Tunnel detection method and equipment based on color image

Abstract

The present invention provides a tunnel detection method based on color images, including using a fill light system to fill light for a color camera, using the color camera to obtain the apparent image data of the tunnel lining; using a three-dimensional measurement sensor to obtain the tunnel lining contour data and the working distance of the color camera; combining the working distance and installation posture information of the color camera, adaptively clipping the apparent image data to obtain the clipped apparent image data; splicing the clipped apparent image data to obtain the full cross-section data of the tunnel lining; using an industrial camera to obtain the landscape image data in front of and obliquely above the tunnel detection equipment, and controlling the automatic opening and closing of the data acquisition and storage module according to the landscape image data, the data acquisition and storage module is used to realize the collection and storage of the apparent image data and the tunnel lining contour data. More accurate detection of cracks, water seepage, peeling and other diseases can be achieved through color image data.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel detection, and in particular to a tunnel detection method and equipment based on color images. Background Art

[0002] Tunnel lining defects can be divided into superficial defects and internal defects based on their manifestations. Superficial defects are defects that appear on the lining surface, such as cracks, water leakage, peeling, etc. Internal defects include insufficient lining thickness and voids.

[0003] At present, tunnel inspection still mainly relies on manual means. Tunnel lining inspection requires professional inspectors to rely on various handheld instruments and use lifting vehicles or scaffolding to approach the tunnel lining for inspection, which is time-consuming and labor-intensive, and poses a safety hazard. At the same time, the inspected tunnel needs to be closed during the inspection process, affecting normal traffic operations. In addition, the inspection results are affected by the subjectivity of the inspectors, making it difficult to ensure the accuracy of the inspection results.

[0004] In recent years, with the continuous development of sensor and computer technology, researchers have begun to integrate a variety of sensor devices on mobile platforms to obtain image data of tunnel surface defects in a non-destructive and non-contact manner, and then automatically detect the surface of the tunnel lining. However, the tunnel images obtained by the existing measurement technology solutions are all gray image data, and gray images cannot effectively distinguish the leakage area, which leads to the omission of important defects, thus affecting the evaluation and guarantee of tunnel operation safety. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a tunnel detection method and equipment based on color images.

[0006] In a first aspect, the present invention provides a tunnel detection method based on color images, comprising:

[0007] In the case where the color camera is supplemented with light by the supplementary light system, the color camera is used to obtain apparent image data of the tunnel lining;

[0008] Using a three-dimensional measurement sensor to obtain tunnel lining profile data and the working distance of the color camera;

[0009] Adaptively cropping the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera to obtain cropped apparent image data of the tunnel lining;

[0010] Performing data splicing on the cropped tunnel lining surface image data to obtain full-section data of the tunnel lining;

[0011] An industrial camera is used to obtain landscape image data directly in front of and diagonally above the tunnel detection equipment, and the automatic opening and closing of the data acquisition and storage module is controlled according to the landscape image data. The data acquisition and storage module is used to realize the acquisition and storage of the apparent image data of the tunnel lining and the contour data of the tunnel lining.

[0012] According to the color image-based tunnel detection method provided by the present invention, the installation posture information of the color camera includes the relative coordinate position of the adjacent camera installations, the camera viewing angle direction, and the camera viewing angle range information;

[0013] The method of adaptively cropping the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera includes:

[0014] In combination with the working distance and installation posture information of the color camera, a first overlapping area and an overlapping boundary position in the apparent image data of the tunnel lining measured by adjacent cameras are obtained;

[0015] Acquire a protection extension area in the first overlapping area by combining the first overlapping area, the overlapping boundary position, and a preset overlapping area protection extension width;

[0016] In the first overlapping area, image data other than the protection extension area is cropped.

[0017] According to the color image-based tunnel detection method provided by the present invention, the cropped tunnel lining surface image data is spliced ​​to obtain the tunnel lining full section data, including:

[0018] Acquire a second overlapping area in the cropped tunnel lining surface image data in combination with the overlapping boundary position and a preset overlapping area search radius;

[0019] By matching feature points with the same name, the second overlapping area is precisely cropped;

[0020] Combined with the timing of image data acquisition and the measurement angle of the color camera, the precisely cropped image data are spliced ​​to obtain the full-section data of the tunnel lining.

[0021] According to the color image-based tunnel detection method provided by the present invention, the industrial camera is used to obtain landscape image data directly in front of and obliquely above the tunnel detection equipment, and the automatic opening and closing of the data acquisition and storage module is controlled according to the landscape image data, including:

[0022] Using binocular vision principle to determine a first preset area in front of the tunnel detection device, and statistically analyzing the landscape image data within the first preset area to obtain a first average brightness of the landscape image data within the first preset area;

[0023] Using binocular vision principle to determine a second preset area range obliquely above the tunnel detection device, and statistically analyzing the landscape image data within the second preset area range to obtain a second average brightness of the landscape image data within the second preset area range;

[0024] Using the variation characteristics of the first average brightness and the second average brightness along the detection mileage, determining whether the tunnel detection device enters or leaves the tunnel;

[0025] If the tunnel detection equipment enters the tunnel, the data collection and storage module is turned on;

[0026] If the tunnel detection device leaves the tunnel, the data acquisition and storage module is turned off.

[0027] According to the color image-based tunnel detection method provided by the present invention, the method of using the variation characteristics of the first average brightness and the second average brightness along the detection mileage to determine whether the tunnel detection device enters or leaves the tunnel includes:

[0028] Using a preset statistical frame interval, calculating a first average brightness difference corresponding to the first average brightness and a second average brightness difference corresponding to the second average brightness in the preset statistical frame interval;

[0029] When the absolute value of the first average brightness difference is greater than or equal to a first preset brightness difference threshold, and the absolute value of the second average brightness difference is greater than or equal to a second preset brightness difference threshold, it is determined whether the tunnel detection device enters or leaves the tunnel based on the first average brightness difference.

[0030] According to the color image-based tunnel detection method provided by the present invention, judging whether the tunnel detection device enters or leaves the tunnel according to the first average brightness difference includes:

[0031] If the absolute value of the first average brightness difference is greater than or equal to a third preset brightness difference threshold, and the first average brightness difference is less than 0, it is determined that the tunnel detection device enters a tunnel; or,

[0032] If the absolute value of the first average brightness difference is less than a third preset brightness difference threshold, and the first average brightness difference is greater than 0, it is determined that the tunnel detection device enters a tunnel;

[0033] If the absolute value of the first average brightness difference is greater than or equal to a third preset brightness difference threshold, and the first average brightness difference is greater than 0, it is determined that the tunnel detection device has left the tunnel; or,

[0034] If the absolute value of the first average brightness difference is less than a third preset brightness difference threshold, and the first average brightness difference is less than 0, it is determined that the tunnel detection device has left the tunnel.

[0035] According to the color image-based tunnel detection method provided by the present invention, the color camera, the fill light system and the three-dimensional measurement sensor constitute a tunnel lining measurement system, and the tunnel lining measurement system is installed on a rotating bracket;

[0036] The rotating bracket can drive the tunnel lining measurement system to rotate together to adjust the overall measurement posture of the tunnel measurement system to achieve measurement of different areas of the tunnel lining.

[0037] The tunnel detection method based on color images provided by the present invention further includes:

[0038] During the driving process of the tunnel inspection equipment, the tunnel lining measurement system is in working state;

[0039] Wherein, when the data acquisition and storage module is in a closed state, the data measured by the tunnel lining measurement system is not stored;

[0040] When the data acquisition and storage module is in the on state, the apparent image data of the tunnel lining in the data measured by the tunnel lining measurement system is cropped, and the cropped apparent image data and the tunnel lining contour data are stored.

[0041] In a second aspect, the present invention further provides a tunnel detection equipment based on color images, comprising a fill light system, a color camera, a three-dimensional measurement sensor, an industrial camera, a data cropping module, a data splicing module, a data acquisition and storage module, and a measurement platform, wherein the fill light system, the color camera, the three-dimensional measurement sensor, the industrial camera, the data acquisition module, the data splicing module, and the data acquisition and storage module are all integrated on the measurement platform;

[0042] The fill light system is used to fill light for the color camera;

[0043] The color camera is used to obtain apparent image data of the tunnel lining when the color camera is supplemented with light by the supplementary light system;

[0044] The three-dimensional measurement sensor is used to obtain tunnel lining profile data and the working distance of the color camera;

[0045] The data cropping module is used to adaptively crop the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera to obtain cropped apparent image data of the tunnel lining;

[0046] The data splicing module is used to perform data splicing on the cropped tunnel lining surface image data to obtain the tunnel lining full section data;

[0047] The industrial camera is used to form a landscape measurement system for acquiring landscape image data directly in front of and obliquely above the tunnel detection equipment, and the automatic opening and closing of the data acquisition and storage module is controlled according to the landscape image data;

[0048] The data acquisition and storage module is used to acquire and store the surface image data of the tunnel lining and the contour data of the tunnel lining.

[0049] According to the color image-based tunnel detection equipment provided by the present invention, the measurement platform is a mobile measurement vehicle, and a positioning system is installed in the measurement platform, and the positioning system includes one or more of GNSS, encoder, and control network.

[0050] The color image-based tunnel detection method provided by the present invention performs tunnel lining detection by using the apparent image data of the tunnel lining obtained by a color camera. Specifically, a fill light system is used to fill light for the color camera, thereby ensuring that high-quality image data is obtained and avoiding the problem of insufficient light or overexposure; the apparent image data of the tunnel lining is obtained by using a color camera, so that the apparent details of the tunnel lining can be captured, including color, texture and other information, so that subsequent data analysis and processing are more comprehensive and accurate; a three-dimensional measurement sensor is used to obtain the contour data of the tunnel lining and the working distance of the color camera; the apparent image data of the tunnel lining is measured in combination with the working distance and installation posture information of the color camera. The image data is adaptively cropped to obtain cropped tunnel lining surface image data; the cropped tunnel lining surface image data is data spliced ​​to obtain the full cross-section data of the tunnel lining. In this way, by adaptively cropping and data splicing the color surface image data, the amount of tunnel lining color image data can be reduced and the data processing efficiency can be improved while ensuring resolution and accuracy. In addition, the present invention also uses an industrial camera to obtain the landscape image data directly in front of and obliquely above the tunnel detection equipment, and controls the automatic opening and closing of the data acquisition and storage module according to the landscape image data, so that data acquisition and storage are only performed when needed, reducing the amount of data processed by the measurement data. Compared with the use of grayscale image data in the prior art, the present invention can more realistically reflect the tunnel lining wall conditions by using tunnel lining color image data, and can more accurately detect cracks, water leakage, peeling and other diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 It is a schematic diagram of the process of the tunnel detection method based on color images provided by the present invention;

[0053] Figure 2 It is a structural schematic diagram of a tunnel detection equipment based on color images provided by the present invention;

[0054] Figure 3 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] It should be noted that, in the description of the present invention, the terms "first", "second", etc. are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable where appropriate, so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type, and the number of objects is not limited, for example, the first object can be one or more.

[0057] The tunnel detection method based on color images provided by the present invention is exemplarily introduced below with reference to the accompanying drawings.

[0058] Figure 1 is a schematic diagram of the process of the tunnel detection method based on color images provided by the present invention, such as Figure 1 As shown, the method includes:

[0059] Step 110, using the color camera to acquire apparent image data of the tunnel lining while using the fill light system to fill light the color camera;

[0060] Step 120, using a three-dimensional measurement sensor to obtain tunnel lining profile data and the working distance of the color camera;

[0061] Step 130, combining the working distance and installation posture information of the color camera, adaptively cropping the apparent image data of the tunnel lining to obtain cropped apparent image data of the tunnel lining;

[0062] Step 140, performing data splicing on the cropped tunnel lining surface image data to obtain tunnel lining full section data;

[0063] Step 150, using an industrial camera to obtain landscape image data directly in front of and diagonally above the tunnel detection equipment, and controlling the automatic opening and closing of a data acquisition and storage module based on the landscape image data, wherein the data acquisition and storage module is used to realize the acquisition and storage of the apparent image data of the tunnel lining and the contour data of the tunnel lining.

[0064] It should be noted that the execution subject of the color image-based tunnel detection method provided in the embodiment of the present invention may be an electronic device, a component in an electronic device, an integrated circuit, or a chip. The electronic device may be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device may be a mobile phone, a tablet computer, a laptop computer, a PDA, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc., and the non-mobile electronic device may be a server, a network attached storage (NAS), a personal computer (PC), etc., which is not specifically limited in the embodiment of the present invention.

[0065] The following takes a computer executing the color image-based tunnel detection method provided by the present invention as an example to describe in detail the technical solution of the embodiment of the present invention.

[0066] Specifically, in the embodiment of the present invention, when the color camera shoots the tunnel lining surface image data, it is affected by the ambient light and easily produces a dark and blurred image. The color camera can be supplemented with light by the supplementary light system, which can effectively improve the brightness and clarity of the image.

[0067] Optionally, the color camera can be a line scan color camera or an area array color camera. The line scan color camera is suitable for collecting images of high-speed moving objects, while the area array color camera is suitable for high-resolution image collection of static objects. In practical applications, the line scan color camera or the area array color camera can be flexibly selected according to actual conditions to obtain the apparent image data of the tunnel lining.

[0068] Optionally, the fill light system uses white LED lights, which can provide uniform and natural lighting, so that the color camera can capture the true color and texture information of the tunnel lining. By filling the color camera with the fill light system, the quality of the apparent image data of the tunnel lining can be effectively improved, the details and contrast of the image can be improved, and the apparent image data of the tunnel lining can be analyzed and processed more accurately, thereby achieving more accurate tunnel detection and evaluation.

[0069] The 3D measurement sensor can measure the 3D spatial position and shape of an object. Using it to obtain tunnel lining profile data can help to locate and analyze tunnel defects later. At the same time, in this embodiment, the 3D measurement sensor can also be used to obtain the distance between the color camera and the tunnel lining, that is, the working distance of the color camera.

[0070] Optionally, the three-dimensional measurement sensor uses a three-dimensional laser radar, which is a sensor that can quickly and accurately obtain three-dimensional point cloud data of an object. By emitting a laser beam and measuring its return time, the distance information of the object surface from the sensor can be obtained, and combined with the rotational scanning of the sensor, the three-dimensional shape of the object can be constructed. In the application of tunnel lining, the three-dimensional laser radar can scan the inside of the tunnel and obtain the three-dimensional contour information of the lining.

[0071] In this embodiment, due to the different installation posture information and observation distance of the color camera, the apparent image data of the tunnel lining captured will also be different. Through adaptive cropping, the apparent image data of the tunnel lining can be effectively cropped according to the working distance and installation posture information of the color camera, so that the size and resolution of the captured apparent image data are more consistent and accurate.

[0072] Furthermore, since the tunnel lining is an arc-shaped structure, it may not be possible to simultaneously obtain complete tunnel lining cross-section data when using a color camera and a 3D measurement sensor for shooting and measurement. Therefore, it is necessary to splice multiple acquired tunnel lining surface image data to obtain complete tunnel lining cross-section data.

[0073] In addition, in this embodiment, an industrial camera is used to obtain landscape image data directly in front of and diagonally above the tunnel detection device, and the landscape image data directly in front of and diagonally above the tunnel detection device is used to determine whether the tunnel detection device has entered or left the tunnel. For example, when the tunnel detection device enters the tunnel, the landscape image data in front and diagonally above will show obvious changes, such as background color, texture, brightness, etc. Therefore, it is possible to determine whether the tunnel detection device has entered the tunnel by comparing the difference between the landscape image data before and after. Similarly, when the tunnel detection device leaves the tunnel, the landscape image data in front and diagonally above will also change, which can be determined by a similar method.

[0074] When the tunnel detection equipment enters the tunnel, the control data acquisition and storage module automatically turns on and starts to collect and store relevant data; when the tunnel detection equipment leaves the tunnel, the control data acquisition and storage module automatically turns off and stops collecting and storing data. This can avoid unnecessary data collection and storage, save storage space and reduce the cost of data processing and transmission.

[0075] The color image-based tunnel detection method provided by the present invention performs tunnel lining detection by using the apparent image data of the tunnel lining obtained by a color camera. Specifically, a fill light system is used to fill light for the color camera, thereby ensuring that high-quality image data is obtained and avoiding the problem of insufficient light or overexposure; the apparent image data of the tunnel lining is obtained by using a color camera, so that the apparent details of the tunnel lining can be captured, including color, texture and other information, so that subsequent data analysis and processing are more comprehensive and accurate; a three-dimensional measurement sensor is used to obtain the contour data of the tunnel lining and the working distance of the color camera; the apparent image data of the tunnel lining is measured in combination with the working distance and installation posture information of the color camera. The image data is adaptively cropped to obtain cropped tunnel lining surface image data; the cropped tunnel lining surface image data is data spliced ​​to obtain the full cross-section data of the tunnel lining. In this way, by adaptively cropping and data splicing the color surface image data, the amount of tunnel lining color image data can be reduced and the data processing efficiency can be improved while ensuring resolution and accuracy. In addition, the present invention also uses an industrial camera to obtain the landscape image data directly in front of and obliquely above the tunnel detection equipment, and controls the automatic opening and closing of the data acquisition and storage module according to the landscape image data, so that data acquisition and storage are only performed when needed, reducing the amount of data processed by the measurement data. Compared with the use of grayscale image data in the prior art, the present invention can more realistically reflect the tunnel lining wall conditions by using tunnel lining color image data, and can more accurately detect cracks, water leakage, peeling and other diseases.

[0076] In some embodiments, the installation posture information of the color camera includes the relative coordinate position of the adjacent camera installation, the camera viewing angle direction and the camera viewing angle range information;

[0077] The method of adaptively cropping the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera includes:

[0078] In combination with the working distance and installation posture information of the color camera, a first overlapping area and an overlapping boundary position in the apparent image data of the tunnel lining measured by adjacent cameras are obtained;

[0079] Acquire a protection extension area in the first overlapping area by combining the first overlapping area, the overlapping boundary position, and a preset overlapping area protection extension width;

[0080] In the first overlapping area, image data other than the protection extension area is cropped.

[0081] In this embodiment, the installation posture information of the color camera is obtained by static calibration. Static calibration is a camera posture estimation method based on known reference markers, which can obtain information such as the camera's position, orientation, and viewing angle range.

[0082] In one example, it is necessary to place some known reference markers, then use a color camera to capture these markers and identify their positions and orientations, so as to calculate the installation posture information of the color camera, including the relative coordinate positions, viewing angle directions and viewing angle ranges between adjacent cameras. This information can be used for subsequent image processing and analysis, such as adaptive cropping of apparent image data of tunnel linings.

[0083] The first overlapping area refers to the overlapping area in the apparent image data of the tunnel lining measured by adjacent cameras. In this area, the measurement data of two adjacent cameras overlap and need to be fused to obtain more accurate data.

[0084] In this embodiment, the boundary position of the overlapping area in the apparent image data of the tunnel lining measured by two adjacent color cameras is first determined according to the relative coordinate positions, viewing directions and viewing ranges of adjacent cameras and the working distances of each camera, and the first overlapping area in the apparent image data of the tunnel lining measured by the two adjacent color cameras is further determined according to the overlapping boundary position.

[0085] Then, the first overlapping area, the overlapping boundary position and the preset overlapping area protection extension width are combined to obtain the protection extension area in the first overlapping area. This protection extension area is used to retain edge features or important information that may exist in the image to avoid accidental deletion during the cropping process.

[0086] Finally, the image data outside the protection extension area is cropped in the first overlapping area, and the cropped image data is retained for subsequent processing and analysis.

[0087] The color image-based tunnel detection method provided by the present invention determines the adaptive cropping area by using the working distance and installation posture information of the color camera to retain the key information of the overlapping area and remove the unnecessary parts. This can improve the processing efficiency and accuracy while avoiding the accidental deletion of important information.

[0088] In some embodiments, the step of splicing the cropped tunnel lining surface image data to obtain tunnel lining full section data includes:

[0089] Acquire a second overlapping area in the cropped tunnel lining surface image data in combination with the overlapping boundary position and a preset overlapping area search radius;

[0090] By matching feature points with the same name, the second overlapping area is precisely cropped;

[0091] Combined with the timing of image data acquisition and the measurement angle of the color camera, the precisely cropped image data are spliced ​​to obtain the full-section data of the tunnel lining.

[0092] In this embodiment, after determining the boundary position of the overlapping area in the apparent image data of the tunnel lining measured by two adjacent color cameras based on the relative coordinate positions, viewing directions and viewing ranges of adjacent cameras and the working distances of each camera, combined with a pre-set overlapping area search radius, it is possible to determine a second overlapping area in the cropped tunnel lining apparent image data by expanding outward by a certain distance starting from the boundary position of the first overlapping area.

[0093] After the second overlapping area is determined, an artificial intelligence algorithm, such as a feature point matching algorithm in the field of computer vision, can be used to identify and match the same feature points in the second overlapping area. By identifying and matching these feature points, the boundary and outline of the second overlapping area can be accurately determined.

[0094] After the feature point matching is completed, the second overlapping area can be accurately cropped according to the matching results. This ensures that the cropped boundary is completely consistent with the overlapping part of the adjacent images, thereby achieving seamless connection and accurate splicing, providing a more reliable foundation for subsequent image processing and data fusion.

[0095] Specifically, the tunnel lining is composed of multiple adjacent parts, and the surface of each part is measured by different cameras at different angles. Therefore, in this embodiment, the tunnel lining image data after precise cropping is spliced ​​in combination with the timing of measurement and the measurement angle of the camera. By splicing the image data of each part, the full cross-section data of the tunnel lining can be obtained.

[0096] In some embodiments, the method of using an industrial camera to obtain landscape image data directly in front of and obliquely above the tunnel detection device, and controlling the automatic opening and closing of the data acquisition and storage module according to the landscape image data, includes:

[0097] Using binocular vision principle to determine a first preset area in front of the tunnel detection device, and statistically analyzing the landscape image data within the first preset area to obtain a first average brightness of the landscape image data within the first preset area;

[0098] Using binocular vision principle to determine a second preset area range obliquely above the tunnel detection device, and statistically analyzing the landscape image data within the second preset area range to obtain a second average brightness of the landscape image data within the second preset area range;

[0099] Using the variation characteristics of the first average brightness and the second average brightness along the detection mileage, determining whether the tunnel detection device enters or leaves the tunnel;

[0100] If the tunnel detection equipment enters the tunnel, the data collection and storage module is turned on;

[0101] If the tunnel detection device leaves the tunnel, the data acquisition and storage module is turned off.

[0102] In this embodiment, the binocular vision principle is first used to determine the preset area ranges directly in front of and obliquely above the tunnel detection device. Then, the brightness values ​​of all pixels in these two areas are counted respectively, and their average values ​​are calculated to obtain the first average brightness of the landscape image data within the first preset area and the second average brightness of the landscape image data within the second preset area.

[0103] Then, the transformation characteristics of the average brightness of the landscape image data in the two areas along the detection mileage are compared. By comparing the transformation characteristics along the detection mileage, it can be determined whether the current tunnel detection device enters or leaves the tunnel.

[0104] If the judgment result is that the tunnel detection device enters the tunnel, the data acquisition and storage module is automatically turned on to start recording relevant data. If the judgment result is that the tunnel detection device leaves the tunnel, the data acquisition and storage module is automatically turned off to stop recording relevant data.

[0105] The color image-based tunnel detection method provided by the present invention uses the binocular vision principle to perform brightness statistics on landscape image data within a preset area directly in front and obliquely above, and judges whether the tunnel detection equipment enters or leaves the tunnel based on the brightness change characteristics, thereby automatically controlling the switch of the data acquisition and storage module.

[0106] In some embodiments, the determining whether the tunnel detection device enters or leaves the tunnel by using the variation characteristics of the first average brightness and the second average brightness along the detection mileage includes:

[0107] Using a preset statistical frame interval, calculating a first average brightness difference corresponding to the first average brightness and a second average brightness difference corresponding to the second average brightness in the preset statistical frame interval;

[0108] When the absolute value of the first average brightness difference is greater than or equal to a first preset brightness difference threshold, and the absolute value of the second average brightness difference is greater than or equal to a second preset brightness difference threshold, it is determined whether the tunnel detection device enters or leaves the tunnel based on the first average brightness difference.

[0109] In one example, the preset statistical frame interval is p, then according to the first average brightness corresponding to the current frame image (such as image frame number m) and the first average brightness before the first average brightness corresponding to the previous p frame image of the current frame (such as image frame number mp), the first average brightness difference Gd 1 .

[0110] According to the second average brightness difference Gd corresponding to the current frame image (such as the image frame number m) and the second average brightness before the second average brightness corresponding to the previous p frame images of the current frame (such as the image frame number mp) 2 .

[0111] If the first average brightness difference Gd 1 The absolute value of the second average brightness difference Gd is greater than or equal to the first preset brightness difference threshold, and the second average brightness difference Gd 2 If the absolute value of is greater than or equal to the second preset brightness difference threshold, it is determined that the scene of the tunnel detection device has changed during this period, that is, the tunnel detection device has left the tunnel, or the tunnel detection device has entered the tunnel. Otherwise, it is determined that the scene of the tunnel detection device has not changed, that is, the tunnel detection device has always been in the tunnel or has always been outside the tunnel.

[0112] When the scene of the tunnel detection device changes, the first average brightness difference Gd 1 Perform analysis to determine whether the tunnel detection equipment is entering or leaving the tunnel.

[0113] Specifically, in some embodiments, judging whether the tunnel detection device enters or leaves the tunnel according to the first average brightness difference includes:

[0114] If the absolute value of the first average brightness difference is greater than or equal to a third preset brightness difference threshold, and the first average brightness difference is less than 0, it is determined that the tunnel detection device enters a tunnel; or,

[0115] If the absolute value of the first average brightness difference is less than a third preset brightness difference threshold, and the first average brightness difference is greater than 0, it is determined that the tunnel detection device enters a tunnel;

[0116] If the absolute value of the first average brightness difference is greater than or equal to a third preset brightness difference threshold, and the first average brightness difference is greater than 0, it is determined that the tunnel detection device has left the tunnel; or,

[0117] If the absolute value of the first average brightness difference is less than a third preset brightness difference threshold, and the first average brightness difference is less than 0, it is determined that the tunnel detection device has left the tunnel.

[0118] Among them, the third preset brightness difference threshold Gd 3 The threshold is set based on the difference in lighting conditions between day and night.

[0119] Specifically, if the first average brightness difference Gd 1 The absolute value of is greater than or equal to the third preset brightness difference threshold Gd 3 , indicating that the current scene is daytime, then continue to analyze the first average brightness difference Gd 1 , if the first average brightness difference Gd 1 is less than 0, then it is determined that the detection device has entered a tunnel; if the first average brightness difference Gd 1 If it is greater than 0, it is determined that the tunnel detection device has left the tunnel.

[0120] If the first average brightness difference Gd 1 The absolute value of the brightness difference is less than the third preset brightness difference threshold Gd 3 , indicating that the current scene is dark, then continue to analyze the first average brightness difference Gd 1 , if the first average brightness difference Gd 1 is greater than 0, then it is determined that the tunnel detection device has entered the tunnel; if the first average brightness difference Gd 1 If it is less than 0, it is determined that the tunnel detection device has left the tunnel.

[0121] In some embodiments, the color camera, the fill light system and the three-dimensional measurement sensor constitute a tunnel lining measurement system, and the tunnel lining measurement system is installed on a rotating bracket;

[0122] The rotating bracket can drive the tunnel lining measurement system to rotate together to adjust the overall measurement posture of the tunnel measurement system to achieve measurement of different areas of the tunnel lining.

[0123] In this embodiment, a tunnel lining measurement system is composed of multiple color cameras, a fill light system and a three-dimensional measurement system, and is installed on a rotating bracket to measure the tunnel lining. By rotating the bracket, the angle and position of the equipment in the tunnel lining measurement system can be changed, thereby measuring different areas of the tunnel lining. On the same tunnel lining, by adjusting the overall measurement posture of the tunnel lining measurement system, the full cross-section (i.e., 180°) of the tunnel lining can be measured.

[0124] In some embodiments, during the driving process of the tunnel inspection device, the tunnel lining measurement system is in working state;

[0125] Wherein, when the data acquisition and storage module is in a closed state, the data measured by the tunnel lining measurement system is not stored;

[0126] When the data acquisition and storage module is in the on state, the apparent image data of the tunnel lining in the data measured by the tunnel lining measurement system is cropped, and the cropped apparent image data and the tunnel lining contour data are stored.

[0127] During the driving process of the tunnel inspection equipment, the tunnel lining measurement system is in working state. At the same time, the data acquisition and storage module can be turned on or off.

[0128] When the data acquisition and storage module is in the off state, the data measured by the tunnel lining measurement system will not be stored. When the data acquisition and storage module is in the on state, the data measured by the tunnel lining measurement system can be stored. Among them, the apparent image data of the tunnel lining will be processed by image cropping and then stored together with the tunnel lining contour data. This can reduce the amount of data and improve the efficiency of subsequent data transmission and processing.

[0129] The tunnel detection equipment based on color images provided by the present invention is described below. Figure 2 is a schematic diagram of the structure of the tunnel detection equipment based on color images provided by the present invention, such as Figure 2As shown, the equipment includes: a fill light system 210, a color camera 220, a three-dimensional measurement sensor 230, an industrial camera 240, a data clipping module 250, a data stitching module 260, a data acquisition and storage module 270 and a measurement platform 280, wherein the fill light system 210, the color camera 220, the three-dimensional measurement sensor 230, the industrial camera 240, the data clipping module 250, the data stitching module 260 and the data acquisition and storage module 270 are all integrated on the measurement platform 280, wherein:

[0130] The fill light system 210 is used to fill light for the color camera 220;

[0131] The color camera 220 is used to obtain apparent image data of the tunnel lining when the color camera 220 is supplemented with light by the supplementary light system 210;

[0132] The three-dimensional measurement sensor 230 is used to obtain tunnel lining profile data and the working distance of the color camera;

[0133] The data clipping module 250 is used to adaptively clip the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera to obtain clipped apparent image data of the tunnel lining;

[0134] The data splicing module 260 is used to perform data splicing on the cropped tunnel lining surface image data to obtain tunnel lining full section data;

[0135] The industrial camera 240 is used to form a landscape measurement system for acquiring landscape image data directly in front of and obliquely above the tunnel detection equipment, and controlling the automatic opening and closing of the data acquisition and storage module according to the landscape image data;

[0136] The data acquisition and storage module 270 is used to acquire and store the surface image data of the tunnel lining and the contour data of the tunnel lining.

[0137] It can be understood that the measuring platform 280 can travel in the tunnel to detect tunnel lining defects.

[0138] It can be understood that the embodiment of the present invention integrates the fill light system 210, the color camera 220, the three-dimensional measurement sensor 230, the industrial camera 240, the data clipping module 250, the data stitching module 260 and the data acquisition and storage module 270 on the same measurement platform 280, and integrates the tunnel detection technology based on color images, the automatic identification technology of tunnel detection equipment entering and leaving the tunnel, and the automatic start and end data acquisition technology of the tunnel. It is achieved that the use of tunnel lining color image data can more realistically reflect the tunnel lining wall conditions, and can more accurately detect cracks, water leakage, peeling and other diseases.

[0139] The color image-based tunnel inspection equipment provided by the present invention performs tunnel lining inspection by using the apparent image data of the tunnel lining obtained by the color camera. Specifically, the color camera is supplemented with light by the supplementary light system, thereby ensuring that high-quality image data is obtained and avoiding the problem of insufficient light or overexposure; the apparent image data of the tunnel lining is obtained by the color camera, so that the apparent details of the tunnel lining can be captured, including color, texture and other information, so that subsequent data analysis and processing are more comprehensive and accurate; the three-dimensional measurement sensor is used to obtain the contour data of the tunnel lining and the working distance of the color camera; the apparent image data of the tunnel lining is obtained by combining the working distance and installation posture information of the color camera. The image data is adaptively cropped to obtain cropped tunnel lining surface image data; the cropped tunnel lining surface image data is data spliced ​​to obtain the full cross-section data of the tunnel lining. In this way, by adaptively cropping and data splicing the color surface image data, the amount of tunnel lining color image data can be reduced and the data processing efficiency can be improved while ensuring resolution and accuracy. In addition, the present invention also uses an industrial camera to obtain the landscape image data directly in front of and obliquely above the tunnel detection equipment, and controls the automatic opening and closing of the data acquisition and storage module according to the landscape image data, so that data acquisition and storage are only performed when needed, reducing the amount of data processed by the measurement data. Compared with the use of grayscale image data in the prior art, the present invention can more realistically reflect the tunnel lining wall conditions by using tunnel lining color image data, and can more accurately detect cracks, water leakage, peeling and other diseases.

[0140] Optionally, the installation posture information of the color camera includes the relative coordinate position of the adjacent camera installation, the camera viewing direction and the camera viewing range information. The data clipping module 250 is also used to obtain the first overlapping area and the overlapping boundary position in the apparent image data of the tunnel lining measured by the adjacent camera in combination with the working distance and the installation posture information of the color camera; obtain the protection extension area in the first overlapping area in combination with the first overlapping area, the overlapping boundary position and the preset overlapping area protection extension width; and clip the image data except the protection extension area in the first overlapping area.

[0141] Optionally, the data cropping module is also used to obtain a second overlapping area in the cropped tunnel lining surface image data in combination with the overlapping boundary position and a preset overlapping area search radius; accurately crop the second overlapping area by matching feature points with the same name; and splice the accurately cropped image data in combination with the timing of image data acquisition and the measurement angle of the color camera to obtain full-section data of the tunnel lining.

[0142] Optionally, the landscape measurement system is also used to use the binocular vision principle to determine a first preset area directly in front of the tunnel detection equipment, and to count the landscape image data within the first preset area to obtain a first average brightness of the landscape image data within the first preset area; use the binocular vision principle to determine a second preset area obliquely above the tunnel detection equipment, and to count the landscape image data within the second preset area to obtain a second average brightness of the landscape image data within the second preset area; use the change characteristics of the first average brightness and the second average brightness along the detection mileage to determine whether the tunnel detection equipment enters or leaves the tunnel; if the tunnel detection equipment enters the tunnel, turn on the data acquisition and storage module; if the tunnel detection equipment leaves the tunnel, turn off the data acquisition and storage module.

[0143] Optionally, the landscape measurement system is also used to calculate, using a preset statistical frame interval, a first average brightness difference corresponding to the first average brightness of the preset statistical frame interval and a second average brightness difference corresponding to the second average brightness; when the absolute value of the first average brightness difference is greater than or equal to a first preset brightness difference threshold, and the absolute value of the second average brightness difference is greater than or equal to a second preset brightness difference threshold, determine whether the tunnel detection device has entered or left the tunnel based on the first average brightness difference.

[0144] Optionally, the landscape measurement system is also used to determine that the tunnel detection device has entered a tunnel if the absolute value of the first average brightness difference is greater than or equal to a third preset brightness difference threshold, and the first average brightness difference is less than 0; or, to determine that the tunnel detection device has entered a tunnel if the absolute value of the first average brightness difference is less than a third preset brightness difference threshold, and the first average brightness difference is greater than 0; to determine that the tunnel detection device has left the tunnel if the absolute value of the first average brightness difference is greater than or equal to the third preset brightness difference threshold, and the first average brightness difference is greater than 0; or, to determine that the tunnel detection device has left the tunnel if the absolute value of the first average brightness difference is less than the third preset brightness difference threshold, and the first average brightness difference is less than 0.

[0145] Optionally, the color camera, the fill light system and the three-dimensional measurement sensor constitute a tunnel lining measurement system, and the tunnel lining measurement system is installed on a rotating bracket; wherein the rotating bracket can drive the tunnel lining measurement system to rotate together to adjust the overall measurement posture of the tunnel measurement system to achieve measurement of different areas of the tunnel lining.

[0146] Optionally, during the driving of the tunnel detection equipment, the tunnel lining measurement system is in a working state; wherein, when the data acquisition and storage module is in a closed state, the data measured by the tunnel lining measurement system is not stored; when the data acquisition and storage module is in an open state, the apparent image data of the tunnel lining in the data measured by the tunnel lining measurement system is cropped, and the cropped apparent image data and the tunnel lining contour data are stored.

[0147] Optionally, the measurement platform in this embodiment is a mobile measurement vehicle, and a positioning system is installed in the measurement platform, and the positioning system includes one or more of GNSS, an encoder, and a control network.

[0148] Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3 As shown, the electronic device may include: a processor 301, a communications interface 302, a memory 303 and a communication bus 304, wherein the processor 301, the communications interface 302 and the memory 303 communicate with each other through the communication bus 304. The processor 301 may call the logic instructions in the memory 303 to execute a tunnel detection method based on a color image, the method comprising:

[0149] In the case where the color camera is supplemented with light by the supplementary light system, the color camera is used to obtain apparent image data of the tunnel lining;

[0150] Using a three-dimensional measurement sensor to obtain tunnel lining profile data and the working distance of the color camera;

[0151] Adaptively cropping the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera to obtain cropped apparent image data of the tunnel lining;

[0152] Performing data splicing on the cropped tunnel lining surface image data to obtain full-section data of the tunnel lining;

[0153] An industrial camera is used to obtain landscape image data directly in front of and diagonally above the tunnel detection equipment, and the automatic opening and closing of the data acquisition and storage module is controlled according to the landscape image data. The data acquisition and storage module is used to realize the acquisition and storage of the apparent image data of the tunnel lining and the contour data of the tunnel lining.

[0154] In addition, the logic instructions in the above-mentioned memory 303 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0155] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program can be stored in a non-transitory computer-readable storage medium, when the computer program is executed by a processor, the computer can execute the color image-based tunnel detection method provided by the above methods, the method comprising:

[0156] In the case where the color camera is supplemented with light by the supplementary light system, the color camera is used to obtain apparent image data of the tunnel lining;

[0157] Using a three-dimensional measurement sensor to obtain tunnel lining profile data and the working distance of the color camera;

[0158] Adaptively cropping the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera to obtain cropped apparent image data of the tunnel lining;

[0159] Performing data splicing on the cropped tunnel lining surface image data to obtain full-section data of the tunnel lining;

[0160] An industrial camera is used to obtain landscape image data directly in front of and diagonally above the tunnel detection equipment, and the automatic opening and closing of the data acquisition and storage module is controlled according to the landscape image data. The data acquisition and storage module is used to realize the acquisition and storage of the apparent image data of the tunnel lining and the contour data of the tunnel lining.

[0161] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to perform the color image-based tunnel detection method provided by the above methods, the method comprising:

[0162] In the case where the color camera is supplemented with light by the supplementary light system, the color camera is used to obtain apparent image data of the tunnel lining;

[0163] Using a three-dimensional measurement sensor to obtain tunnel lining profile data and the working distance of the color camera;

[0164] Adaptively cropping the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera to obtain cropped apparent image data of the tunnel lining;

[0165] Performing data splicing on the cropped tunnel lining surface image data to obtain full-section data of the tunnel lining;

[0166] An industrial camera is used to obtain landscape image data directly in front of and diagonally above the tunnel detection equipment, and the automatic opening and closing of the data acquisition and storage module is controlled according to the landscape image data. The data acquisition and storage module is used to realize the acquisition and storage of the apparent image data of the tunnel lining and the contour data of the tunnel lining.

[0167] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0168] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0169] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A tunnel detection method based on color images, characterized in that: include: In the case where the color camera is supplemented with light by the supplementary light system, the color camera is used to obtain apparent image data of the tunnel lining; Using a three-dimensional measurement sensor to obtain tunnel lining profile data and the working distance of the color camera; Adaptively cropping the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera to obtain cropped apparent image data of the tunnel lining; Performing data splicing on the cropped tunnel lining surface image data to obtain full-section data of the tunnel lining; Using an industrial camera to obtain landscape image data directly in front of and obliquely above the tunnel detection equipment, and controlling the automatic opening and closing of a data acquisition and storage module according to the landscape image data, the data acquisition and storage module is used to realize the acquisition and storage of the apparent image data of the tunnel lining and the contour data of the tunnel lining; The installation posture information of the color camera includes the relative coordinate position of the adjacent camera installation, the camera viewing angle direction and the camera viewing angle range information; The method of adaptively cropping the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera comprises: In combination with the working distance and installation posture information of the color camera, a first overlapping area and an overlapping boundary position in the apparent image data of the tunnel lining measured by adjacent cameras are obtained; the first overlapping area refers to an overlapping area in the apparent image data of the tunnel lining measured by adjacent cameras; Acquire a protection extension area in the first overlapping area by combining the first overlapping area, the overlapping boundary position, and a preset overlapping area protection extension width; the protection extension area is used to retain edge features or important information in the image; Cut out the image data except the protection extension area in the first overlapping area; The step of performing data splicing on the cropped tunnel lining surface image data to obtain tunnel lining full section data includes: In combination with a preset overlapping area search radius, a second overlapping area in the cropped tunnel lining surface image data is acquired by expanding outwards a certain distance from the overlapping boundary position of the first overlapping area; By matching feature points with the same name, the second overlapping area is precisely cropped; Combined with the timing of image data acquisition and the measurement angle of the color camera, the precisely cropped image data are spliced ​​to obtain the full-section data of the tunnel lining.

2. The tunnel detection method based on color images according to claim 1, characterized in that: The method of using an industrial camera to obtain landscape image data directly in front of and obliquely above the tunnel detection equipment and controlling the automatic opening and closing of a data acquisition and storage module according to the landscape image data includes: Using binocular vision principle to determine a first preset area in front of the tunnel detection device, and statistically analyzing the landscape image data within the first preset area to obtain a first average brightness of the landscape image data within the first preset area; Using binocular vision principle to determine a second preset area range obliquely above the tunnel detection device, and statistically analyzing the landscape image data within the second preset area range to obtain a second average brightness of the landscape image data within the second preset area range; Using the variation characteristics of the first average brightness and the second average brightness along the detection mileage, determining whether the tunnel detection device enters or leaves the tunnel; If the tunnel detection equipment enters the tunnel, the data collection and storage module is turned on; If the tunnel detection device leaves the tunnel, the data acquisition and storage module is turned off.

3. The tunnel detection method based on color images according to claim 2 is characterized in that: The method of using the variation characteristics of the first average brightness and the second average brightness along the detection mileage to determine whether the tunnel detection device enters or leaves the tunnel includes: Using a preset statistical frame interval, calculating a first average brightness difference corresponding to the first average brightness and a second average brightness difference corresponding to the second average brightness in the preset statistical frame interval; When the absolute value of the first average brightness difference is greater than or equal to a first preset brightness difference threshold, and the absolute value of the second average brightness difference is greater than or equal to a second preset brightness difference threshold, it is determined whether the tunnel detection device enters or leaves the tunnel based on the first average brightness difference.

4. The tunnel detection method based on color images according to claim 3 is characterized in that: The determining, according to the first average brightness difference, whether the tunnel detection device has entered or left the tunnel comprises: If the absolute value of the first average brightness difference is greater than or equal to a third preset brightness difference threshold, and the first average brightness difference is less than 0, it is determined that the tunnel detection device enters a tunnel; or, If the absolute value of the first average brightness difference is less than a third preset brightness difference threshold, and the first average brightness difference is greater than 0, it is determined that the tunnel detection device enters a tunnel; If the absolute value of the first average brightness difference is greater than or equal to a third preset brightness difference threshold, and the first average brightness difference is greater than 0, it is determined that the tunnel detection device has left the tunnel; or, If the absolute value of the first average brightness difference is less than a third preset brightness difference threshold, and the first average brightness difference is less than 0, it is determined that the tunnel detection device has left the tunnel.

5. The tunnel detection method based on color images according to claim 1, characterized in that: The color camera, the fill light system and the three-dimensional measurement sensor constitute a tunnel lining measurement system, and the tunnel lining measurement system is installed on a rotating bracket; The rotating bracket can drive the tunnel lining measurement system to rotate together to adjust the overall measurement posture of the tunnel lining measurement system to achieve measurement of different areas of the tunnel lining.

6. The tunnel detection method based on color images according to any one of claims 1 to 5, characterized in that: Also includes: During the driving process of the tunnel detection equipment, the tunnel lining measurement system is in a working state; wherein, when the data acquisition and storage module is in a closed state, the data measured by the tunnel lining measurement system is not stored; When the data acquisition and storage module is in the on state, the apparent image data of the tunnel lining in the data measured by the tunnel lining measurement system is cropped, and the cropped apparent image data and the tunnel lining contour data are stored.

7. A tunnel detection device based on color images, characterized in that: It includes a fill light system, a color camera, a three-dimensional measurement sensor, an industrial camera, a data clipping module, a data splicing module, a data acquisition and storage module, and a measurement platform, wherein the fill light system, the color camera, the three-dimensional measurement sensor, the industrial camera, the data acquisition module, the data splicing module, and the data acquisition and storage module are all integrated on the measurement platform; The fill light system is used to fill light for the color camera; The color camera is used to obtain apparent image data of the tunnel lining when the color camera is supplemented with light by the supplementary light system; The three-dimensional measurement sensor is used to obtain tunnel lining profile data and the working distance of the color camera; The data cropping module is used to adaptively crop the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera to obtain cropped apparent image data of the tunnel lining; The data splicing module is used to perform data splicing on the cropped tunnel lining surface image data to obtain the tunnel lining full section data; The industrial camera is used to form a landscape measurement system for acquiring landscape image data directly in front of and obliquely above the tunnel detection equipment, and the automatic opening and closing of the data acquisition and storage module is controlled according to the landscape image data; The data acquisition and storage module is used to realize the acquisition and storage of the apparent image data of the tunnel lining and the contour data of the tunnel lining; The installation posture information of the color camera includes the relative coordinate position of the adjacent camera installation, the camera viewing angle direction and the camera viewing angle range information; The method of adaptively cropping the apparent image data of the tunnel lining in combination with the working distance and installation posture information of the color camera comprises: In combination with the working distance and installation posture information of the color camera, a first overlapping area and an overlapping boundary position in the apparent image data of the tunnel lining measured by adjacent cameras are obtained; the first overlapping area refers to an overlapping area in the apparent image data of the tunnel lining measured by adjacent cameras; Acquire a protection extension area in the first overlapping area by combining the first overlapping area, the overlapping boundary position, and a preset overlapping area protection extension width; the protection extension area is used to retain edge features or important information in the image; Cut out the image data except the protection extension area in the first overlapping area; The step of performing data splicing on the cropped tunnel lining surface image data to obtain tunnel lining full section data includes: In combination with a preset overlapping area search radius, a second overlapping area in the cropped tunnel lining surface image data is acquired by expanding outwards a certain distance from the overlapping boundary position of the first overlapping area; By matching feature points with the same name, the second overlapping area is precisely cropped; Combined with the timing of image data acquisition and the measurement angle of the color camera, the precisely cropped image data are spliced ​​to obtain the full-section data of the tunnel lining.

8. The color image-based tunnel detection equipment according to claim 7, characterized in that: The measuring platform is a mobile measuring vehicle, and a positioning system is installed in the measuring platform. The positioning system includes one or more of GNSS, an encoder, and a control network.

Images