KR101607078B1 - Method of measuring curvature and mapping of underground pipeline using vision - Google Patents
Method of measuring curvature and mapping of underground pipeline using vision Download PDFInfo
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- KR101607078B1 KR101607078B1 KR1020150058858A KR20150058858A KR101607078B1 KR 101607078 B1 KR101607078 B1 KR 101607078B1 KR 1020150058858 A KR1020150058858 A KR 1020150058858A KR 20150058858 A KR20150058858 A KR 20150058858A KR 101607078 B1 KR101607078 B1 KR 101607078B1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/255—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures for measuring radius of curvature
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
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Abstract
The present invention relates to a method of measuring a curvature of an inside of a pipe by using an internal image of an underground pipe, judging the presence or absence of a defect, and displaying the 3D map.
The present invention can effectively and systematically analyze the shape of a pipeline in a special environment using a robot control research and a computer vision that can freely move the inspection equipment into a pipeline, In addition, by implementing the technique of displaying the measured data using the 3D map using the internal image acquired by the camera, the operator can understand the exact shape of the pipe, for example, the diameter, the curvature, and the defect position Provided is a curvature measurement and mapping method of an underground conduit using a vision that can increase the efficiency of overall operation related to maintenance of a conduit, etc. by displaying it easily.
Description
The present invention relates to a method of measuring and mapping a curvature of an underground channel using a vision, and more particularly, to a method of measuring a curvature of an inner channel of an underground channel and determining the presence or absence of a defect and displaying the 3D image.
Recently, facilities such as power and communication network have been changed from ground to underground (underground) pipeline installation due to the problem of beauty and stability.
In general, when the pipe is buried, there are many problems in stability due to the damage of the existing installation, the pipe breakage due to the ground change, and the defect caused by the aging corrosion.
Such pipe defects are the main cause of accidents, so efficient management is required for installation and maintenance, but it is difficult to access underground facilities and economic problems arise during excavation.
For example, as the urbanization progresses rapidly, the installation of water supply and drainage pipes, city gas supply pipes, oil transfer pipes, electric power and communication lines are increasing rapidly in order to expand infrastructure such as electricity, communication, and water supply and sewage.
These facilities are mostly buried in the ground due to the protection of the aesthetics and facilities. However, since the information about the location and depth of the underground facilities is not accumulated, it is difficult to visually ascertain its position and condition, making maintenance of the underground facilities difficult.
Also, when installing a new underground buried object or building, it takes time and expense to accurately grasp the location of the existing underground object, and it is also dangerous to the safety of the worker due to destruction of existing underground objects during the construction.
In other words, if there is a lot of pipelines buried in a densely populated area, failure to understand the location and condition of pipelines can lead to accidents.
In order to prepare for this, a guide plate passing through a communication cable line or a gas supply pipe is displayed on the road, but accurate information on the position and depth of the guide plate is inevitably dependent on existing design schemes.
In order to solve these problems, the importance of nondestructive inspection without revealing underground facilities has increased.
For non-destructive testing, it is necessary to develop a system that can inspect the test equipment by injecting it into the pipeline.
In addition, since water or foreign substances are contained in the pipe during inspection, it is required to have a technology capable of inspection in a special environment.
Usually, cars are used mainly in the form of robots that can be remotely controlled for exploring and inspecting the inside of the pipelines. Such a self-propelled car is equipped with a camera such as a camera to shoot the inside of the pipeline, It is possible to determine whether maintenance or replacement is necessary.
However, in most cases, since the image data obtained by the operator is determined by the operator's experience, it is not possible to perform more objective and systematic analysis and evaluation, resulting in a disadvantage that the efficiency with respect to the maintenance of the pipeline is inferior .
In other words, it is reliable in that it can visually confirm the photographed data photographed by the camera. However, it can be confirmed that only the damaged part of the pipeline can be confirmed, and the damage position can not be confirmed, and the change of the pipe diameter and the legality of the pipe network ) Can not be confirmed.
Accordingly, the present invention has been made in view of the above points, and it is possible to effectively and systematically analyze the shape of the piping in a special environment by using the robot control research and the computer vision that can freely move the inspection equipment into the pipeline. And a method of measuring and mapping a curvature of an underground channel using a vision that enables proper maintenance through grasping such a channel shape.
It is another object of the present invention to provide a method of displaying a 3D map of data obtained by using a pipe internal image acquired by a camera, thereby enabling the operator to accurately display the pipe shape, for example, diameter, curvature, The present invention provides a method of measuring and mapping a curvature of an underground channel by using a vision that can improve the efficiency of the overall operation related to the maintenance and the like of the channel.
In order to achieve the above object, a curvature measurement and mapping method of an underground channel using a vision provided by the present invention has the following features.
The method of measuring and mapping the curvature of an underground channel using the vision is a method of measuring and mapping a curvature using an image captured inside a pipeline in which a mountain and a bone are repeated, A second step of selecting a candidate group of the diameter line by measuring a Gaussian distribution of the brightness of the transmitted pipe internal image and fitting the selected diameter line candidate group into an ideal circle to select a final diameter circle, A third step of calculating the curvature of the pipe using the center coordinates of the diameter circle collected while moving the camera while computing the center coordinates of the finally selected diameter circle and the third step of calculating the mapping technique using the 3D graphic API The final diameter circle is displayed on the screen in a circular form, and the pipe shape obtained from the calculated curvature is displayed on the screen. And a system.
In the second step, the Gaussian distribution map is obtained by plotting the distribution of brightness of the channel image, and the inner diameter of the spot having the maximum brightness in the Gaussian distribution map is measured to display the diameter line candidate group on the screen.
In the second step, noise may be removed using a morphology image processing technique among candidate groups of diameter lines, and adjacent lines may be connected to select a final diameter line candidate group.
In the second step, in order to fit the ideal circle from the diameter line candidate group, the outline coordinate value obtained from the diameter line candidate group may be substituted into the least squares method to form an ideal circle.
As a preferred embodiment, the second step may further include a step of selecting a final diameter circle using an intersection area with an already known circle through an ideal circle and calibration.
As a preferred embodiment, in the third step, as the camera moves, the collected center coordinates may be normalized at regular intervals to calculate the curvature of the channel.
The curvature measurement and mapping method of the underground channel using the vision provided by the present invention has the following effects.
First, the shape of the inside of the underground pipe is analyzed by using only the image. Especially, the diameter and the curvature of the pipe are measured by using the image inside the underground pipe, the existence of the defect is determined, So that it is possible to grasp accurately and perform appropriate maintenance.
Second, the accurate shape of the pipe diameter, shape, and defect position is displayed on the screen together with the numerical value and the like so that the operator can easily understand the pipe, thereby improving the efficiency of the overall work related to maintenance and the like of the pipe.
Third, by applying a vision system, a new system for accurately analyzing and mapping the shape of diameter, curvature, and defect position of the ground and underground pipelines can be constructed. This system can be applied not only to domestic market but also to overseas market. Can be variously secured.
1 is a block diagram of an image acquisition system used in a curvature measurement and mapping method of an underground channel using a vision according to an embodiment of the present invention
FIG. 2 is a schematic diagram illustrating a method of measuring a curvature of an underground channel using a vision according to an exemplary embodiment of the present invention,
FIG. 3A is a graph showing a Gaussian distribution diagram used in a curvature measurement and mapping method of an underground channel by using a vision according to an exemplary embodiment of the present invention.
FIG. 3B is a graph showing a distribution of brightness values in a curvature measurement and mapping method of an underground channel using a vision according to an exemplary embodiment of the present invention
FIG. 4 is a diagram illustrating a line detection image using a Gaussian distribution used in a curvature measurement and mapping method of an underground channel using a vision according to an embodiment of the present invention.
FIG. 5 is a block diagram illustrating a noise canceling and line connection image used in a curvature measurement and mapping method of an underground channel using a vision according to an exemplary embodiment of the present invention.
6A is an ideal circular view of a focusing area used in a curvature measurement and mapping method of an underground channel using a vision according to an embodiment of the present invention.
6B is a schematic view illustrating a method for detecting a final circle in a curvature measurement and mapping method of an underground channel by using a vision according to an embodiment of the present invention
FIG. 7 is a flowchart illustrating a method for measuring a curvature of an underground channel using a vision according to an exemplary embodiment of the present invention,
FIG. 8 is a schematic view illustrating a circular pipe model used in a curvature measurement and mapping method of an underground channel by using a vision according to an embodiment of the present invention.
9 is a view showing an SW main screen used in a curvature measurement and mapping method of an underground channel using a vision according to an embodiment of the present invention
Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.
The curvature measurement and mapping method of the underground channel using the vision of the present invention is a technique of analyzing the shape of the underground channel using only the image, for example, measuring the diameter and curvature of the channel using the image inside the underground channel, And a mapping technique for displaying the diameter and curvature of the pipe inside the tube thus measured and the position of the defect on the screen.
Therefore, the pipe shape can be easily grasped through the method proposed by the present invention, and maintenance that is suitable for the pipeline can be efficiently performed.
1 is a block diagram of an image acquisition system used in a curvature measurement and mapping method of an underground channel using a vision according to an embodiment of the present invention.
As shown in FIG. 1, the image acquisition system is a system for receiving images acquired by a camera and analyzing the images using image analysis software. The system includes a
In this system, the pipe diameter and curvature are measured through the pipe internal image, that is, the pipe diameter and the curvature are measured using only the image inputted through the camera, and the mapping technique for displaying the measurement data allows the operator to understand the diameter and curvature So that it is easy to display.
The computer device displays an image received from a camera on a screen, analyzes the diameter, curvature, and the like, maps the image with its own software, and displays the result on a screen or stores the result on a database do.
That is, when the image of the pipe taken by the camera is inputted, the computer device can measure, calculate and map the diameter and curvature of the pipe using only the input image, and display the result on the screen.
The frame grabber is an electronic device for capturing a digital frame from an analog video signal or a digital video stream. The frame grabber is used as a component of a computer vision system. In such a component, a video frame is extracted in a digital format, And stored and transmitted in a circular or compressed format.
In addition, the camera can be transported by various known methods such as a method using a self-powered truck or a towing method using a cable.
In the case of such an image acquisition system, it can be usefully applied to the analysis of the shape of the channel, which is repeated in the shape of the mountain and the bone, as well as the general channel of the ground and the ground,
A method of generating a 3D map of an underground channel using the image acquisition system, that is, a method of measuring and mapping a curvature of an underground channel using a vision will be described in detail.
In the first step, the inside of the channel is photographed with a camera equipped with an illumination, and the image is transmitted.
For example, a camera equipped with LED (not shown) illumination for a dark internal photographing is connected to a frame grabber, and the internal image of the pipe taken by the camera is transmitted to a computer device.
In the second step, the Gaussian distribution of the brightness of the transmitted pipe image is measured to select the candidate group of the diameter line, and the selected diameter line candidate group is fitted to the ideal circle to select the final diameter circle.
That is, as shown in FIG. 2, it can be seen that the internal image of the pipeline is repeatedly brightened and darkened at the spiral mountain and the valley portion.
If the distribution of brightness is plotted, a Gaussian distribution diagram as shown in FIG. 3 can be obtained.
For example, in order to obtain a Gaussian distribution diagram by plotting the distribution of the brightness, a Gaussian sampler that detects an edge is usually used as a second-order differential operator.
In particular, according to the present invention, it is possible to predict that the pixel distribution of the channel image itself is composed of mountains and corners, and accurate values can be obtained when detecting an edge using a Gaussian distribution rather than a general edge detector.
That is, the edge detection using the Gaussian distribution can obtain the most accurate value in the channel image of the form of the object of the present invention.
In the Gaussian distribution diagram of FIG. 3A, the place where the brightness becomes maximum like m 1 and m 2 becomes the line for measuring the inner diameter, and the distribution of the brightness is measured to show the candidate group of the diameter line as shown in FIG.
In the second step, the Gaussian distribution is obtained by plotting the distribution of the luminance of the channel image, and the inner diameter of the region where the brightness is maximized in the Gaussian distribution chart is measured to display the diameter line candidate group as shown in FIG. 4 .
For example, assuming that an imaginary line is drawn diagonally from the center of the image in the example 1 of Fig. 3B, the graph of the distribution of the brightness values represented by the line is Example 2.
In the characteristics of the channel image, the bright part can be represented as an acid and the dark part can be represented as a valley, and m 1 and m 2 represent the brightest value among the respective acids.
A red circle can be used to find an edge in a bright part, and a red circle can be used to find an edge in the darkest part. FIG. 4 shows a shape expressed by an edge by finding m 1 and m 2 in a dark part.
At this time, noise is eliminated by using a morphology image processing technique among the candidates of the diameter line, and adjacent lines are connected to each other to select a final diameter line candidate group, and it can be displayed on the screen.
That is, among the candidates of the diameter line, it is possible to generate the corresponding portion (the positions of the blue circles in FIG. 4) and the broken line (the positions of the red circles in FIG. 4) The noise is eliminated by using the morphology image processing technique, and the final diameter line candidates are selected by connecting adjacent lines.
Then, the selected final diameter line candidates are displayed as shown in FIG.
That is, all the lines indicated by the colors in FIG. 5 belong to the candidate group, and FIG. 5 is an image from which noise shown in FIG. 4 is removed.
Particularly, in the second step, in order to fit the ideal circle from the diameter line candidate group, the outline coordinate value obtained from the diameter line candidate group is substituted into the least squares method to form an ideal circle.
Here, the ideal circle refers to a circle expressed by the image when the focus position of the used camera is measured as approximately 15 cm, assuming that the pipe inner diameter is approximately 10 cm in diameter at that position.
For example, the final line is selected by comparing the selected diameter line candidates with the ideal rounds calculated for the diameter measurement.
That is, when the coordinate values of the outline obtained from the selected diameter line candidate group, that is, the outline in the image processing is detected, are the extension lines of the point, and based on the image coordinate values representing the respective points at this time, A circle is formed by using a least square method fitting a virtual circle of each outline of the line candidate group.
A circle forming method by fitting is as follows.
The circle equation is derived by substituting the coordinates of the outline obtained in the general circle equation (1) into the least square method (2).
Run the partial derivative to solve the stigma.
The equation of the partial derivative is as follows.
In the above equation,
Determined through determinants
Where y is the y coordinate of the circle (the y coordinate of the obtained outline) in the original equation, k is the constant of the y coordinate Value, h is a constant value of the x coordinate, and r is the radius of the estimated circle.
FIG. 6A is an ideal circle implemented using values of actually calculated outlines. FIG.
Meanwhile, the second step can further perform a process of selecting a final diameter circle using an intersection area with a known circle through an ideal circle and a calibration.
That is, the method of detecting the final circle can be obtained through the intersection area of the ideal circle extracted from the outline of the percocated Gaussian form and the circle of the focusing area of 10 cm in diameter, which can be known through calibration do.
For example, as shown in FIG. 6B, a virtual circle having a diameter of 10 cm and a diameter of 10 cm at a position 15 cm from the camera, which is the focusing point of the camera image to obtain normalized data, The calibration and display on the coordinate is the circle of the focusing area of 10 cm in diameter obtained through calibration.
When the center of the circle is converted into the collected center coordinates, the intersection point with the fitted circle is displayed. If the size of the fitting circle at the intersection point is indicated by the diameter, the final circle can be obtained.
Fig. 7 is a view of the intersection area O and the obtained circle of diameter.
As a third step, the center coordinates of the finally selected diameter circle are calculated, and the curvature of the pipe is calculated using the coordinates of the center of the diameter circle collected while moving the camera.
That is, the center coordinates of the finally selected line (circle) are calculated and collected for the measurement of the curvature of the channel, and the central coordinates collected as the camera moves are normalized at regular intervals to calculate the curvature of the channel .
For example, since the equation of the fitting source can be obtained through the above equations (1) to (6), the fitting source of the finally selected line is obtained, the center coordinates of the circle are collected, The curvature of the pipe can be obtained by collecting the center of the fitting circle of the pipe.
As a fourth step, a final diameter circle is displayed on a circular screen through a mapping technique using a 3D graphic API, and a pipe shape obtained from the calculated curvature is displayed on the screen.
For example, the fourth step is a mapping step of displaying measurement data. As shown in FIG. 8, a pipeline is mapped using OpenGL, which is one of three-dimensional graphics API (Application Programming Interface) The circular shape is represented by the diameter, and the pipe shape can be displayed by using the calculated center coordinates.
By comparing the pipe shape, the measured pipe diameter value, and the curvature value displayed in the 3D map form with various data at the time of pipe design and construction, it is possible to determine the presence or absence of a defect in the pipe and the position of the defect.
That is, a defect in an underground pipe refers to a case where a diameter changes due to breakage or distortion of a pipe.
It is possible to determine the presence or absence of a defect according to the magnitude of the actual diameter of the pipe to be measured and the magnitude of the measured diameter, record the corresponding position, and display the corresponding defective position as a circle of different colors do.
On the other hand, in the case of the image acquisition system used for the curvature measurement and mapping method of the underground channel by using the vision, it includes software for displaying the real time screen and the measured diameter inside the channel, .
For example, FIG. 9 is a photograph showing an SW main screen used in a curvature measurement and mapping method of an underground channel using a vision according to an embodiment of the present invention, which includes a camera, a serial port, an Excel file path, Software-specific functional items such as path, live, record, close, distance, diameter, etc. are displayed.
Here, each software detailed function item will be described as follows.
1. Camera
The camera item confirms whether the camera is connected or not when the program is executed.
2. Serial Port
Confirm whether serial port connection for distance measurement is confirmed during program execution.
3. Excel File Path
Displays the Excel File path that stores the diameter measurements and center coordinate results.
4. Image File Path
A path for storing an image photographed inside the pipe is displayed.
5. Live (Live)
It is the function to display camera on / off and real time image on the main screen.
6. Record
It is a button to execute image saving after turning on the camera power.
7. Close
It is a program end button.
8. Distance
Measure the distance the camera moves.
9. Diameter
Displays the inner diameter measured by the image.
As described above, in the present invention, a new system for measuring the diameter and curvature of a channel using only the internal image of the underground channel and displaying the measured channel inner diameter and curvature in a 3D map form is constructed to easily grasp the shape of the channel It is possible to efficiently perform maintenance.
10: Camera
20:
30: frame grabber
40: Computer device
Claims (6)
A first step of photographing the inside of the duct by using a camera equipped with a light and transmitting the image;
A second step of selecting a candidate group of the diameter line by measuring a Gaussian distribution of the brightness of the transmitted pipe internal image and selecting a final diameter circle by fitting the selected diameter line candidate group to an ideal circle;
A third step of calculating the curvature of the pipe using the center coordinates of the diameter circle collected while moving the camera while computing the center coordinates of the finally selected diameter circle;
A fourth step of displaying a final diameter circle as a circle on a screen through a mapping technique using a 3D graphic API and displaying a pipe shape obtained through a calculated curvature on a screen;
And measuring the curvature of the ground channel.
The second step is to visualize the distribution of brightness of the channel image to obtain a Gaussian distribution map, measure the inner diameter of the area where the brightness is maximum in the Gaussian distribution map, and display the diameter line candidate group on the screen. Method of measuring and mapping the curvature of a used underground channel.
The second step selects the final diameter line candidates by removing the noise using the morphology image processing technique among the candidate groups of the diameter lines and connecting adjacent lines to each other to select the curvature measurement and mapping method of the underground channel by using the vision .
In the second step, an outline coordinate value obtained from the diameter line candidate group is fitted to the least squares method to fit the ideal circle from the diameter line candidate group to form an ideal circle, and the curvature measurement and mapping method using the vision .
Wherein the second step further comprises the step of selecting a final diameter circle by using an intersection area with a known circle through an ideal circle and a calibration, and a method for measuring and mapping a curvature of an underground pipe using the vision.
And calculating a curvature of the channel by normalizing the collected center coordinates at regular intervals as the camera moves in a third step.
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| KR101857961B1 (en) * | 2016-10-04 | 2018-05-24 | 계명대학교 산학협력단 | Sinkhole detection system and method using a drone-based thermal camera and image processing |
| CN108798637A (en) * | 2018-06-07 | 2018-11-13 | 山东科技大学 | Detection method and its propulsion device are pried through in the pinpoint drilling of one kind |
| KR20200087330A (en) * | 2018-12-28 | 2020-07-21 | 네이버시스템(주) | State information analysis and modelling method of sewerage pipe |
| CN112163309A (en) * | 2020-07-27 | 2021-01-01 | 扬州市职业大学(扬州市广播电视大学) | Method for quickly extracting space circle center of single plane circular image |
| CN112989527A (en) * | 2021-01-28 | 2021-06-18 | 上海淀山勘测有限公司 | Method for quickly mapping underground pipeline |
| CN114441539A (en) * | 2020-11-03 | 2022-05-06 | 南京北控工程检测咨询有限公司 | Water supply and drainage pipeline detection system and detection method |
| KR20220075742A (en) * | 2020-11-30 | 2022-06-08 | 한국로봇융합연구원 | An inspection robot of pipe and operating method of the same |
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| KR101857961B1 (en) * | 2016-10-04 | 2018-05-24 | 계명대학교 산학협력단 | Sinkhole detection system and method using a drone-based thermal camera and image processing |
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| CN114441539A (en) * | 2020-11-03 | 2022-05-06 | 南京北控工程检测咨询有限公司 | Water supply and drainage pipeline detection system and detection method |
| KR20220075742A (en) * | 2020-11-30 | 2022-06-08 | 한국로봇융합연구원 | An inspection robot of pipe and operating method of the same |
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| CN112989527A (en) * | 2021-01-28 | 2021-06-18 | 上海淀山勘测有限公司 | Method for quickly mapping underground pipeline |
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