CN113776462A - High-speed rail no-ballast rail bearing platform three-dimensional shape detection method based on digital image - Google Patents
High-speed rail no-ballast rail bearing platform three-dimensional shape detection method based on digital image Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
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Abstract
The invention discloses a high-speed rail no-containment rail bearing platform three-dimensional shape detection method based on digital images, which comprises the steps that a binocular vision camera and a total station prism measuring unit form a detection system, prism groups in the binocular vision camera and the total station prism measuring unit are fixedly arranged on a measuring rack together, and camera coordinates are established; reconstructing three-dimensional point cloud contour data of the rail bearing platform by using a digital image which is obtained by shooting through a binocular vision camera and contains natural texture on the surface of the rail bearing platform; and the total station prism measurement unit obtains the position of each prism in the prism group in the CP III control network, establishes the relation between a camera coordinate system and the CP III control network, and unifies the three-dimensional point cloud profile data of the track bearing table under the CP III control network according to the relation, thereby realizing the three-dimensional shape detection of the track bearing table. The invention greatly improves the detection efficiency, and the measurement precision meets the requirement of realizing the working condition.
Description
Technical Field
The invention relates to construction of a ballastless track, in particular to a method for detecting three-dimensional morphology of a ballastless track bearing platform.
Background
The high-speed railway has high operation speed and high density and has high requirements on the smoothness and the stability of the track. In order to ensure the smoothness and stability of the high-speed railway track, the three-dimensional space appearance of a rail bearing platform on a track slab needs to be measured before the high-speed railway track is constructed and laid.
At present, in practical application, the detection of the rail bearing platform is mainly manual measurement, the measurement efficiency is low, the labor intensity is high, and the detection requirement of a modern high-speed railway cannot be met.
The utility model discloses a measurement frock is kept silent to the bearing rail platform, and when measuring on the spot, place this measurement frock and contact with bearing rail platform notch, use the total powerstation to measure the prism on the measurement frock, remove the measurement frock and detect on each bearing rail platform one by one, until accomplishing the detection of all bearing rail platforms on a slice CPTSIII type track board in the utility model patent application document of publication number CN 206208175U, the name is "CRTSIII type track board bearing rail platform measurement frock". The method is simple to operate, but has low efficiency, and is difficult to meet the requirement of high-efficiency and high-precision measurement on a construction site.
The invention discloses a detection method for rapidly acquiring surface data of a track slab by combining an absolute laser tracker and a handheld laser scanner, wherein the detection method is disclosed in the invention patent application with the publication number of CN 105906219A and is named as a method for detecting the deviation of the appearance dimension of a CRTSIII type track slab. However, the method only aims at the factory detection of a track slab processing workshop, and cannot be applied to the detection of a track bearing platform on a track slab on a construction site, and meanwhile, the used absolute laser tracker and the used handheld laser tracker lack use conditions in the civil engineering and iron construction industries.
In the chinese patent application publication No. CN 111486831 a entitled "detection apparatus and method for ballastless track supporting platform measurement tool", a method for measuring key dimension information of a supporting platform using a supporting platform detection mold including a precision prism bar is disclosed, and the measurement mold is elastically connected to a lifting bracket for realizing automatic mold placement. The method reduces manual intervention to a certain extent, but the position of a measuring die needs to be continuously adjusted during each measurement, the measuring process is long, meanwhile, the measuring information only comprises the elevation data of the track, and the information quantity is small, so that the requirement of actual construction on omnibearing and multidimensional three-dimensional topography data is difficult to meet.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides a digital image-based three-dimensional shape detection method for a high-speed rail no-tie rail bearing platform, which realizes high-efficiency and high-precision measurement of the spatial shapes of a plurality of bearing platforms in an outdoor environment by integrating an optical measurement method and comprises single bearing platform shape measurement and relative position measurement of the plurality of bearing platforms; the measurement data can be used for fitting and predicting the three-dimensional trend of the track after the track is laid, guiding subsequent construction and material purchase, and improving the track laying efficiency and quality.
The invention adopts the following technical scheme for solving the technical problems:
the invention relates to a high-speed rail no-ballast rail bearing platform three-dimensional shape detection method based on digital images, which is characterized by comprising the following steps:
setting a detection system which comprises a binocular vision camera and a total station prism measuring unit;
the binocular vision camera consists of two cameras, namely a first camera and a second camera, wherein the two cameras are fixedly installed at the same height position of the detection rack and are respectively arranged on the left side and the right side of the detection rack;
the total station prism measuring unit consists of a total station and a prism group fixedly arranged on the detection rack; the prism group comprises at least 4 prisms;
the binocular vision camera obtains a digital image containing surface natural textures of the rail bearing platform through shooting, and three-dimensional point cloud contour data of the rail bearing platform are reconstructed through image processing of the digital image;
the total station prism measurement unit obtains the position of each prism in the prism group in the CP III control network through measurement, and therefore the relation between a camera coordinate system of the binocular vision camera and the CP III control network is obtained;
and unifying the three-dimensional point cloud profile data of the rail bearing platform under the CP III control network according to the relation between the camera coordinate system and the CP III control network, so as to realize the detection of the three-dimensional shape of the rail bearing platform.
The method for detecting the three-dimensional morphology of the high-speed rail ballastless track bearing platform based on the digital image is also characterized in that:
the method comprises the following steps of arranging a movable detection rack, fixedly arranging a binocular vision camera on the detection rack, and fixedly arranging a prism group in a total station prism measurement unit; calibrating parameters of the binocular vision camera, determining a camera coordinate system of the binocular vision camera, and calibrating three-dimensional coordinates of each prism in the prism group in the camera coordinate system;
the detection method comprises the following steps:
and 5, moving the detection rack and the total station along the track slab of the section to be detected, keeping the total station and each prism in the measurement rack at a set distance, and repeating the steps 2-4 to realize the three-dimensional shape detection of all the rail bearing tables in the section to be detected.
The method for detecting the three-dimensional morphology of the high-speed rail ballastless track bearing platform based on the digital image is also characterized in that:
the parameter calibration is carried out on the binocular vision camera, a camera coordinate system of the binocular vision camera is determined, and the three-dimensional coordinates of each prism in the calibration prism group in the camera coordinate system are carried out according to the following modes:
step 3.1, adjusting a first camera and a second camera in the binocular vision camera to enable the first camera and the second camera to simultaneously and clearly image relative to the rail bearing platform to be measured; respectively obtaining calibration images of a calibration plate by using the first camera and the second camera through image acquisition, calibrating the first camera and the second camera by using the calibration images of the first camera and the second camera and calibration plate information, calculating camera parameters of the first camera and the second camera, and establishing a camera coordinate system on the first camera;
the calibration plate information in the step comprises the distance between 3 non-collinear feature points on the calibration plate;
the camera parameters include: the first camera and the second camera respectively have equivalent focal length, principal point coordinates and distortion parameters; the position relation from the first camera to the second camera comprises an angle relation between an optical axis of the first camera and an optical axis of the second camera, and a distance relation between an optical center of the first camera and an optical center of the second camera;
step 3.2, erecting a total station at a set distance from the measuring rack, establishing a total station coordinate system, measuring three-dimensional coordinates of the prisms on the measuring rack one by the total station, repeatedly measuring for multiple times, and taking an average value as the three-dimensional coordinates of the prisms in the total station coordinate system;
3.3, placing a central cross circular mark point in the area to be measured, and shooting the circular mark point by the first camera and the second camera to obtain a mark point three-dimensional coordinate of the circular mark point under a camera coordinate system; measuring the central cross of the circular mark point by a total station and a prism centering rod to obtain the three-dimensional coordinates of the mark point of the circular mark point in a total station coordinate system;
3.4, randomly moving the circular mark points in the area to be measured, repeating the step 3.3, obtaining three-dimensional coordinates of the circular mark points at different positions in a camera coordinate system and a total station coordinate system, and calculating to obtain a coordinate transformation relation between the camera coordinate system and the total station coordinate system; the area to be measured is a space area defined according to the surface profile of the rail bearing platform;
and 3.5, calculating to obtain the three-dimensional coordinates of the prism group in the camera coordinate system according to the three-dimensional coordinates of the prisms in the total station coordinate system obtained in the step 3.2 and the transformation relation between the camera coordinate system and the total station coordinate system in the step 2.4, and completing calibration.
The method for detecting the three-dimensional morphology of the high-speed rail ballastless track bearing platform based on the digital image is also characterized in that: the CP III control network is a third-stage foundation pile control network in a railway engineering measurement plane control network of a ballastless track passenger dedicated line; the CP III control network is a three-dimensional rectangular coordinate system which is arranged on a fixed point and does not move along with the detection rack, or is a GPS control network and a Beidou control network.
Compared with the prior art, the invention has the beneficial effects that:
1. the method is characterized in that pictures of the rail bearing platform in a binocular camera are shot based on binocular stereoscopic vision, a digital image correlation method is used for performing correlation calculation by utilizing the specific concrete texture of the surface of the rail bearing platform, a projector and a laser transmitter are not needed, and the measurement of the three-dimensional surface profile of the rail bearing platform is realized.
2. Compared with the method for measuring by adopting a laser scanner in the prior art, the method has the advantages of short measuring time, high measuring efficiency and capability of completing measurement by acquiring pictures at one time.
3. The invention keeps the measuring precision below 0.1mm and meets the requirements of actual working conditions.
4. The method realizes the conversion of the relation between the camera coordinate system and the CP III control network by pre-measuring the position of the prism in the camera coordinate system, and the used total station and the prism are all measuring instruments which are already mastered by a construction unit, so that the method does not need to separately train measuring personnel and is easy to accurately implement.
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FIG. 1 is a schematic view of the detection method of the present invention;
FIG. 2 is a schematic view of a measuring rack in the detecting method of the present invention;
FIG. 3 is a schematic diagram of a calibration process of a measuring stand and a total station in the detection method of the present invention;
FIGS. 4a and 4b are front and top views, respectively, of a rail bearing platform;
reference numbers in the figures: the system comprises a detection rack 1, a first prism 2, a second prism 3, a first camera 4, a second camera 5, a total station 6, a track plate 7, a track bearing table 8, a prism centering rod 9 and a circular mark point 10.
Detailed Description
Referring to fig. 1, 2 and 3, the detection system is arranged for realizing the three-dimensional shape detection of the high-speed rail ballastless track bearing platform based on digital images, and comprises a binocular vision camera and a total station prism measurement unit; the binocular vision camera comprises a first camera 4 and a second camera 5 which are respectively arranged on the same height position of the detection rack 1 and are respectively arranged on the left side and the right side of the detection rack 1; in the specific implementation, the binocular vision camera consists of two industrial cameras and a matched lens, the model of the camera is Haekwovens MV-CH089-10UM, the resolution is 4096 multiplied by 2160 pixels, and the length-width ratio is 16: 9, approximating the shape of a single support rail platform; the lens matched with the industrial camera is a Haokangwei MVL-KF2528M-12MP lens with 25mm focus, and the track bearing platform shot at the distance of 1.5 meters can occupy the main part of the image by selecting the lens with 25mm focus; the two cameras are fixedly installed on a cross beam of the detection rack, the height from the ground is 1.5 m, the distance between the cameras is 410 mm, and the installation included angle is 16.3 degrees.
The total station prism measuring unit consists of a total station and a prism group fixedly arranged on the detection rack 1; the prism group comprises at least 4 prisms, wherein 5 prisms are arranged in the prism group, two prisms face one side of the rail bearing table to be tested, and the other three prisms are arranged on one side deviating from the rail bearing table to be tested; in fig. 2, the first prism 2 and the second prism 3 are indicated by reference numerals, respectively, and there are other prisms located at different positions; in fig. 1, binocular vision cameras are respectively arranged on two sides of a detection frame 1 and used for simultaneously detecting two rail bearing platforms which are respectively arranged on two sides of a rail plate, so that the detection efficiency is improved.
The detection method comprises the following steps: a binocular vision camera obtains a digital image containing surface natural textures of the rail bearing platform 8 through shooting, and three-dimensional point cloud contour data of the rail bearing platform are reconstructed through image processing of the digital image; the total station prism measurement unit obtains the position of each prism in the prism group in the CP III control network through measurement, and therefore the relation between a camera coordinate system of the binocular vision camera and the CP III control network is obtained; and unifying the three-dimensional point cloud profile data of the rail bearing platform 8 to the CP III control network according to the relation between the camera coordinate system and the CP III control network, thereby realizing the detection of the three-dimensional shape of the rail bearing platform.
As shown in fig. 1, 2 and 3, in the present embodiment, a movable inspection frame 1 is provided, a binocular vision camera is fixedly arranged on the inspection frame 1, and a prism group in a total station prism measurement unit is fixedly arranged; calibrating parameters of a binocular vision camera, determining a camera coordinate system M of the binocular vision camera, and calibrating three-dimensional coordinates of each prism in a prism group in the camera coordinate system M; the detection method comprises the following steps:
And 5, moving the detection rack 1 and the total station along the track plate 7 of the section to be detected, keeping the total station and each prism in the measurement rack at a set distance, and repeating the steps 2-4 to realize the three-dimensional shape detection of all the rail bearing tables 8 in the section to be detected.
In this embodiment, the parameter calibration is performed on the binocular vision camera, the camera coordinate system M of the binocular vision camera is determined, and the three-dimensional coordinates of each prism in the prism group in the camera coordinate system M are calibrated in the following manner:
place single support rail platform in the laboratory, will detect the frame and remove to support rail platform position top, adjust first camera 4 and second camera 5 in the binocular vision camera, make first camera 4 and second camera 5 can be clear formation of image simultaneously to the support rail platform that awaits measuring. In consideration of sufficient illumination in an outdoor environment, extra light supplement of a lamp needs to be arranged in the laboratory calibration process. After the binocular vision camera is adjusted to clearly image, the rail bearing platform is removed, and the calibration work of the detection rack is started.
A1, placing a single rail bearing table in a laboratory, moving a detection rack above the position of the rail bearing table, and adjusting a first camera 4 and a second camera 5 in a binocular vision camera to enable the first camera 4 and the second camera 5 to simultaneously and clearly image the rail bearing table to be detected; and then, removing the rail bearing table, placing a calibration plate at the position of the rail bearing table, respectively obtaining calibration images of the calibration plate by using the first camera 4 and the second camera 5 through image acquisition, randomly moving the calibration plate, simultaneously keeping the calibration plate in the range of the area to be measured, carrying out image acquisition again, repeating the operation for at least 14 times, carrying out calibration calculation on the first camera 4 and the second camera 5 by using the calibration images and the calibration plate information obtained by shooting by using the first camera 4 and the second camera 5, obtaining camera parameters of the first camera 4 and the second camera 5, establishing a camera coordinate system M on the first camera 4, wherein the coordinate origin is at the optical center of the first camera 4, the xy plane is overlapped with the target surface of the first camera 4, and the z axis is perpendicular to the target surface of the first camera 4 and points to the area to be measured.
The calibration plate information comprises the distance between 3 non-collinear feature points on the calibration plate;
the camera parameters include: the equivalent focal length, principal point coordinates and distortion parameters of each of the first camera 4 and the second camera 5; the positional relationship of the first camera 4 to the second camera 5 includes an angular relationship between the optical axis of the first camera 4 and the optical axis of the second camera 5, a distance relationship between the optical center of the first camera 4 and the optical center of the second camera 5;
step a2, erecting a total station 6 at a set distance from the measuring rack 1, establishing a total station coordinate system N by adopting a free station setting method, measuring three-dimensional coordinates of the prisms on the measuring rack 1 one by the total station 6, repeatedly measuring for multiple times, and taking an average value as a prism three-dimensional coordinate of each prism in the total station coordinate system N
Wherein: o is from 1 to 5.
Step s3, placing the rail bearing platform 8 back into the area to be measured, placing a central cross circular mark point 10 in the area to be measured, wherein the circular mark point 10 is made of a reflective material and is adhered to an aluminum plate with the thickness of 2mm, shooting the circular mark point 10 by the first camera 4 and the second camera 5, using a findcircle function in opencv to perform point location on the circular mark point in the images shot by the first camera 4 and the second camera 5, and using the camera parameters obtained in the step a1 to perform reconstruction calculation on the three-dimensional space coordinate value of the circular mark point 10 to obtain the three-dimensional coordinate of the circular mark point 10 under the camera coordinate system M;
measuring the central cross of the circular mark point 10 by the total station 6 and the prism centering rod 9, namely abutting the prism centering rod 9 against the central cross of the circular mark point, adjusting the position of the prism centering rod 9 to enable a horizontal bubble on the prism centering rod to be centered, and measuring the three-dimensional coordinate of the prism of the centering rod by using the total station 6 to obtain the three-dimensional coordinate of the circular mark point 10 under a total station coordinate system N.
Step a4, randomly moving the circular mark points 10 in the area to be measured, repeating step 3.3, and obtaining 20 groups of three-dimensional coordinates of the circular mark points 10 at different positions in the camera coordinate system M
Wherein: i from 1 to 20, and three-dimensional coordinates in a total station coordinate system N
Wherein: i from 1 to 20, thereby obtaining the coordinate transformation relation R between the camera coordinate system M and the total station coordinate system N through calculationN-MAnd TN-M；
The area to be measured is a space area defined according to the surface profile of the rail bearing platform;
step a5, obtaining prism three-dimensional coordinates of each prism in the total station coordinate system N according to the step a2 ((
o from 1 to 5) and step a4 transformation relation R between camera coordinate system M and total station coordinate system NN-MAnd TN -MCalculating to obtain three-dimensional coordinates of the prism group in the camera coordinate system M (
o from 1 to 5):
and completing calibration.
The CP III control network is a third-stage foundation pile control network in a railway engineering measurement plane control network of a ballastless track passenger dedicated line; the CP III control network or the GPS control network and the Beidou control network is a three-dimensional rectangular coordinate system which is established on a fixed point and does not move along with the detection rack.
The precision of the invention can reach below 0.1mm, and the invention meets the requirements of actual working conditions.
And (3) verifying the measurement precision:
in an outdoor environment, the rail bearing platform a and the rail bearing platform B on a single rail plate are detected by the method of the invention, and are simultaneously detected by the three-dimensional laser scanner, and relevant dimension information is obtained as shown in table 1, including the inner inclination angles α 1 and α 2 of the rail bearing platform shown in fig. 4a and 4B, and the bottom edge width L of the rail bearing platform.
TABLE 1
Compared with a three-dimensional laser scanner, the method has short measurement time (only one-time picture acquisition is needed), and high measurement efficiency; when the method is compared with the laser scanner in terms of accuracy, compared with the nominal accuracy of 0.02mm of the laser scanner, the accuracy of the method is slightly reduced, but still below 0.1mm, and the method meets the requirement of actual working conditions.
In addition, the method realizes the conversion of the relation between the camera coordinate system and the CP III control network by measuring the position of the prism in the camera coordinate system in advance, and the total station and the prism are measuring instruments which are already mastered by a construction unit, so that the individual training of measuring personnel is not needed.
Claims (4)
1. A high-speed rail no-ballast rail bearing platform three-dimensional morphology detection method based on digital images is characterized by comprising the following steps:
setting a detection system which comprises a binocular vision camera and a total station prism measuring unit;
the binocular vision camera consists of two cameras, namely a first camera (4) and a second camera (5), wherein the two cameras are fixedly installed at the same height position of the detection rack (1) and are respectively arranged at the left side and the right side of the detection rack (1);
the total station prism measuring unit consists of a total station and a prism group fixedly arranged on the detection rack (1); the prism group comprises at least 4 prisms;
the binocular vision camera obtains a digital image containing surface natural textures of a rail bearing platform (8) through shooting, and three-dimensional point cloud contour data of the rail bearing platform are reconstructed through image processing of the digital image;
the total station prism measurement unit obtains the position of each prism in the prism group in the CP III control network through measurement, and therefore the relation between a camera coordinate system of the binocular vision camera and the CP III control network is obtained;
and unifying the three-dimensional point cloud profile data of the rail bearing platform (8) to the CP III control network according to the relation between the camera coordinate system and the CP III control network, thereby realizing the detection of the three-dimensional shape of the rail bearing platform.
2. The digital image-based three-dimensional topography detection method for the high-speed rail ballastless track bearing platform of claim 1, wherein the method comprises the following steps:
the method comprises the following steps of arranging a movable detection rack (1), fixedly arranging a binocular vision camera on the detection rack (1), and fixedly arranging a prism group in a total station prism measurement unit; performing parameter calibration on the binocular vision camera, determining a camera coordinate system (M) of the binocular vision camera, and calibrating three-dimensional coordinates of each prism in the prism group in the camera coordinate system (M);
the detection method comprises the following steps:
step 1, placing the detection rack (1) on a track slab of a section to be detected, and enabling a rail bearing platform to be detected to be in a central area of a visual field of a binocular vision camera; erecting a total station at a set distance from the detection rack (1), and erecting a CP III control network by adopting a method of freely setting station and marking corner intersection;
step 2, shooting by the binocular vision camera to obtain a digital image containing natural texture on the surface of the rail bearing platform to be measured, numbering and storing; meanwhile, acquiring three-dimensional coordinates of each prism on the detection rack (1) in a CP III control network by using a total station, numbering and storing;
step 3, based on an image matching algorithm, performing digital image processing on the digital image containing the natural texture of the surface of the rail bearing platform to be detected, and calculating to obtain pixel coordinates of characteristic points of the surface of the rail bearing platform in the digital image; aiming at the pixel coordinates, performing three-dimensional reconstruction according to camera parameters calibrated by a binocular vision camera, thereby obtaining three-dimensional point cloud profile data of the rail bearing platform under a camera coordinate system (M);
step 4, establishing a coordinate transformation relation between a camera coordinate system (M) and the CP III control network according to the three-dimensional coordinates of the prisms in the CP III control network and the three-dimensional coordinates of the prisms in the camera coordinate system (M), and converting the three-dimensional point cloud profile data of the track bearing platform in the camera coordinate system (M) into the CP III control network according to the coordinate transformation relation;
and 5, moving the detection rack (1) and the total station along the track slab of the section to be detected, keeping the total station and each prism in the measurement rack at a set distance, and repeating the steps 2-4 to realize the three-dimensional shape detection of all the rail bearing tables in the section to be detected.
3. The digital image-based three-dimensional topography detection method for the high-speed rail ballastless track bearing platform of claim 2, wherein the method comprises the following steps:
the parameter calibration is carried out on the binocular vision camera, a camera coordinate system (M) of the binocular vision camera is determined, and the three-dimensional coordinates of each prism in the calibration prism group in the camera coordinate system (M) are carried out in the following mode:
step 3.1, adjusting a first camera (4) and a second camera (5) in the binocular vision camera to enable the first camera (4) and the second camera (5) to simultaneously and clearly image a rail bearing platform to be measured; respectively obtaining calibration images of a calibration plate by using the first camera (4) and the second camera (5) through image acquisition, calibrating the first camera (4) and the second camera (5) by using the calibration images of the first camera (4) and the second camera (5) and calibration plate information, calculating camera parameters of the first camera (4) and the second camera (5), and establishing a camera coordinate system (M) on the first camera (4);
the calibration plate information in the step comprises the distance between 3 non-collinear feature points on the calibration plate;
the camera parameters include: the equivalent focal length, principal point coordinates and distortion parameters of the first camera (4) and the second camera (5) respectively; the position relation from the first camera (4) to the second camera (5) comprises an angle relation between an optical axis of the first camera (4) and an optical axis of the second camera (5) and a distance relation between an optical center of the first camera (4) and an optical center of the second camera (5);
step 3.2, erecting a total station (6) at a set distance from the measuring rack (1), establishing a total station coordinate system (N), carrying out three-dimensional coordinate measurement on each prism on the measuring rack (1) one by the total station (6), and taking an average value as the prism three-dimensional coordinate of each prism in the total station coordinate system (N) after repeated measurement for many times;
3.3, centering a circular mark point (10) of a cross in the area to be measured, and shooting the circular mark point (10) by the first camera (4) and the second camera (5) to obtain a mark point three-dimensional coordinate of the circular mark point (10) under a camera coordinate system (M); measuring the central cross of the circular mark point (10) by a total station (6) and a prism centering rod (9) to obtain the three-dimensional coordinates of the mark point of the circular mark point (10) under a total station coordinate system (N);
3.4, randomly moving the circular mark point (10) in the area to be measured, and repeating the step 3.3 to obtain three-dimensional coordinates of the circular mark point (10) at different positions in a camera coordinate system (M) and a total station coordinate system (N), so as to calculate and obtain a coordinate transformation relation between the camera coordinate system (M) and the total station coordinate system (N); the area to be measured is a space area defined according to the surface profile of the rail bearing platform;
and 3.5, calculating to obtain the three-dimensional coordinates of the prism group in the camera coordinate system (M) according to the three-dimensional coordinates of the prisms in the total station coordinate system (N) obtained in the step 3.2 and the transformation relation between the camera coordinate system (M) and the total station coordinate system (N) in the step 2.4, and completing calibration.
4. The digital image-based three-dimensional topography detection method for the high-speed rail ballastless track bearing platform of claim 1, wherein the method comprises the following steps: the CP III control network is a third-stage foundation pile control network in a railway engineering measurement plane control network of a ballastless track passenger dedicated line; the CP III control network is a three-dimensional rectangular coordinate system which is arranged on a fixed point and does not move along with the detection rack, or is a GPS control network and a Beidou control network.
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