the pixels whose absolute magnitudes exceed the preset threshold value? M exceed a preset percentage in one curve, they are set as the first correction group, The first correction group can be removed in the image.

Through this process, it is possible to calculate the parameter Gi which causes the first correction group to be the maximum straight line among the removed lines.

The filtering module 123 can define and filter the lines serving as the error element in the parameter calculation as the second correction group even though the curve is not a curve on the 3D coordinates.

For lines located near the center point, you can narrow the range to which the parameter is applied by setting more precise thresholds.

For example, referring to FIG. 4, when it is determined that the error of each pixel exceeds a predetermined threshold value, a weight is applied to the threshold value according to the distance from the image center to the curve Lm to determine whether it corresponds to the second correction group Can be determined.

The distance from the image center point A to the curve Lm can be defined as the length am of the perpendicular line on the straight line F, and the weight can be normalized to a range between 0 and 1.

At this time, am can be defined as shown in Equation (4) below.

&Quot; (4) &quot;

When the weight for normalization is 0, am is 0 when the line passes the center of the image, and when the weight is 1, am is the distance from the center of the image to the diagonal vertex.

The new threshold value? M_new to which the weight is applied can be expressed by the following equation (5).

&Quot; (5) &quot;

Here, R denotes the length of the image diagonal, m = 1 to M, M denotes the number of lines, and? Is a user parameter.

As described above, the new threshold value? M_new can be calculated by weighting the threshold value according to the distance from the center of the image to the line, and more precise image correction can be performed by obtaining a more accurate parameter Gi.

The image correction module 125 may correct the image warping phenomenon using parameters obtained through the above process.

The mobile mapping apparatus 100 corrects the image through the process described above, and the corrected image is transmitted to the data processing module 500.

5, the data processing module 500 includes an object extraction module 501, an aerial photograph extraction module 502, an object positioning module 503, a coordinate comparison module 504, and a three-dimensional modeling module 505. [ &Lt; / RTI &gt;

The object extraction module 501 may extract a desired object from the corrected image obtained from the mobile mapping apparatus 100 and obtain coordinate information of the object.

A search area may be set to extract the target object, and a target object may be extracted from the corrected image according to the search area.

At this time, the target object can use each pixel RGB value of the corrected image. For example, a pixel having the same characteristic can be detected by confirming eight integer pixel values adjacent to the target pixel.

If there are a plurality of target objects extracted through the above process, an object having the closest distance from the previous position of the target object can be selected. If no target object is extracted, the object can be selected by the user's input .

The object position determination module 503 can obtain the coordinate information of the target object by determining the center point of the target object extracted from the object extraction module 501. [

The center point may be determined by Equation (6) below.

&Quot; (6) &quot;

Here, x and y represent the coordinates of the center point, n is the number of pixels in the x-axis direction, and N is the number of pixels in the y-axis direction.

The aerial photograph extraction module 502 can extract the aerial photograph coordinate information corresponding to the corresponding image from the aerial photograph database 400. [

At this time, the aerial photograph extracting module 502 may extract the corresponding image corresponding to the position information from the aerial photograph database 400 according to the position information obtained from the GPS receiving module 140. [

The coordinate comparison module 504 can check whether the objects are matched by comparing the coordinate information of the object obtained from the object positioning module 503 with the aerial photograph coordinate information obtained from the aerial photograph extraction module 502 have.

For example, matching points can be identified by extracting common points unchanged in size and rotation from images having different directions and sizes.

An aerial photograph image extracted from the aerial photograph database 400 may be passed through a Gaussian filter having various dispersion values and an error image may be generated by sequentially subtracting the passed images according to a scale.

This can be performed by Equation (7) below.

&Quot; (7) &quot;

Where D (x, y, σ) represents the function of the image passed through the Gaussian filter and G (x, y, σ) represents the Gaussian filter. Respectively.

The position of the pixel corresponding to the extreme value (maximum and minimum values) can be extracted from the generated error image.

Here, the pixel position corresponding to the extreme value (maximum and minimum values) is a case where the selected pixel value is larger or smaller than a total of 26 pixel values, that is, eight pixels adjacent to the selected pixel value and nine pixels of the scaled upper and lower images .

That is, pixels corresponding to the extreme values (maximum and minimum values) can be extracted as a common point. Noise removal and strong edge components are removed from the extracted common points, and direction information and size are set for the remaining common points.

The direction information and the size are determined by the following equations (8) and (9), respectively.

&Quot; (8) &quot;

&Quot; (9) &quot;

A 16x16 block is set around the common point, and the direction of change is measured for each pixel in the block.

The change direction is set to be proportional to the change slope, and the larger the change slope, the larger the probability distribution in the change direction.

The probability distribution for the change direction is divided into eight directions and stored, which is expressed in a 128-dimensional vector form with respect to a 16x16 block.

The common point vector information of the aerial photographic images thus obtained and the common point vector information of the corrected image are compared to check whether the objects are matched.

The coordinate information of the target object can be extracted based on the matching check result.

As another embodiment to which the present invention is applied, filtering may be used for the object identification.

First, a boundary region of an object in an image is identified, and a target object can be identified using the geometric characteristics of the boundary region.

For example, since a building, a signboard, a roadside tree, and the like have respective geometric characteristics, a target object can be identified by extracting and comparing only the points of the corner of the building, the signboard, .

The three-dimensional modeling module 505 can model the three-dimensional coordinate information using the coordinate information of the target object.

6, assuming that two left and right cameras photograph an object in order to model the three-dimensional coordinate information, the distances from the inner angle of the triangle and the left and right cameras to the object are obtained using Equations 10 to 17 below .

&Quot; (10) &quot;

&Quot; (11) &quot;

&Quot; (12) &quot;

&Quot; (13) &quot;

&Quot; (14) &quot;

The three-dimensional coordinates (X_o, Y_o, Z_o) of the target object O can be obtained by the following equations (15) to (17), where Z_o coordinate is obtained by multiplying the Y_l coordinate of the image obtained from the left camera and the Y_l coordinate The average value of the coordinates, the focal length information, and the Y-axis distance to the object.

&Quot; (15) &quot;

&Quot; (16) &quot;

&Quot; (17) &quot;

Dimensional space modeling can be performed using the three-dimensional coordinates (X_o, Y_o, Z_o) of the object O obtained by the equations (15) to (17).

FIG. 7 is a flowchart for explaining a three-dimensional space modeling method according to an embodiment to which the present invention is applied.

First, the captured image acquisition module 110 in the mobile mapping apparatus 100 includes a left eye image camera and a right eye image camera, and a left eye image and a right eye image can be obtained from the cameras, respectively (S710).

The current position information of the cameras in the mobile mapping apparatus 100, that is, the obtained left and right eye images, is acquired from the GPS receiving module 140, and the horizontal information of the camera is acquired from the inertia measurement module 130 (S720).

The parameter extraction module 121 in the image processing module 120 may extract parameters for image correction using the horizontal information and the current position information of the camera in operation S730.

At this time, the filtering module 123 may perform filtering using the weighted threshold value at the time of extracting the parameters (S740). The image correction module 125 may perform image correction using parameters that have been performed until filtering (S750).

The object extraction module 501 in the data processing module 500 receives the corrected image from the mobile mapping device 100 and extracts the target object in operation S760.

Then, the object position determination module 503 can obtain the coordinate information of the target object by determining the center point of the extracted target object (S770).

The coordinate comparison module 504 can check whether the matching is performed by comparing the coordinate information of the obtained object and the coordinate information of the corresponding aerial photograph (S780).

The three-dimensional modeling module 505 can perform three-dimensional space modeling using the coordinate information of the target object (S790).

8 is a flowchart for explaining a method of correcting an image obtained from a camera for three-dimensional space modeling according to an embodiment of the present invention.

First, a curve may be detected from the image information obtained from the captured image acquisition module 110 (S810).

The first correction group may be set to non-straight lines on the three-dimensional coordinates of the detected curves (S820).

The lines corresponding to the set first correction group may be removed from the image information (S830).

In step S840, the first correction group may be detected from the center of the three-dimensional coordinate image, and the second correction group may be set to a second correction group.

At this time, in order to reset a more precise threshold value, a new threshold value can be reset by applying a weight according to the distance from the image center point to the curve.

And the second correction group can be set based on the reset threshold value.

The lines corresponding to the set second correction group may be removed from the image information (S850).

The parameter may be extracted from the image from which the second correction group is removed (S860).

The image correction may be performed by performing inverse transformation using the extracted parameters (S870).

9 is a flowchart for explaining a method for acquiring coordinate information of a target object from a corrected image for three-dimensional space modeling according to an embodiment of the present invention.

The image information of the target object obtained from the object position determination module 503 can be extracted (S910).

Then, the coordinate information of the aerial photograph corresponding to the corrected image can be obtained from the aerial photograph database 400 (S920).

The image information of the target object is compared with the aerial photograph coordinate information to confirm whether the objects are matched.

For example, matching points can be identified by extracting common points unchanged in size and rotation from images having different directions and sizes.

The aerial photographic image is passed through a Gaussian filter, and an error image is generated by sequentially subtracting the passed images according to a scale (S930).

The positions of pixels corresponding to extreme values (maximum and minimum values) from the generated error images can be extracted and set as common points (S940).

Common point vector information can be generated by removing noise and strong edge components from the extracted common points and setting direction information and size for the remaining common points (S950).

By comparing the common point vector information of the aerial photographic images thus obtained and the common point vector information of the corrected image, it is possible to confirm whether or not the objects are matched.

The coordinate information of the target object may be obtained based on the matching result (S960).

10 and 11, the mobile mapping apparatus 100 can be implemented in the vehicle 1, and in particular, by specifying the installation structure of the captured image acquisition module 110, Can be improved.

To this end, the present invention includes the driving unit 10 as shown in Fig.

At this time, the driving unit 10 is mounted on the upper surface of the movable vehicle 1, and a control panel CTR for controlling the driving of the driving unit 10 is installed in the driver's seat DRV of the vehicle 1 And is connected to a control module 150 mounted on a main control box (not shown) of the vehicle 1 so as to transmit and receive a control signal, which is designed to drive the drive unit 10 using electricity of the vehicle 1 . That is, the control panel CTR is designed to merely control the driving of the driving unit 10, and the control module 150 mounted on the main control box (not shown) .

Particularly, the drive unit 10 is installed so as to be able to be lifted so as to be housed in a storage chamber CHM formed inside the vehicle 1 through the upper surface of the vehicle 1. [

To this end, a slit (not shown) is formed on both sides of the housing chamber CHM and a joint piece JNT protruding from both sides of the support plate 12 constituting the drive unit 10 is inserted into the slit And the joint piece JNT can be moved up and down by the slit.

A screw shaft BSC is screwed to each of the joint pieces JNT and the upper and lower ends of the screw shaft BSC are rotatably fixed by bearings BR.

A driven bevel gear BBV is integrally fixed to each lower end of the screw shaft BSC and each of the driven bevel gears BBV is coupled to a pair of drive bevel gears DBV , And the motor rotation shaft (MRT) is connected to a rotation motor (MOT) fixed inside the vehicle (1).

Therefore, since the receiving plate 12 is raised or lowered according to the rotating direction of the rotating motor MOT, the driving unit 10 including the receiving plate 12 can be used by being raised when necessary, And when it is lowered, it can be safely kept and stored.

In this case, although not shown, a separate cover is provided to cover the upper surface of the opened vehicle 1 when the drive unit 10 is housed, thereby protecting the drive unit 10 when it rains or when the snow comes.

More specifically, the drive unit 10 includes a rotation drive unit 20 as illustrated in FIG.

The rotation driving unit 20 includes a support plate 12 embedded in the housing chamber CHM of the vehicle 1 in the ceiling of the vehicle 1 to be elevated and lowered in the housing chamber CHM, A sub shaft 24 integrally formed with the main shaft 22 and having a larger diameter and a rack 26 formed in the circumferential direction of the sub shaft 24, A pinion 28 coupled to the rack 26 and a rotary motor 30 fixed to the pinion 28 and fixed to the pinion plate 12; A rectangular frame 34 seated on the upper plate 32, a ball screw 36 fixed to the square frame 34 so as to be rotatably rotatable at both ends thereof, A driven gear 38 fixed to one end of the ball screw 36 through the square frame 34, a drive gear 40 gear-coupled to the driven gear 38, A driving motor 42 fixed to the outer surface of the rectangular frame 34 with the gear 40 fixed and fixed to the ball screw 36 so as to be moved in the rotational direction of the ball screw 36 A pair of first and second flow blocks 44a and 44b and a guide groove 46 formed on the inner surface of the rectangular frame 34 facing the rectangular frame 34 and having a predetermined length, And the other end thereof includes a guide bar 48 screwed to both side surfaces of the first and second flow blocks 44a and 44b.

At this time, the main shaft 22 is grooved in a state of being recessed in the center of the upper surface of the receiving plate 12, and is installed uprightly in a state where it is caught under the interposition of bearings in the grooves.

The upper plate 32 is screwed or bolted to the upper surface of the sub shaft 24 through a plurality of screws or bolts.

In addition, the square frame 34 is fastened and fixed to the upper surface of the upper plate 32 by using a plurality of screws or bolts.

Particularly, the first and second flow blocks 44a and 44b should have an upper end protruding higher than the upper surface of the rectangular frame 34, and a rotating rod 48 having the same structure is installed at the center of the projected upper surface, The first and second flow blocks 44a and 44b are rotatably controlled by a rotating rod starting motor 50 having the same structure and provided on the outer surfaces of the first and second flow blocks 44a and 44b. However, such a combination of bevel gears is a well-known structure, and a description thereof will be omitted.

Although the ball screw 36 is not specifically shown in the figure, the screw (spiral) directions of both the left and right sides are reversed from the center of the length, and when rotating, the pair of first and second flow blocks 44a, 44b are gathered and flowed in the form of being opened.

A left eye image camera CAM1 and a right eye image camera CAM2 are fixedly installed on the upper end of the rotation bar 48, respectively.

The present invention having such a configuration is accommodated in the storage chamber CHM before performing the measurement operation, but is raised when the measurement operation is performed.

That is, when housed in the housing chamber CHM, the entire drive unit 10 is lowered as it is, and the entire drive unit 10 is lifted when performing a measurement operation.

When the rotation is required, the main shaft 22 and the sub-shaft 24 can be rotated by rotating the rotation motor 30 under the control of the control panel CTR, The frame 34 can be rotated and the position and direction of the support 30 can be controlled.

As described above, the present invention can easily change the position of the support stand 30, minimizing the trouble during photographing, and is excellent in the storage stability, so that it can be stored safely when not being measured.

In addition, since the rotation rods 48 can be individually rotated through the rotation shaft starting motor 50, the rotational drive of the left eye image camera CAM1 and the right eye image camera CAM2 can be individually controlled, In various directions in various directions.

In addition, since the driving unit 10 according to the present invention has a long period of time in which the driving unit 10 is kept exposed to the outside and has a high probability of meeting the snow and rain according to the weather condition, it is preferable that the driving unit 10 is coated with a corrosion- Do.

The corrosion-resistant material according to the present invention comprises 15 wt% of an inorganic binder in which Si (OH) ₄ monomer is dispersed, 25 wt% of colloidal silica, 30 wt% of a modified nano- And the remaining antimony tin compound.

At this time, the inorganic binder maintains a sufficiently dispersed state of the Si (OH) ₄ monomer, and a silicon alkoxide is used for this purpose. If the amount of the inorganic binder exceeds or falls below the above range, the functional nanomaterial is difficult to manifest and the coating layer is deteriorated.

In this case, TEOS (Tetraethylorthosilicate) or TMOS (Tetramethylorthosilicate) can be used as the silicon alkoxide. Since TEOS is ethanol and TMOS is produced as a by-product after the hydrolysis reaction, TEOS is used in consideration of environment and workers' hygiene desirable.

Colloidal silica (Ludox HS-30) preferably has a particle size of 15 nm or less and is added for pH control. Since the water-soluble inorganic binder has a pH of about 3, colloidal silica having a pH of about 10 is preferably added in an appropriate amount, To 25% by weight, so that the pH of the mixture is maintained at about 7.

In addition, the functional nanomaterial can be obtained by preparing a sulfur dispersion by using ultrasonic waves, adding a surfactant to the dispersion, and electrolyzing the dispersion and the surfactant mixture to obtain a sulfur nano-aqueous solution, And a dicyclopentadiene (DCPD) type modifier is used as a sulfur modifier. This is to increase resistance to salt.

Finally, the antimony tin compound is a material used for heat shielding, and 30% by weight of distilled water and 30% by weight of 1,4-butanediol are mixed and adjusted to pH = 11 using caustic soda (NaOH). 37% by weight of tin tetrachloride (SnCl ₄ .5H ₂ O) and 3% by weight of antimony trichloride (SbCl ₃ ) were added thereto and dispersed by ultrasonic waves so as to be uniformly mixed.

The thus prepared mixture is put into an autoclave and heated to 300 ° C at a rate of 5 ° C / min in a nitrogen atmosphere for crystallization, and then maintained for 4 hours to prepare a 20 nm antimony tin compound.

100: mobile mapping device 200: communication module
300: Update module 400: Aerial photograph database
500: Data processing module

Claims (1)

An image capture module for acquiring image information from a plurality of cameras when building three-dimensional spatial information using an aerial photograph and a mobile mapping system; A GPS receiving module for receiving GPS information from a satellite and obtaining current position information of the camera; An inertia measurement module for obtaining horizontal information of the camera using a plurality of sensors; An image processing module for correcting the image information based on the image information, the current position information, and the horizontal information; A control module for controlling the image information, current position information and horizontal information to be transmitted to the image processing module; And a buffer for storing image information; An aerial photograph database for receiving and storing the image information from the mobile mapping device or receiving and storing aerial photograph data from an external database; A data processing module for determining a target object by comparing the image information obtained from the mobile mapping device with the aerial photograph data obtained from the aerial photograph database, and performing three-dimensional space modeling using the determined target object information; And a communication module for receiving request information for a spatial modeling service from a user, transmitting the request information to the mobile mapping device, the aerial photograph database, and the data processing module, and transmitting the three-dimensional spatial data obtained from the data processing module to a user; Wherein the image processing module detects a curve from the image information received from the captured image acquisition module to set a first correction group, removes the first correction group from the image information, Sets the lines out of the threshold value from the center point on the three-dimensional coordinates as the second correction group from the image information from which the group is removed, removes the second correction group from the image information from which the first correction group is removed, silver

(Where am denotes the length of the waterline at the center of the curve at the center of the image, R denotes the length of the image diagonal, m = 1 to M, M denotes the number of lines, and ψ denotes the user parameter) A filtering module to be obtained; A parameter extracting module for extracting a parameter indicating a degree of warping of the image based on the image information from which the first correction group and the second correction group have been removed; And an image correction module for performing correction of the image information using the parameters, the system comprising:
A control panel CTR is installed in the driver's seat DRV of the vehicle 1 in communication with the control module 150 which is a main controller and the control panel CTR is installed in the driver's seat DRV of the vehicle 1, And the drive unit 10 is elevably installed so as to be housed in a storage chamber CHM formed inside the vehicle 1 through the upper surface of the vehicle 1; A main shaft 22 fixed to the bearing plate 12 by bearings, a support shaft 12 fixedly mounted on the support plate 12, A circular sub shaft 24 integrally formed with the main shaft 22 and having a circular cross section and having a diameter larger than that of the main shaft 22 and a rack 26 formed in the circumferential direction of the sub shaft 24 A pinion 28 coupled to the rack 26 and a rotary motor 30 fixed to the pinion 28 and fixed to the support plate 12; A rectangular frame 34 seated on the upper plate 32 and fixed to the frame so that both ends of the rectangular frame 34 are rotatable through the square frame 34, A ball screw 36 which is screwed in an opposite direction and a ball screw 36 which is fixed to one end of the square frame 34 of the ball screw 36 A drive gear 40 fixed to the outer surface of one side of the rectangular frame 34 and fixed to the drive gear 40; First and second flow blocks 44a and 44b that are inserted into the ball screw 36 in a state of being engaged with the ball screw 36 and flow in a manner of gathering or spreading according to the rotation direction of the ball screw 36, A guide groove 46 having one end fixed to the guide groove 46 and the other end screwed on both sides of the first and second flow blocks 44a and 44b; A rotary bar start motor 50 provided on each of the outer surfaces of the first and second flow blocks 44a and 44b and a second rotary block 44 installed on the first and second flow blocks 44a and 44b, And a rotation bar 48 which is rotatably controlled by a starter motor 50 and has upper left and lower right image cameras CAM1 and CAM2, 3D spatial information building system using MMS and multidirectional oblique aerial photograph.

Images