CN113269713B - Intelligent recognition method and determination device for tunnel face underground water outlet form - Google Patents
Intelligent recognition method and determination device for tunnel face underground water outlet form Download PDFInfo
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Abstract
The application provides an intelligent identification method and a determination device for a tunnel face underground water outlet form, and belongs to the field of tunnels and underground engineering. The tunnel face groundwater outlet form intelligent identification method and the determination device extract each frame of image in the video based on the video splitting technology, and the extracted images are numbered according to the time sequence; based on an image processing technology, carrying out gray level processing on each extracted frame image; converting the gray level image into binary images of a moving area and a static area based on a video processing method; and intelligently identifying the underground water state based on the video processing result and the underground water flow characteristics. The method has the advantages that subjective factor influence is less introduced, the technical problem of low recognition accuracy of the traditional method is solved, and the problem of low efficiency of traditional manual judgment is solved.
Description
Technical Field
The application relates to the field of tunnels and underground engineering, in particular to an intelligent identification method and a determination device for a tunnel face underground water outlet form.
Background
Since 2010, the human beings have pulled open the curtain of the fourth industrial revolution, and the design concept and the construction technology of the tunnel and the underground engineering gradually develop towards the direction of artificial intelligence (AI technology). With the continuous innovation of design concept and construction process, the tunnel engineering gradually develops towards mechanization, informatization and intellectualization. How to accurately, less people and nobody acquire the surrounding rock parameters becomes the key point of research on intelligent construction of the current tunnel and underground engineering. The water outlet form of the tunnel face can better reflect the magnitude of the underground water permeability of the tunnel face, and further influences the stability of the tunnel face and the design and construction of a tunnel supporting structure. In addition, different face water outlet forms have great influence on the correction grading of the face and the correction of the basic quality index BQ of the surrounding rock.
Therefore, the method for efficiently and accurately judging the tunnel face underground water outlet form has great significance for guiding the design and construction of tunnels and underground engineering. At present, the underground water state identification method still stays at the technical level of the traditional manual interpretation, the water outlet form of the tunnel face is qualitatively interpreted through naked eyes according to the water outlet condition of the tunnel face exposed after blasting, and then the underground water level of the tunnel face is further determined.
Disclosure of Invention
In view of this, the embodiment of the application provides an intelligent identification method and a determination device for a tunnel face groundwater outlet form, which aim at intellectualization and accuracy of groundwater state identification, guide tunnel engineering design and construction, and ensure that the tunnel engineering construction safety plays a key role.
In a first aspect, the present embodiment provides a method for intelligently identifying a tunnel face groundwater outlet form, including
Collecting a video at a groundwater outlet;
extracting each frame of image of the video, numbering and storing each frame of image according to the time sequence of the photos;
carrying out gray level processing on each extracted frame image;
processing the video, determining a background image in the recombined video, dividing a moving area and a static area in the background image into 2 types, and marking pixel points of the moving area and the static area by using 1 and 0 respectively;
carrying out image processing based on the classified binary images of the motion area and the static area, and extracting physical characteristics of underground water;
based on the video processing result and the underground water flowing characteristics, intelligently and qualitatively identifying the underground water state;
the intelligent qualitative identification of the underground water state comprises identification of a water outlet form, identification of the area of a surface water outlet area and identification of a water outlet position.
With reference to the embodiments of the first aspect, in some embodiments, the collecting the video at the groundwater outlet specifically includes:
2 high-definition cameras in front view and side view are respectively arranged at an underground water outlet;
and respectively recording the distance between the front-view camera and the side-view camera from the water outlet, and the focal length and resolution information of the cameras.
With reference to the embodiments of the first aspect, in some embodiments, the tunnel face groundwater outlet form is qualitatively divided into anhydrous, contact type effluent and non-contact type effluent according to the flow form of groundwater at the water outlet, and if the processing result of the video acquired by the front-view camera and the video acquired by the side-view camera indicates that both the video acquisition areas are static areas, the tunnel face groundwater outlet form is anhydrous; if the videos collected by the front-view camera and the videos collected by the side-view camera are processed, the video processing result collected by the front-view camera indicates that a motion area exists in the video collecting area, and the video processing result collected by the side-view camera indicates that the motion area and the video collecting area are static areas, the underground water outlet form of the tunnel face is contact type water outlet; and if the videos collected by the front-view camera and the side-view camera are processed, and if the processed results show that a motion area exists in the video collection area, the underground water outlet form of the tunnel face is non-contact water outlet. On the basis of contact type water outlet judgment, connected domain detection is carried out on the processing result of the video and geometric coordinates of the mass center of the connected domain are counted, if the maximum distance of the mass center of different connected domains in the same video is larger than a set threshold value, discontinuous water outlet is judged, otherwise, continuous water outlet is judged.
With reference to the embodiments of the first aspect, in some embodiments, if the water outlet state is a contact type or a non-contact type, the method for calculating the surface water outlet area is as follows:
S＝n i ×A
in the formula: s-area of water outlet (m) 2 )；
n i Acquiring the number of pixels with the gray value of 255 in a video identification result graph by the front-view camera;
a-actual area (m) represented by a single pixel 2 )；
If the outlet form of the underground water is contact or non-contact, determining the position of the water outlet, wherein the specific determination method comprises the following steps:
constructing a local coordinate system by taking a lower left corner pixel point in a video collected by a front-view camera as a coordinate origin, taking the width direction of each frame image of the front-view video as an X axis, taking the height direction as a Y axis and taking the width direction of each frame image of the side-view video as a Z axis;
recording local coordinates of pixel points with the gray scale value of 255 in videos collected by the front-view camera and the side-view camera based on the constructed local coordinate system;
and if the water outlet is judged to be in a contact type, according to the video processing result acquired by the front-view camera, the local coordinate of the pixel point with the maximum Y coordinate in the pixel points with the gray value of 255 is used for representing the water outlet position, and if the water outlet is judged to be in a non-contact type, according to the video processing result acquired by the side-view camera, the local coordinate of the pixel point with the minimum Z coordinate in the pixel points with the gray value of 255 is used for representing the water outlet position. With reference to the embodiments of the first aspect, in some embodiments, the collecting the video at the groundwater outlet specifically includes:
2 high-definition cameras in front view and side view are respectively arranged at an underground water outlet;
and respectively recording the distance between the front-view camera and the side-view camera from the water outlet, the focal length of the camera and the resolution information.
With reference to the embodiment of the first aspect, in some embodiments, the grayscale processing is performed on each extracted frame image, specifically:
converting color images in the video into gray images based on RGB values, HSI values, HSV values and the like of each frame of image;
and (4) carrying out segmentation, enhancement and sharpening processing on the gray level image based on an image processing technology, and storing.
With reference to the embodiments of the first aspect, in some embodiments, processing a video, determining a background image in a reconstructed video, dividing a moving area and a static area in the background image into 2 types, and marking pixel points of the moving area and the static area with 1 and 0 respectively is specifically:
based on a video recombination technology, recombining the stored gray processing images into a gray video according to a time sequence;
determining a background image in the recombined video based on video processing methods such as background subtraction, background enhancement and the like, and simultaneously dividing a moving area and a static area in the background image into 2 types;
and marking the pixel points of the motion area and the static area by 1 and 0 respectively based on the classification result after video processing.
In some embodiments, in combination with an embodiment of the first aspect, the image processing is performed based on a classification binary map of moving and stationary regions, extracting groundwater physical features, including
Converting the background image into a binary image based on the moving area and the static area classification labels;
based on the classification binary image of the moving and static areas and an image processing technology, the brightness, the appearance and the color visual characteristics, the size, the mass center, the movement mode, the area and the frequency domain physical characteristics of the underground water flow are extracted.
In a second aspect, the present application provides an underground water discharge form determination apparatus comprising
The acquisition module is used for acquiring videos at the position of the underground water outlet;
the video splitting module is used for extracting each frame of image of the video, numbering and storing each frame of image according to the time sequence of the photos;
the image processing module is used for carrying out gray processing on each extracted frame image;
the video processing module is used for processing the video, determining a background image in the recombined video, dividing a moving area and a static area in the background image into 2 types, and marking pixel points of the moving area and the static area by 1 and 0 respectively;
the extraction module is used for carrying out image processing based on the classified binary image of the moving and static areas and extracting the physical characteristics of underground water;
the identification module is used for intelligently and qualitatively identifying the underground water state based on the video processing result and the underground water flow characteristics;
the intelligent qualitative identification of the underground water state comprises identification of a water outlet form, identification of the area of a surface water outlet area and identification of a water outlet position.
In a third aspect, the present application provides an electronic device, comprising:
one or more processors;
storage means for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors realize the intelligent recognition method for the tunnel face groundwater outlet form.
In a fourth aspect, the present application provides a computer-readable medium, on which a computer program is stored, where the program, when executed by a processor, implements the intelligent recognition method for the form of groundwater outlet from the tunnel face as described above.
The beneficial effects of the invention are: extracting each frame of image in the video based on a video splitting technology, and numbering the extracted images according to a time sequence; based on an image processing technology, carrying out gray level processing on each extracted frame image; converting the gray level image into binary images of a moving area and a static area based on a video processing method; and intelligently identifying the underground water state based on the video processing result and the underground water flow characteristics. The method has the advantages that subjective factor influence is less introduced, the technical problem of low recognition accuracy of the traditional method is solved, and the problem of low efficiency of traditional manual judgment is solved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some examples of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also derive other related drawings based on these drawings without inventive effort.
FIG. 1 is a flowchart of an intelligent recognition method for a tunnel face groundwater outlet form provided by an embodiment of the application;
FIG. 2 is an original image of an end frame of a forward looking video in water inrush provided by an embodiment of the application;
FIG. 3 is a raw image of a water-inrush side view video termination frame provided by an embodiment of the present application;
fig. 4 is a grayscale image of an original image of an inrush front view video end frame after RGB values and gray values are converted according to an embodiment of the present application;
fig. 5 is a gray image of an original image of a water-inrush side-view video termination frame after RGB values and gray values are converted according to an embodiment of the present disclosure;
FIG. 6 is an image of a gray level image of a surge orthophoto video termination frame provided by an embodiment of the present application after further processing such as image enhancement and sharpening;
FIG. 7 is an image of a water-inrush side view video termination frame grayscale image provided by an embodiment of the present application after further processing such as image enhancement and sharpening;
FIG. 8 is a binary image of a water gushing orthographic video used to distinguish between moving and still regions provided by embodiments of the present application;
FIG. 9 is a binary image of a water gushing side view video for distinguishing moving and static areas provided by embodiments of the present application;
FIG. 10 is a schematic illustration of a local coordinate system of camera placement and construction provided in a real-time example of the present application;
fig. 11 is a schematic diagram of the structure of a groundwater condition determination device according to an embodiment of the present application.
Fig. 12 is a schematic diagram of a basic structure of an electronic device provided in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings of the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
In the description of the present invention, it should be understood that the terms "original image", "front-view video", "side-view video", "grayscale image", "initial frame", "end frame", "front-view original image", "side-view original image", etc. indicate that the terms of representative images and sequences in the video are based on the representative images and sequence relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the equipment or elements referred to must have representative images and sequences, and therefore, should not be construed as limiting the invention.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the present invention, unless otherwise explicitly stated or limited, the terms "mounted," "connected," "fixed," and the like are to be construed broadly, e.g., as being permanently connected, detachably connected, or integral; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood according to specific situations by those of ordinary skill in the art.
Examples
The fourth industrial revolution takes the place of the whole world, the development of emerging industries such as internet of things, big data, artificial intelligence and the like is accelerated, and the tunnel engineering construction technology gradually develops towards mechanization, informatization and intellectualization. The underground water state is efficiently identified, so that the key effect is played on guiding the design and construction of tunnel engineering, and ensuring the construction and operation safety.
Therefore, through long-term research, the inventor provides an intelligent identification method and a determination device for the underground water outlet form of the tunnel face, and aims to improve the construction level of tunnels in China and initiate a new mode of construction and operation of high-quality, high-efficiency, few people and no people for tunnel engineering in China.
Fig. 1 shows a flowchart of an embodiment of an intelligent recognition method for a tunnel face groundwater outlet form according to the disclosure. Referring to fig. 1, the intelligent recognition method for the tunnel face groundwater outlet form is used in the field of tunnel engineering, and recognizes the groundwater state in the construction stage.
Referring to fig. 1, the intelligent identification method for the tunnel face groundwater outlet form includes the following steps:
Here, step 101 is specifically: and 2 high-definition cameras in front view and side view are respectively arranged at the underground water outlet.
And respectively recording the distance between the front-view camera and the side-view camera from the water outlet, the focal length of the camera, the resolution ratio and other information.
And 102, extracting each frame of image of the video, numbering each frame of image according to the time sequence of the pictures and storing the images.
Here, step 102 specifically includes
Extracting each frame of image in the collected video from the front-view camera and the side-view camera based on a video splitting technology;
and numbering and storing the extracted frame images according to the time sequence.
In a specific embodiment, a water inrush phenomenon occurs in a tunnel surrounding rock, each frame of original image is extracted through a video splitting technology, the front-view video termination frame of original image is shown in fig. 2, and the side-view video termination frame of original image is shown in fig. 3.
And 103, carrying out gray scale processing on each extracted frame image.
And converting the color images in the front-view video and the side-view video into gray images based on the RGB value, HSI value, HSV value and the like of each frame of image.
And (3) segmenting, enhancing and sharpening the gray level image based on an image processing technology, and storing.
And preliminarily converting the color image in the video into a gray image based on the RGB value, HSI value, HSV value and other calculation methods of each frame of image.
Wherein the gray scale image of the end frame image preliminary conversion in the front view video is shown in fig. 4; the gray-scale image of the end frame image preliminary conversion in the side-view video is shown in fig. 5; an image of the end frame gray image in the front-view video after further processing of image enhancement and sharpening is shown in fig. 6; the image of the end frame gray scale image in the side view video after further processing by image enhancement and sharpening is shown in fig. 7.
And 104, processing the video, determining a background image in the recombined video, dividing a motion area and a static area in the background image into 2 types, and marking pixel points of the motion area and the static area by 1 and 0 respectively.
Here, step 104 is specifically as follows:
based on a video recombination technology, recombining the stored gray processing images into a gray video according to a time sequence;
and determining a background image in the recombined video based on video processing methods such as background subtraction, background enhancement and the like, and simultaneously dividing a moving area and a static area in the background image into 2 types. The background subtraction can use inter-frame difference, mean value accumulation, gaussian modeling, and gaussian mixture modeling.
And marking the pixel points of the motion area and the static area by 1 and 0 respectively based on the classification result after video processing.
And 105, carrying out image processing based on the classified binary image of the motion and static areas, and extracting the physical characteristics of the underground water.
Based on the moving and static area classification labels, the background image may be converted to a binary image, matrix, or the like. Wherein the binary image is used to distinguish between moving and still regions. The binarization result of the end frame of the front-view video is shown in FIG. 8; the side view video termination frame binarization result is shown in fig. 9.
And extracting the visual characteristics such as brightness, appearance, color and the like of groundwater flow, and the physical characteristics such as size, mass center, motion mode, area and frequency domain.
And 106, intelligently and qualitatively identifying the underground water state based on the video processing result and the underground water flow characteristics.
The intelligent qualitative identification of the underground water state comprises identification of a water outlet form (including no water, contact water outlet and non-contact water outlet), the surface water outlet area, the water outlet position and the like.
According to the flowing form of underground water at a water outlet, the underground water outlet form of the tunnel face can be qualitatively divided into 3 states: water-free, contact-type water outlet and non-contact-type water outlet. The specific interpretation method is as follows:
(1) Without water
And (3) processing the video collected by the front-view camera and the video collected by the side-view camera, wherein if the processing results show that the video collecting areas are static areas (namely, waterless areas), no underground water is leaked.
(2) Contact type water outlet
And processing the video collected by the front-view camera and the video collected by the side-view camera, wherein if the video processing result collected by the front-view camera shows that a motion region (namely a water region) exists in the video collecting region, and the video processing result collected by the side-view camera shows that the area of the motion region in the video collecting region is lower than a statistical threshold value, the underground water outlet form of the tunnel face is contact water outlet.
(3) Non-contact water outlet
And (3) processing videos collected by the side-view camera and the side-view camera, wherein if the processed results show that a motion area (namely a water area) exists in the video collection area, the underground water outlet form of the tunnel face is non-contact water outlet.
The surface water-out area calculation method comprises the following steps:
S＝n i ×A
in the formula: s-area of water outlet (m) 2 )；
n i Acquiring the number of pixels with the gray value of 255 in a video identification result graph by the front-view camera;
a-actual area (m) represented by a single pixel 2 )。
If the effluent form of the underground water is contact or non-contact, further judging whether the effluent form is continuous effluent, wherein the specific criterion is as follows:
ΔL≥ε
in the formula: delta L is the maximum centroid distance of a connected domain in the front view video processing result;
ε -maximum centroid threshold;
if the formula is satisfied, the water is further judged to be discharged discontinuously, and if not, the water is discharged continuously.
If the outlet form of the underground water is in a contact type or a non-contact type, determining the position of the water outlet, wherein the specific determination method comprises the following steps:
and taking a lower left corner pixel point in a video collected by a front-view camera as a coordinate origin, taking the width direction of each frame image of the front-view video as an X axis, taking the height direction as a Y axis, and taking the width direction of each frame image of the side-view video as a Z axis, so as to construct a local coordinate system. A schematic diagram of a local coordinate system for camera arrangement and construction is shown in fig. 10;
and recording local coordinates of pixel points with the gray value of 255 in videos collected by the front-view camera and the side-view camera based on the constructed local coordinate system.
(1) Contact type water outlet
If the water outlet is judged to be in contact type, according to a video processing result acquired by the front-view camera, the local coordinate of the pixel point with the maximum Y coordinate in the pixel points with the gray value of 255 is used for representing the water outlet position.
(2) Non-contact water outlet
And if the non-contact type water outlet is judged, according to the video processing result acquired by the side-looking camera, the local coordinate of the pixel point with the minimum Z coordinate in the pixel points with the gray value of 255 is used for representing the position of the water outlet.
The tunnel face groundwater outlet form intelligent identification method is based on a video splitting technology, extracts each frame of image in a video, and numbers the extracted images according to a time sequence; based on an image processing technology, carrying out gray processing on each extracted frame image; converting the gray level image into binary images of a moving area and a static area based on a video processing method; and intelligently and qualitatively identifying the underground water state based on the video processing result and the underground water flowing characteristics. The method has the advantages that subjective factor influence is less introduced, the technical problem that the traditional method is low in identification accuracy is solved, and the problem that the traditional manual judgment is low in efficiency is solved.
In addition, the method creates an intelligent, efficient, few-people and unmanned underground water state intelligent identification new mode, and has high degree of intelligence which is not possessed by the traditional method.
Further, as an implementation of the above-described illustrated method, the present disclosure provides a groundwater status determination apparatus, please refer to fig. 11. The embodiment of the device corresponds to the embodiment of the method shown in fig. 1, and the device can be applied to various electronic devices.
The application further discloses groundwater status determination device includes: the acquisition module 701, the acquisition module 701 is used for acquiring videos at an underground water outlet; the video splitting module 702 is used for extracting each frame of image of the video, numbering each frame of image according to the time sequence of the photos and storing each frame of image; an image processing module 703, where the image processing module 703 is configured to perform gray processing on each extracted frame image; the video processing module 704 is configured to process a video, determine a background image in a reconstructed video, divide a moving area and a static area in the background image into 2 types, and mark pixels of the moving area and the static area with 1 and 0, respectively; an extraction module 705, wherein the extraction module 705 is used for processing images based on the classified binary image of the motion and static areas and extracting the physical characteristics of underground water; an identification module 706, wherein the identification module 706 is used for intelligently and qualitatively identifying the groundwater state based on the video processing result and the groundwater flow characteristics. The intelligent qualitative identification of the underground water state comprises identification of a water outlet form (including no water, contact water outlet and non-contact water outlet), a surface water outlet area, a water outlet position and the like.
According to the flowing form of the underground water at the water outlet, the outlet form of the underground water on the tunnel face can be qualitatively divided into 3 states: water-free, contact-type water outlet and non-contact-type water outlet. The specific interpretation method is as follows:
(1) Without water
And (3) processing the video collected by the front-view camera and the video collected by the side-view camera, wherein if the processing results show that the video collecting areas are static areas (namely, waterless areas), no underground water is leaked.
(2) Contact type water outlet
And processing the video collected by the front-view camera and the video collected by the side-view camera, wherein if the video processing result collected by the front-view camera shows that a moving area (namely a water area) exists in the video collecting area, and the video processing result collected by the side-view camera shows that the moving area and the side-view camera both belong to static areas in the video collecting area, the underground water outlet form of the tunnel face is contact water outlet.
(3) Non-contact water outlet
And (3) processing videos collected by the side-view camera and the side-view camera, wherein if the processed results show that a motion area (namely a water area) exists in the video collection area, the underground water outlet form of the tunnel face is non-contact water outlet.
If the water outlet state is in a contact type or non-contact type, the surface water outlet area calculation method comprises the following steps:
S＝n i ×A
in the formula: s-area of water outlet (m) 2 )；
n i The front-view camera collects the number of the pixel points with the gray value of 255 in the video identification result graph;
a-actual area (m) represented by a single pixel 2 )。
If the outlet form of the underground water is contact or non-contact, determining the position of the water outlet, wherein the specific determination method comprises the following steps:
constructing a local coordinate system by taking a lower left corner pixel point in a video collected by a front-view camera as a coordinate origin, taking the width direction of each frame image of the front-view video as an X axis, taking the height direction as a Y axis and taking the width direction of each frame image of the side-view video as a Z axis;
and recording local coordinates of pixel points with the gray value of 255 in videos collected by the front-view camera and the side-view camera based on the constructed local coordinate system.
(1) Contact type water outlet
If the water outlet is judged to be in contact type, according to a video processing result acquired by the front-view camera, the local coordinate of the pixel point with the maximum Y coordinate in the pixel points with the gray value of 255 is used for representing the water outlet position.
(2) Non-contact type water outlet
And if the non-contact type water outlet is judged, according to the video processing result acquired by the side-view camera, the local coordinate of the pixel point with the minimum Z coordinate in the pixel points with the gray value of 255 is used for representing the water outlet position.
In some optional embodiments, the image processing module is specifically configured to convert a color image in a video into a grayscale image based on an RGB value, an HSI value, an HSV value, and the like of each frame of image; and (4) carrying out segmentation, enhancement and sharpening processing on the gray level image based on an image processing technology, and storing.
In some alternative embodiments, the video processing module is specifically adapted for
Based on a video recombination technology, recombining the stored gray processing images into a gray video according to a time sequence;
determining a background image in the recombined video based on video processing methods such as machine learning, background subtraction, background enhancement and the like, and simultaneously dividing a moving area and a static area in the background image into 2 types;
and marking the pixel points of the motion area and the static area by 1 and 0 respectively based on the classification result after video processing.
Referring now to FIG. 8, shown is a schematic diagram of an electronic device suitable for use in implementing embodiments of the present disclosure. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., car navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 12 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 11, the electronic device may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 801 that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 802 or a program loaded from a storage means 808 into a Random Access Memory (RAM) 803. In the RAM803, various programs and data necessary for the operation of the electronic apparatus 900 are also stored. The processing device 801, the ROM802, and the RAM803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.
Generally, the following devices may be connected to the I/O interface 805: input devices 806 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 807 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage 808 including, for example, magnetic tape, hard disk, etc.; and a communication device 809. The communication means 809 may allow the electronic device to communicate wirelessly or by wire with other devices to exchange data. While fig. 11 illustrates an electronic device having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, the processes described above with reference to the flow diagrams may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 809, or installed from the storage means 808, or installed from the ROM 802. The computer program, when executed by the processing apparatus 801, performs the above-described functions defined in the methods of the embodiments of the present disclosure.
It should be noted that the computer readable medium of the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to:
collecting a video at an underground water outlet; extracting each frame of image of the video, numbering and storing each frame of image according to the time sequence of the photos; carrying out gray level processing on each extracted frame image; processing the video, determining a background image in the recombined video, dividing a moving area and a static area in the background image into 2 types, and marking pixel points of the moving area and the static area by 1 and 0 respectively; carrying out image processing based on the classified binary image of the moving and static areas, and extracting the physical characteristics of underground water; based on the video processing result and the underground water flow characteristics, intelligently and qualitatively identifying the underground water state; the intelligent qualitative identification of the underground water state comprises identification of a water outlet form (including no water, contact water outlet and non-contact water outlet), a surface water outlet area, a water outlet position and the like.
According to the flowing form of the underground water at the water outlet, the water outlet form of the underground water on the tunnel face can be qualitatively divided into 3 states: water-free, contact-type water outlet and non-contact-type water outlet. The specific interpretation method is as follows:
(1) Without water
And (3) processing the video collected by the front-view camera and the video collected by the side-view camera, wherein if the processing results show that the video collecting areas are static areas (namely, waterless areas), no underground water is leaked.
(2) Contact type water outlet
And processing the video collected by the front-view camera and the video collected by the side-view camera, wherein if the video processing result collected by the front-view camera shows that a motion region (namely a water region) exists in the video collecting region, and the video processing result collected by the side-view camera shows that the area of the motion region in the video collecting region is lower than a statistical threshold value, the underground water outlet form of the tunnel face is contact water outlet.
(3) Non-contact water outlet
And (3) processing videos collected by the side-view camera and the side-view camera, wherein if the processed results show that a motion area (namely a water area) exists in the video collection area, the underground water outlet form of the tunnel face is non-contact water outlet.
If the water outlet state is contact or non-contact, the surface water outlet area calculation method is as follows:
S＝n i ×A
in the formula: s-area of water outlet (m) 2 )；
n i The front-view camera collects the number of the pixel points with the gray value of 255 in the video identification result graph;
a-actual area (m) represented by a single pixel 2 )；
If the outlet form of the underground water is contact or non-contact, determining the position of the water outlet, wherein the specific determination method comprises the following steps:
constructing a local coordinate system by taking a lower left corner pixel point in a video collected by a front-view camera as a coordinate origin, taking the width direction of each frame image of the front-view video as an X axis, taking the height direction as a Y axis and taking the width direction of each frame image of the side-view video as a Z axis;
and recording local coordinates of pixel points with the gray scale value of 255 in videos collected by the front-view camera and the side-view camera based on the constructed local coordinate system.
(1) Contact type water outlet
And if the water outlet is judged to be in contact type, according to a video processing result acquired by the front-view camera, the local coordinate of the pixel point with the maximum Y coordinate in the pixel points with the gray value of 255 is used for representing the position of the water outlet.
(2) Non-contact water outlet
And if the non-contact type water outlet is judged, according to the video processing result acquired by the side-looking camera, the local coordinate of the pixel point with the minimum Z coordinate in the pixel points with the gray value of 255 is used for representing the position of the water outlet.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, smalltalk, python, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of a module does not in some cases constitute a limitation of the module itself, for example, an acquisition module may also be described as a "module of groundwater video".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems on a chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other embodiments in which any combination of the features described above or their equivalents does not depart from the spirit of the disclosure. For example, the above features and the technical features disclosed in the present disclosure (but not limited to) having similar functions are replaced with each other to form the technical solution.
Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
The above is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and variations may be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (9)
1. An intelligent recognition method for a tunnel face groundwater outlet form is characterized by comprising
Collecting a video at a groundwater outlet;
extracting each frame of image of the video, numbering and storing each frame of image according to the time sequence of the photos;
carrying out gray level processing on each extracted frame image;
processing the video, determining a background image in the recombined video, dividing a moving area and a static area in the background image into 2 types, and marking pixel points of the moving area and the static area by using 1 and 0 respectively;
carrying out image processing based on the classified binary image of the motion area and the static area, and extracting the physical characteristics of underground water;
based on the video processing result and the underground water flowing characteristic, intelligently and qualitatively identifying the underground water state, including qualitatively dividing the underground water outlet form of the tunnel face into anhydrous, contact type water outlet and non-contact type water outlet according to the flowing form of the underground water at the water outlet, processing the video collected by the front-view camera and the video collected by the side-view camera, and if the processing results show that the underground water outlet form of the tunnel face is anhydrous in the video collecting area; if the videos collected by the front-view camera and the videos collected by the side-view camera are processed, the video processing result collected by the front-view camera indicates that a motion area exists in the video collecting area, and the video processing result collected by the side-view camera indicates that the motion area and the video collecting area are static areas, the underground water outlet form of the tunnel face is contact type water outlet; if the videos collected by the front-view camera and the side-view camera are processed, and if the processing results show that a motion area exists in the video collection area, the underground water outlet form of the tunnel face is non-contact water outlet; on the basis of contact type water outlet judgment, connected domain detection is carried out on the processing result of the video and geometric coordinates of the mass center of the connected domain are counted, if the maximum distance of the mass center of different connected domains in the same video is larger than a set threshold value, discontinuous water outlet is judged, otherwise, continuous water outlet is judged;
the intelligent qualitative identification of the underground water state comprises identification of a water outlet form, identification of the area of a surface water outlet area and identification of a water outlet position.
2. The intelligent identification method for the underground water outlet form of the tunnel face according to claim 1, characterized by collecting videos at the underground water outlet, specifically comprising the following steps:
2 high-definition cameras in front view and side view are respectively arranged at an underground water outlet;
and respectively recording the distance between the front-view camera and the side-view camera from the water outlet, the focal length of the camera and the resolution information.
3. The intelligent recognition method for the underground water outlet form of the tunnel face according to claim 2, wherein if the underground water outlet form is contact or non-contact, the surface water outlet area calculation method is as follows:
S＝n i ×A
in the formula: s is the water outlet area;
n i acquiring the number of pixels with the gray value of 255 in a video identification result graph by the front-view camera;
a-the actual area represented by a single pixel point;
if the outlet form of the underground water is contact or non-contact, determining the position of the water outlet, wherein the specific determination method comprises the following steps:
constructing a local coordinate system by taking a lower left corner pixel point in a video collected by a front-view camera as a coordinate origin, taking the width direction of each frame image of the front-view video as an X axis, taking the height direction as a Y axis and taking the width direction of each frame image of the side-view video as a Z axis;
recording local coordinates of pixel points with the gray scale value of 255 in videos collected by the front-view camera and the side-view camera based on the constructed local coordinate system;
and if the water outlet is judged to be in contact type, according to the video processing result acquired by the front-view camera, the water outlet position is represented by the local coordinate of the pixel point with the maximum Y coordinate in the pixel points with the gray value of 255, and if the water outlet is judged to be in non-contact type, according to the video processing result acquired by the side-view camera, the water outlet position is represented by the local coordinate of the pixel point with the minimum Z coordinate in the pixel points with the gray value of 255.
4. The intelligent recognition method for the underground water outlet form of the tunnel face according to claim 1, wherein the extracted frames of images are subjected to gray level processing, and the method specifically comprises the following steps:
converting color images in the video into gray images based on RGB values, HSI values, HSV values and gray values of all frames of images;
and (3) segmenting, enhancing and sharpening the gray level image based on an image processing technology, and storing.
5. The method for intelligently identifying the underground water outlet form of the tunnel face according to claim 1, wherein the video is processed to determine a background image in the recombined video, a motion area and a static area in the background image are divided into 2 types, and pixels of the motion area and the static area are respectively marked by 1 and 0, specifically:
based on a video recombination technology, recombining the stored gray processing images into a gray video according to a time sequence;
determining a background image in the recombined video based on a background subtraction and background enhancement video processing method, and simultaneously dividing a moving area and a static area in the background image into 2 types;
and marking the pixel points of the motion area and the static area by 1 and 0 respectively based on the classification result after video processing.
6. The method of claim 1, wherein the image processing is performed based on a binary image of the classification of moving and static areas, and the extraction of the physical characteristics of the groundwater comprises
Converting the background image into a binary image based on the moving area and the static area classification labels;
based on the classification binary image of the moving and static areas and an image processing technology, the brightness, the appearance and the color visual characteristics, the size, the mass center, the movement mode, the area and the frequency domain physical characteristics of the underground water flow are extracted.
7. An underground water outlet form determining device is characterized by comprising
The acquisition module is used for the video at the underground water outlet;
the video splitting module is used for extracting each frame of image of the video, numbering and storing each frame of image according to the time sequence of the photos;
the image processing module is used for carrying out gray level processing on each extracted frame image;
the video processing module is used for processing the video, determining a background image in the recombined video, dividing a moving area and a static area in the background image into 2 types, and marking pixel points of the moving area and the static area by 1 and 0 respectively;
the extraction module is used for carrying out image processing based on the classified binary image of the moving and static areas and extracting the physical characteristics of underground water;
the identification module is used for intelligently and qualitatively identifying the underground water state based on the video processing result and the underground water flowing characteristic, wherein the underground water state identification method comprises the steps of qualitatively dividing the underground water outlet form of the tunnel face into waterless, contact-type water outlet and non-contact-type water outlet according to the flowing form of the underground water at the water outlet, processing the video acquired by the front-view camera and the video acquired by the side-view camera, and if the processing results indicate that the video acquisition regions are all static regions, determining that the underground water outlet form of the tunnel face is waterless; if the videos collected by the front-view camera and the videos collected by the side-view camera are processed, the video processing result collected by the front-view camera indicates that a motion area exists in the video collecting area, and the video processing result collected by the side-view camera indicates that the motion area and the video collecting area are static areas, the underground water outlet form of the tunnel face is contact type water outlet; if the videos collected by the side-view camera and the vision-looking camera are processed, and if the processing results show that a motion area exists in the video collection area, the underground water outlet form of the tunnel face is non-contact type water outlet; on the basis of contact type water outlet judgment, connected domain detection is carried out on the processing result of the video and geometric coordinates of the mass center of the connected domain are counted, if the maximum distance of the mass center of different connected domains in the same video is larger than a set threshold value, discontinuous water outlet is judged, otherwise, continuous water outlet is judged;
the intelligent qualitative identification of the underground water state comprises identification of a water outlet form, identification of the area of a surface water outlet area and identification of a water outlet position.
8. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
9. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-6.
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| JPH11259656A (en) * | 1998-03-10 | 1999-09-24 | Teito Rapid Transit Authority | Tunnel wall surface decision device |
| CN110529186A (en) * | 2019-09-11 | 2019-12-03 | 上海同岩土木工程科技股份有限公司 | Tunnel structure percolating water based on infrared thermal imaging accurately identifies device and method |
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