CN117346689A - Method and apparatus for detecting contour measuring system and readable storage medium - Google Patents
Method and apparatus for detecting contour measuring system and readable storage medium Download PDFInfo
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
- G01B11/2504—Calibration devices
Abstract
The application discloses a detection method, detection equipment and a readable storage medium of a contour measurement system, and relates to the field of contour measurement. Applied to a profile measuring system comprising at least two profile measuring instruments arranged at different positions, the method comprising: determining reference coordinate distribution of a reference point group according to the camera optical axis included angle, the base line distance and the horizontal view angle of the profile measuring instrument; determining the difference distribution of the reference coordinate distribution and the real coordinate distribution as an error transfer coefficient; the error transfer coefficient is determined as a detection value of the profile measuring system. The technical problem that error accumulation is easy to generate in a rotary scanning mode in the related technology, and finally the overall error is large is solved, the technical effect that complex fusion operation is not needed to be carried out on point cloud data, and the overall measurement error of a system is reduced is achieved.
Description
Technical Field
The present application relates to the field of contour metrology, and in particular, to a method and apparatus for detecting a contour measurement system, and a readable storage medium.
Background
A three-dimensional laser profilometer is a device commonly used to measure the shape and size of an object surface. The method analyzes the laser bar image reflected by the object surface by utilizing the principle of a laser triangulation method.
In the related art, when a detected object with a relatively complex surface needs to be detected, a plurality of line laser contour sensors are usually adopted to be loaded on a rotary platform, and measurement of three-dimensional data of the surface is realized through rotary scanning. In the measuring method of the plurality of contour sensors, the rotating platform is matched, so that the measuring coordinate system fusion is required to be carried out after the scanning is completed, and the three-dimensional data of the surface are generated. When errors exist in the contour sensor, the overall error of the system is larger due to the accumulation of errors after the rotation scanning is completed.
Disclosure of Invention
According to the detection method, the detection device and the readable storage medium of the profile measurement system, the technical problem that error accumulation is easy to occur in a rotary scanning mode in the related technology and finally the overall error is large is solved, and the technical effect that complex fusion operation is not needed to be carried out on point cloud data and the overall measurement error of the system is reduced is achieved.
The embodiment of the application provides a detection method of a profile measuring system, which is applied to the profile measuring system, wherein the profile measuring system comprises at least two profile measuring instruments arranged at different positions, and the detection method of the profile measuring system comprises the following steps:
Determining reference coordinate distribution of a reference point group according to the camera optical axis included angle, the base line distance and the horizontal view angle of the profile measuring instrument;
determining the difference distribution of the reference coordinate distribution and the real coordinate distribution as an error transfer coefficient;
the error transfer coefficient is determined as a detection value of the profile measuring system.
Optionally, after the step of determining a difference distribution between the reference coordinate distribution and the true coordinate distribution as an error transfer coefficient, the method includes:
determining calibration parameters through nonlinear optimization based on the internal parameter initial value and the external parameter initial value of the profile measuring instrument;
fitting a laser plane equation based on the calibration parameters according to the collected calibration plate picture data of a plurality of heights;
and determining a pose conversion matrix based on the calibration plate picture data acquired by the profile measuring instrument and the laser plane equation.
Optionally, the step of determining the calibration parameter by nonlinear optimization based on the internal parameter initial value and the external parameter initial value of the profile measuring instrument includes:
determining the initial value of the external parameter according to the pose information of the contour measuring instrument;
extracting characteristic points of a preset number of calibration pictures based on the internal parameter initial value and the external parameter initial value;
Establishing a corresponding relation between the calibration pictures based on the characteristic points;
and calculating the calibration parameters based on nonlinear optimization based on the corresponding relation, the internal parameter and the external parameter.
Optionally, the step of fitting the laser plane equation based on the calibration parameters according to the collected calibration plate picture data of the plurality of heights includes:
determining characteristic point data corresponding to the calibration plate picture data of a preset height sequence;
establishing a characteristic equation based on the characteristic point data and the calibration parameters;
and combining the characteristic equation with the corresponding height value, and fitting the laser plane equation.
Optionally, the step of determining the pose conversion matrix based on the calibration plate picture data acquired by the camera and the laser plane equation includes:
determining a main conversion matrix of a main contour measuring instrument to a system coordinate system based on calibration plate data in the system coordinate system and main calibration plate picture data acquired by the main contour measuring instrument;
determining an auxiliary conversion matrix of the auxiliary contour measuring instrument to the main contour measuring instrument based on the main calibration plate picture data and the auxiliary calibration plate picture data acquired by the auxiliary contour measuring instrument;
And performing matrix calculation according to the auxiliary conversion matrix and the main conversion matrix to obtain the pose conversion matrix.
Optionally, after the step of determining the pose conversion matrix based on the calibration plate image data acquired by the profile measuring instrument and the laser plane equation, the method includes:
the method comprises the steps of processing first point cloud coordinates acquired by a main profile measuring instrument according to a main transformation matrix to obtain three-dimensional coordinates of a first detection point;
processing the second point cloud coordinates acquired by the auxiliary profile measuring instrument according to the pose conversion matrix to obtain three-dimensional coordinates of a second detection point;
and determining a three-dimensional image of the object to be detected based on the three-dimensional coordinates of the first detection point and the three-dimensional coordinates of the second detection point.
Optionally, after the step of determining a difference distribution between the reference coordinate distribution and the true coordinate distribution as an error transfer coefficient, the method includes:
determining a nonlinear function based on the error transfer coefficient;
iterating the nonlinear function based on a preset camera pose distribution;
determining the pose of the target camera according to the approach value of the error overall evaluation value corresponding to the iteration value;
and outputting the prompting information of pose adjustment according to the pose of the target camera and the pose information of the contour measuring instrument.
Optionally, after the step of determining a difference distribution between the reference coordinate distribution and the true coordinate distribution as an error transfer coefficient, the method includes:
determining an overall deviation value corresponding to the error transfer coefficient;
and outputting prompt information of finishing setting the erection position when the total deviation value is smaller than a preset threshold value.
In addition, the application also provides a detection device of the profile measuring system, which comprises a memory, a processor and a detection program of the profile measuring system, wherein the detection program is stored on the memory and can run on the processor, and the processor realizes the steps of the detection method of the profile measuring system when executing the detection program of the profile measuring system.
Furthermore, the present application proposes a computer-readable storage medium, on which a detection program of a contour measurement system is stored, which, when being executed by a processor, implements the steps of the detection method of a contour measurement system as described above.
One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
the reference coordinate distribution of the reference point group is determined according to the included angle of the camera optical axis, the base line distance and the horizontal view angle of the profile measuring instrument, and then the error size existing in the profile measuring system can be determined by analyzing the difference distribution between the reference coordinate distribution and the real coordinate distribution of the reference point group. According to the error transfer coefficient, the error in the system can be compensated, so that the measurement error of the whole system is reduced. By using the error transfer coefficient as a detection value for the profile measuring system, error information can be incorporated into the measurement result, thereby improving the accuracy of the measurement. Therefore, the technical problem that error accumulation is easy to occur in a rotary scanning mode in the related technology, and finally the overall error is large is effectively solved, and the technical effect that complex fusion operation is not needed to be carried out on point cloud data, and the overall measurement error of a system is reduced is achieved.
Drawings
FIG. 1 is a schematic flow chart of a first embodiment of a detection method of a profile measurement system of the present application;
FIG. 2 is a schematic diagram of a contour measurement system according to a first embodiment of a detection method of the contour measurement system of the present application;
FIG. 3 is a schematic diagram of a system structural parameter model of a contour measurement system according to a first embodiment of a detection method of the contour measurement system of the present application;
FIG. 4 is a flowchart of steps S210-S230 in a second embodiment of a detection method of the profile measuring system of the present application;
fig. 5 is a schematic flow chart of refinement of step S230 in the third embodiment of the detection method of the contour measurement system of the present application;
fig. 6 is a schematic diagram of a hardware structure related to an embodiment of a detection device of the profile measurement system of the present application.
Detailed Description
In the related art, a 3D laser profile measuring apparatus mainly uses the principle of laser triangulation to analyze a laser bar image reflected by the surface of an object, so as to realize three-dimensional profile measurement of the measured object. However, for the object with complex surface, a single 3D laser profile measuring instrument is utilized to perform scanning measurement, only one side of information can be obtained in one measurement, and only a single 3D laser profile measuring instrument is erected to shoot under the influence of the measured space, so that a certain blind area exists, the whole image cannot be shot, and an ideal measurement result cannot be obtained. The method of moving a single 3D laser profiler or rotating a measured object by the erection robot can scan three-dimensional data of all surfaces and then perform point cloud splicing, so that the scanning of the whole object can be completed, but the error of the whole system is higher. The main technical scheme adopted by the embodiment of the application is as follows: and calculating the reference coordinate distribution of the reference point group according to the pose information of the contour measuring instrument, determining an error transfer coefficient based on the difference distribution between the reference coordinate distribution and the real coordinate distribution corresponding to the reference point group, and taking the error transfer coefficient as a detection value of the contour measuring system. Therefore, the obtained point cloud data are coordinates in the same system coordinate system, measurement and judgment can be directly carried out, complex fusion operation is not needed, and the technical effect of improving detection accuracy is achieved.
In order to better understand the above technical solution, exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Example 1
An embodiment of the present application discloses a detection method of a profile measuring system, which is applied to the profile measuring system, wherein the profile measuring system includes at least two profile measuring instruments disposed at different positions, and referring to fig. 1, the detection method of the profile measuring system includes:
step S110, determining the reference coordinate distribution of the reference point group according to the included angle of the camera optical axis, the base line distance and the horizontal view angle of the profile measuring instrument.
In this embodiment, the profile measuring system includes at least two profile measuring instruments in different positions. The included angle of the camera optical axis is the included angle between the camera optical axis of the contour measuring instrument and the base line. The optical axis of a camera refers to the direction of light rays in the center of a camera lens, and can be understood as the transmission direction of the light rays. For the profile measuring instrument, the camera optical axis refers to the main line of sight direction of the camera lens, i.e. the straight line formed by the light rays emitted outwards from the center of the camera lens. The camera optical axis is a reference line for locating and determining the spatial coordinates of the measurement object, generally perpendicular to the scan plane of the measurement. The baseline refers to the distance between two cameras in the profilometer, also referred to as the line of sight base. In binocular profilometers, it is common to consist of two cameras, each of which is located on the optical axis of the camera and is held at a distance from each other. This distance is the baseline. The magnitude of the baseline is directly related to the measurement range and accuracy of the meter. Larger baselines may enable longer range measurements, but the accuracy may be reduced; the smaller baseline is suitable for making close range, high accuracy measurements. The horizontal field angle refers to the angle of the spatial point in the horizontal field direction of the camera.
As an optional implementation manner, a horizontal field angle of the reference point relative to the contour measuring instrument is obtained, and an included angle of an optical axis of the camera and a length of a base line are determined according to pose information of the contour measuring instrument, wherein the length of the base line is a base line distance. Substituting the included angle of the optical axis of the camera, the base line distance, the horizontal field angle and the focal length of the camera of the profile measuring instrument into a preset relational expression, and determining the reference coordinates of the reference point. And executing the operation on each reference point in the reference point group, determining the reference coordinates of each reference point, and generating the reference coordinate distribution.
The preset relation is as follows:
the included angles between the optical axes of the cameras of the two profile measuring instruments and the base line are alpha 1 and alpha 2 respectively, the base line distance is B, the focal lengths of the cameras of the two profile measuring instruments are f1 and f2 respectively, and the horizontal field angles of the reference points in the cameras of the two profile measuring instruments are omega 1 and omega 2 respectively. X, Y and Z are the coordinates of the calculated reference points.
By combining the three relational expressions, for the current pose information, the included angle of the optical axis of the camera, the base line distance and the focal length of the camera of the profile measuring instrument are determined values, and the reference coordinate distribution of the reference point group is determined by substituting each reference point into the horizontal field angles omega 1 and omega 2 in the cameras of the two profile measuring instruments.
In the preset relation, the X coordinate of the reference point is determined by the trigonometric function value of the horizontal angle of view ω1 and the camera optical axis angle α1, the trigonometric function value of the horizontal angle of view ω2 and the camera optical axis angle α2, and the baseline distance. The Y coordinate of the reference point is determined by the trigonometric values of the horizontal angle of view ω1 and the camera optical axis angle α1, the trigonometric values of the horizontal angle of view ω2 and the camera optical axis angle α2, and the base line distance.
Referring to fig. 2, fig. 2 is an example of a profile measuring system in this embodiment, where the profile measuring system includes two profile measuring instruments in different positions, that is, a camera 1 and a camera 2 in fig. 2, through their crossed detection ranges, point cloud data of a detection point on a surface of an object to be measured located on a reference plane is completed in real time without rotating the platform, and mapping conversion is performed on coordinate data under a system coordinate system, so as to reduce errors of the whole system.
For example, as shown in fig. 3, the system structure parameter model of two profilometers is established by adopting a trigonometry method, and parameters included in the optimal system setting determined according to the inclination angles of the cameras in the profilers and the erection inclination angles mainly include included angles α1 and α2 between the optical axes of the cameras and a base line, a base line distance B, and focal lengths f1 and f2 of the cameras of the two profilers. These parameters are independent of each other, but are mutually constrained for the whole system, and the combination affects the performance of the system. The projection geometry of the spatial point P on the left and right cameras passes through the horizontal field angles omega 1, omega 2 and the vertical field angle Describing, three-dimensional coordinates of the P point are obtained from the triangular geometric relationship. Wherein X1, Y1, Z1, X2, Y2 and Z2 are the coordinate systems of two profile measuring instruments respectively. X, Y, Z is a system coordinate system.
Step S120, determining a difference distribution between the reference coordinate distribution and the real coordinate distribution as an error transfer coefficient.
In this embodiment, the real coordinates are distributed as real coordinates of each reference point in the reference point group under the system coordinate system, and are known data. Wherein the system coordinate system may be a world coordinate system.
As an alternative implementation manner, two coordinate values of the reference point in the reference coordinate distribution and the real coordinate distribution are determined, the difference value of the two coordinate values in three coordinate directions is used as the associated difference value of the reference point, the difference value distribution is determined according to all the difference values, and the difference value distribution is used as an error transfer coefficient.
Illustratively, the measurement result of the reference point is compared with the true coordinate value thereof, and the difference therebetween is calculated. The difference distribution of the reference coordinate distribution and the real coordinate distribution can be obtained by calculating the difference between the measurement result of each reference point and the real coordinate value and carrying out statistics and analysis on the differences. And determining an error transfer coefficient according to the difference distribution, and determining the form and the numerical value of the error transfer coefficient by a fitting curve or a statistical analysis method. The error transfer coefficient may represent the extent to which different error sources in the system have an effect on the measurement. The determined error transfer coefficient is applied to the detection process of the contour measurement system. In the measuring process, comparing the measuring result with the difference distribution of the reference coordinate distribution and the real coordinate distribution, and correcting the measuring result according to the error transfer coefficient. The measurement results can be modified linearly or nonlinearly according to the values and forms of the error transfer coefficients.
Step S130, determining the error transfer coefficient as a detection value of the profile measuring system.
As an alternative implementation manner, the error transfer coefficient is determined as a detection value of the profile measuring system, after which corresponding prompt information can be output based on the detection value to control the profile measuring system to adjust the camera inclination angle and the erection inclination angle of the profile measuring instrument according to the prompt information.
As another alternative embodiment, the error transfer coefficient is determined as the detection value of the profile measuring system, after which corresponding prompt information including pose change information of the profile measuring apparatus may be output based on the detection value, so as to prompt a worker to adjust the camera tilt angle and the erection tilt angle of the profile measuring apparatus according to the pose change information.
As another optional implementation manner, the calibrated pose conversion matrix is corrected according to the error transfer coefficient, so that accuracy of determining the corresponding coordinates of the point cloud data according to the pose conversion matrix is improved. And correcting measurement errors caused by the camera inclination angle and the erection inclination angle of the profile measuring instrument.
The technical scheme in the embodiment of the application at least has the following technical effects or advantages:
The reference coordinate distribution of the reference point group is determined according to the included angle of the camera optical axis, the base line distance and the horizontal view angle of the profile measuring instrument, and then the error size existing in the profile measuring system can be determined by analyzing the difference distribution between the reference coordinate distribution and the real coordinate distribution of the reference point group. According to the error transfer coefficient, the error in the system can be compensated, so that the measurement error of the whole system is reduced. By using the error transfer coefficient as a detection value for the profile measuring system, error information can be incorporated into the measurement result, thereby improving the accuracy of the measurement. Therefore, the technical problem that error accumulation is easy to occur in a rotary scanning mode in the related technology, and finally the overall error is large is effectively solved, and the technical effect that complex fusion operation is not needed to be carried out on point cloud data, and the overall measurement error of a system is reduced is achieved.
In a second embodiment, based on the first embodiment, a detection method of a profile measurement system is provided in the second embodiment of the present application, referring to fig. 4, after step S120, including:
step S210, determining calibration parameters through nonlinear optimization based on the internal parameter initial value and the external parameter initial value of the profile measuring instrument.
In this embodiment, the internal parameter initial value and the external parameter initial value are parameters of the profile measuring instrument itself. The internal and external parameters of the camera are parameters obtained in the camera calibration process and are used for describing the geometric characteristics of the camera and the relationship between the camera and the world coordinate system. The internal parameters of the camera include parameters such as focal length, principal point coordinates, distortion coefficients and the like, and are used for describing imaging characteristics of the camera. The focal length refers to the distance from the focal point of the camera to the imaging plane, the principal point coordinates are the origin coordinates on the imaging plane, and the distortion coefficient is used to describe the distortion condition of the camera lens. The camera's external parameters include a rotation matrix and translation vectors that describe the camera's position and pose in the world coordinate system. The rotation matrix describes the rotational relationship between the camera coordinate system and the world coordinate system, and the translation vector describes the position of the origin of the camera coordinate system in the world coordinate system.
As an alternative embodiment, the internal parameters and the external parameters of the profile measuring instrument are obtained as the internal parameter initial value and the external parameter initial value, and the calibration parameters are optimized by using a nonlinear optimization algorithm, such as a Levenberg-Marquardt algorithm, based on the parameter initial value and the external parameter initial value. By minimizing the re-projection error, more accurate internal and external parameters, namely calibration parameters, are obtained.
Optionally, step S210 includes:
step S211, determining the initial value of the external parameter according to the pose information of the contour measuring instrument.
As an alternative embodiment, the profile measuring instrument may provide position and attitude information in space from which initial values of the external parameters may be determined. The position and the orientation of the camera can be determined by measuring the position and the gesture of the device, so that the external parameter is initialized, and the external parameter initial value is obtained.
And S212, extracting the characteristic points of the preset number of calibration pictures based on the internal parameter initial value and the external parameter initial value.
As an alternative embodiment, a profile measuring instrument is used to take picture data of a series of calibration plates and to determine a preset number of calibration pictures. For each calibration picture, firstly, performing image processing, and extracting characteristic points of the calibration plate. Corner points or center points of a specific pattern are usually used as feature points.
And step S213, establishing the corresponding relation between the calibration pictures based on the characteristic points.
As an alternative embodiment, for each calibration picture, a correspondence relationship between the feature points is established by matching them. Feature point descriptors and matching algorithms may be used to achieve matching of feature points.
Step S214, calculating the calibration parameters based on nonlinear optimization based on the corresponding relation, the internal parameter and the external parameter.
As an alternative implementation manner, a nonlinear optimization algorithm is utilized to perform iterative calculation based on the corresponding relation between the calibration pictures and the initial values of the internal reference and the external reference, so as to continuously optimize the calibration parameters and minimize the re-projection error.
And step S220, fitting a laser plane equation based on the calibration parameters according to the acquired calibration plate picture data of a plurality of heights.
In the embodiment, a fine adjustment lifting platform is erected on a reference plane, calibration plate picture acquisition is carried out on each profile measuring instrument at different heights within the measuring depth range, and a laser plane equation is fitted.
As an alternative embodiment, a profile meter is used to collect a series of calibration plate picture data of different heights. The calibration plate can be completely shot at different heights, and the picture data contains corner information of the calibration plate. And for each calibration plate picture, extracting the corner information of the calibration plate by using an image processing algorithm. And (3) using a corner detection algorithm to find the corner position on the calibration plate. And converting the angular point positions of the calibration plates from an image coordinate system to a world coordinate system. And performing coordinate conversion through an internal reference matrix corresponding to the known calibration plate size and the calibration parameters of the camera. According to the internal reference matrix of the camera, the angular point positions in the image coordinate system can be converted into positions in the camera coordinate system. And using the converted corner positions as input data, and fitting a laser plane equation by using a fitting algorithm.
Where the laser plane equation can be expressed as ax+by+cz+d=0, where A, B, C and D are parameters of the plane.
Plane parameters obtained through a fitting algorithm, namely A, B, C and D, are parameters of a laser plane. These parameters describe the geometry of the laser plane in the world coordinate system.
Optionally, step S220 includes:
step S221, determining characteristic point data corresponding to the calibration plate picture data of a preset height sequence. As an alternative embodiment, a set of preset height sequences is selected, the calibration plates are respectively placed at different height positions, and the profile measuring instrument is used for collecting the picture data of the calibration plates with corresponding heights. And extracting the characteristic points of each picture, and recording the pixel coordinates of the characteristic points.
And step S222, establishing a characteristic equation based on the characteristic point data and the calibration parameters.
As an alternative embodiment, the pixel coordinates of each feature point are converted to world coordinates using calibration parameters. And establishing a characteristic equation through the world coordinates of the plurality of groups of characteristic points and corresponding pixel coordinate data. A linear regression method or a least square method is used to fit the characteristic equation.
And step S223, combining the characteristic equation with the corresponding height value, and fitting out the laser plane equation.
As an alternative embodiment, for each preset height, the corresponding characteristic equation is combined with the height value obtained by actual measurement. The equation of the laser plane can be solved by a fitting algorithm, such as a least square method, etc.
And step S230, determining a pose conversion matrix based on the calibration plate picture data acquired by the contour measuring instrument and the laser plane equation.
In this embodiment, a calibration plate is placed in the center of a reference plane, the center area of the reference plane is a common area of two profilometers, the calibration plate is placed in the common area and is fixed, the two profilometers respectively shoot pictures of the calibration plate to calculate the pose, then a pose conversion matrix is calculated, and the coordinate system of the profiler is converted into the same world coordinate system, namely a system coordinate system.
As an alternative implementation manner, based on calibration plate picture data of known height collected by the profile measuring instrument, corresponding laser plane equation is determined according to the known height, and calibration plate coordinate data corresponding to the profile measuring instrument is determined. And then calculating the pose conversion matrix between every two contour measuring instruments, selecting a main contour measuring instrument in the contour measuring instruments, and determining the pose conversion matrix of the coordinate data of the calibration plate corresponding to the main contour measuring instrument and the system coordinate system. And then determining the pose conversion matrix of each contour measuring instrument relative to the system coordinate system according to each pose conversion matrix.
The calibration parameters are determined through nonlinear optimization due to the adoption of the internal parameter initial value and the external parameter initial value based on the profile measuring instrument; fitting a laser plane equation based on the calibration parameters according to the collected calibration plate picture data of a plurality of heights; and determining a pose conversion matrix based on the calibration plate picture data acquired by the profile measuring instrument and the laser plane equation. The method solves the problems that the clear ranges of the two cameras are inconsistent and the two cameras are difficult to calibrate simultaneously. And the obtained point cloud data are coordinates in the same system coordinate system, so that measurement and judgment can be directly carried out, and the technical effect of complex fusion operation is not needed.
Based on the second embodiment, a third embodiment of the present application provides a detection method of a profile measurement system, referring to fig. 5, step S230 includes:
step S310, determining a main conversion matrix of the main profilometer to the system coordinate system based on calibration plate data in the system coordinate system and main calibration plate picture data acquired by the main profilometer.
In this embodiment, the main profile measuring instrument of the profile measuring instruments is selected, and the remaining profile measuring instruments are auxiliary profile measuring instruments. And determining the pose conversion matrix of the contour measuring instrument to the system coordinate system by determining the main conversion matrix of the main contour measuring instrument and the system coordinate system and the auxiliary conversion matrix of each auxiliary contour measuring instrument to the main camera.
As an alternative embodiment, a calibration plate is placed at a known location within the system coordinate system and master calibration plate picture data for that location is acquired using a master profilometer. And extracting characteristic points from the picture data of the calibration plate, and calculating pixel coordinates of the characteristic points. And (3) utilizing the position information of the known calibration plate in the system coordinate system to correspond to the pixel coordinates of the feature points, and then calculating a main conversion matrix of the main contour measuring instrument to the system coordinate system by using a corresponding calibration algorithm, such as a least square method.
Step S320, determining a secondary conversion matrix from the secondary profile measuring apparatus to the primary profile measuring apparatus based on the primary calibration board picture data and the secondary calibration board picture data acquired by the secondary profile measuring apparatus.
As an alternative implementation manner, the feature point extraction is respectively performed on the image data of the auxiliary calibration plate collected by the same calibration plate based on the image data of the main calibration plate and the auxiliary profile measuring instrument, and the pixel coordinates of the feature point are calculated. And (3) utilizing the known position information of the main calibration plate in the system coordinate system to correspond to the pixel coordinates of the characteristic points of the main contour measuring instrument, and then using a corresponding calibration algorithm, such as a least square method, to calculate a main conversion matrix of the main contour measuring instrument to the system coordinate system. The known position information of the auxiliary calibration plate in the coordinate system of the main contour measuring instrument is utilized to correspond to the pixel coordinates of the characteristic points of the auxiliary contour measuring instrument, and then a corresponding calibration algorithm, such as a least square method, is used for calculating an auxiliary conversion matrix from the auxiliary contour measuring instrument to the coordinate system of the main contour measuring instrument.
As another alternative, a known location of the calibration plate within the system coordinate system is placed and master calibration plate picture data for that location is acquired using a master profilometer. And acquiring image data of the auxiliary calibration plate at the position by using an auxiliary profile measuring instrument, extracting characteristic points from the image data of the two calibration plates, and calculating pixel coordinates of the characteristic points. And the pixel coordinates of the characteristic points in the main contour measuring instrument and the auxiliary contour measuring instrument are utilized to correspond, and then a corresponding calibration algorithm, such as a least square method, is used for calculating an auxiliary conversion matrix from the auxiliary contour measuring instrument to a main contour measuring instrument coordinate system.
And step S330, performing matrix calculation according to the auxiliary conversion matrix and the main conversion matrix to obtain the pose conversion matrix.
As an alternative embodiment, the primary and secondary transformation matrices are transformed into the form of homogeneous matrices, respectively. And (3) aligning the primary conversion matrix and the secondary conversion matrix to perform matrix multiplication operation, wherein the obtained result is a pose conversion matrix which represents the pose of the secondary contour measuring instrument relative to a system coordinate system. And the main transformation matrix is used as the pose transformation matrix of the main contour measuring instrument.
The main conversion matrix of the main contour measuring instrument to the system coordinate system is determined by adopting calibration plate data based on the system coordinate system and main calibration plate picture data acquired by the main contour measuring instrument; determining an auxiliary conversion matrix of the auxiliary contour measuring instrument to the main contour measuring instrument based on the main calibration plate picture data and the auxiliary calibration plate picture data acquired by the auxiliary contour measuring instrument; and performing matrix calculation according to the auxiliary conversion matrix and the main conversion matrix to obtain the pose conversion matrix. And the obtained point cloud data are coordinates in the same system coordinate system, so that measurement and judgment can be directly carried out, and the technical effect of complex fusion operation is not needed.
Based on the second embodiment, a fourth embodiment of the present application provides a detection method of a profile measurement system, after step S230, including:
step S410, the first point cloud coordinates acquired by the main profile measuring instrument are processed according to the main transformation matrix to obtain three-dimensional coordinates of the first detection point.
Step S420, the second point cloud coordinates acquired by the auxiliary profile measuring instrument are processed according to the pose conversion matrix to obtain the three-dimensional coordinates of the second detection points;
step S430, determining a three-dimensional image of the object to be detected based on the three-dimensional coordinates of the first detection point and the three-dimensional coordinates of the second detection point.
As an alternative implementation manner, the first point cloud coordinates acquired by the main profiler are processed according to the main transformation matrix to obtain the three-dimensional coordinates of the first detection point, and the coordinate information of the first detection point is extracted by using the point cloud data acquired by the main profiler. And converting the first point cloud coordinate into a homogeneous coordinate form, and performing matrix calculation with a main conversion matrix to obtain the three-dimensional coordinate of the first detection point. And extracting coordinate information of the second detection point by using the point cloud data acquired by the auxiliary profile measuring instrument. And converting the second point cloud coordinate into a homogeneous coordinate form, and performing matrix calculation with the pose conversion matrix to obtain the three-dimensional coordinate of the second detection point. The three-dimensional coordinates of the first detection point and the three-dimensional coordinates of the second detection point can be used for determining the shape, the size and other information of the object to be detected. And further processing the three-dimensional coordinate data to reconstruct a three-dimensional image of the object to be measured, and carrying out corresponding analysis and measurement.
In this embodiment, the coordinate system of the main and auxiliary profile measuring instruments is integrated into the system coordinate system, so that coordinate conversion of the point cloud data can be completed in real time, so that the collected point cloud data can generate coordinate data under the corresponding system coordinate system in real time, and real-time splicing of the coordinate data determined by the main and auxiliary profile measuring instruments is further realized. The method solves the technical problems of long time consumption and large error caused by the fact that coordinate fusion is required to be carried out after the detection task is completed in the related art.
Based on the first embodiment, a fifth embodiment of the present application provides a detection method of a profile measurement system, after step S120, including:
step S510, determining a nonlinear function based on the error transfer coefficient.
In this embodiment, the gradient decreasing form of the nonlinear function is used to iterate each inclination angle value, and the minimum value of the error transfer coefficient is obtained. And taking the inclination angle value at the moment as the target camera pose of the contour measuring instrument.
As an alternative embodiment, a nonlinear function is established with the overall evaluation value of the error transfer coefficient as an optimization target.
As another alternative, after determining the error transfer coefficient, a nonlinear function is established that maps small variations in the input camera pose to the error distribution at the target point based on the error transfer coefficient.
Step S510, iterating the nonlinear function based on a preset camera pose distribution.
In this embodiment, the preset camera pose distribution is a plurality of groups of preset camera tilt angles and erection tilt angles of the profile measuring instrument.
As an optional implementation manner, substituting each camera inclination angle and erection inclination angle corresponding to preset camera pose distribution into a nonlinear function, and determining a target error transfer coefficient corresponding to the iteration value.
Step S510, determining the pose of the target camera according to the approach value of the error overall evaluation value corresponding to the iteration value.
As an alternative implementation manner, the error overall evaluation value of each target error transfer coefficient is determined according to a weighting algorithm, and when the error overall evaluation value approaches zero, the camera inclination angle and the erection inclination angle corresponding to the iteration value at the moment are determined as the target camera pose.
And step S510, outputting the prompting information of pose adjustment according to the pose of the target camera and the pose information of the contour measuring instrument.
As an alternative implementation, determining a camera tilt offset according to a target camera tilt in the target camera pose and a camera tilt in pose information; determining an erection inclination angle offset according to a target erection inclination angle in the pose of the target camera and an erection inclination angle in pose information; and taking the inclination angle offset of the camera and the erection inclination angle offset as pose adjustment values, and outputting corresponding prompt information.
Optionally, after step S120, the method further includes:
step S550, determining an overall deviation value corresponding to the error transfer coefficient;
step S560, outputting prompt information of completion of setting the erection position when the total deviation value is smaller than a preset threshold value.
As an optional implementation manner, according to the weight value of each reference point and the error value corresponding to the error distribution in the error transfer coefficient, the overall deviation value corresponding to the error transfer coefficient is determined in a weighting manner; and setting a preset threshold value, wherein the threshold value can be determined according to actual needs and requirements. And comparing the total deviation value with a preset threshold, if the total deviation value is smaller than the preset threshold, indicating that the setting of the erection position is completed, and outputting corresponding prompt information.
Through the steps in the above embodiment, we can calculate the overall deviation value according to the error transfer coefficient and the error distribution of the reference point, and compare with the preset threshold. If the total deviation value is smaller than the preset threshold value, the setting of the erection position is finished, and corresponding prompt information can be output. Therefore, the accuracy detection and control of the erection position can be performed by considering the error distribution and the error transfer coefficient of the reference point, and the accuracy and stability of the erection position are ensured.
Determining a nonlinear function based on the error transfer coefficient is adopted; iterating the nonlinear function based on a preset camera pose distribution; determining the pose of the target camera according to the approach value of the error overall evaluation value corresponding to the iteration value; and outputting the prompting information of pose adjustment according to the pose of the target camera and the pose information of the contour measuring instrument. The method solves the technical problems that in the related art, a multi-profile measuring instrument needs to be established to be matched with a rotary platform for measurement, the operation difficulty is high, and the use cost is high, and further realizes that the optimal erection position of a profile measuring system is determined with low cost and high efficiency through function planning, so that three-dimensional coordinate data of the surface of an object to be measured are spliced in real time by matching with a pose conversion matrix.
The application further provides a detection device of the contour measurement system, referring to fig. 6, and fig. 6 is a schematic structural diagram of the detection device of the contour measurement system of the hardware running environment according to the embodiment of the application.
As shown in fig. 6, the detection apparatus of the profile measuring system may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the configuration shown in fig. 6 does not constitute a limitation of the detection apparatus of the profile measuring system, and may include more or fewer components than shown, or may combine certain components, or may be a different arrangement of components.
Optionally, the memory 1005 is electrically connected to the processor 1001, and the processor 1001 may be configured to control operation of the memory 1005, and may also read data in the memory 1005 to implement detection of the profile measurement system.
Alternatively, as shown in fig. 6, an operating system, a data storage module, a network communication module, a user interface module, and a detection program of the profile measuring system may be included in the memory 1005 as one storage medium.
Optionally, in the detection device of the profile measurement system shown in fig. 6, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the detection device of the profile measuring system of the present application may be provided in the detection device of the profile measuring system.
As shown in fig. 6, the method is applied to a profile measuring system, the profile measuring system includes at least two profile measuring instruments disposed at different positions, a detection device of the profile measuring system invokes a detection program of the profile measuring system stored in a memory 1005 through a processor 1001, and performs related steps of a detection method of the profile measuring system provided in the embodiment of the present application:
Determining reference coordinate distribution of a reference point group according to the camera optical axis included angle, the base line distance and the horizontal view angle of the profile measuring instrument;
determining the difference distribution of the reference coordinate distribution and the real coordinate distribution as an error transfer coefficient;
the error transfer coefficient is determined as a detection value of the profile measuring system.
Alternatively, the processor 1001 may call the detection program of the profile measurement system stored in the memory 1005, and also perform the following operations:
determining calibration parameters through nonlinear optimization based on the internal parameter initial value and the external parameter initial value of the profile measuring instrument;
fitting a laser plane equation based on the calibration parameters according to the collected calibration plate picture data of a plurality of heights;
and determining a pose conversion matrix based on the calibration plate picture data acquired by the profile measuring instrument and the laser plane equation.
Alternatively, the processor 1001 may call the detection program of the profile measurement system stored in the memory 1005, and also perform the following operations:
determining the initial value of the external parameter according to the pose information of the contour measuring instrument;
extracting characteristic points of a preset number of calibration pictures based on the internal parameter initial value and the external parameter initial value;
Establishing a corresponding relation between the calibration pictures based on the characteristic points;
and calculating the calibration parameters based on nonlinear optimization based on the corresponding relation, the internal parameter and the external parameter.
Alternatively, the processor 1001 may call the detection program of the profile measurement system stored in the memory 1005, and also perform the following operations:
determining characteristic point data corresponding to the calibration plate picture data of a preset height sequence;
establishing a characteristic equation based on the characteristic point data and the calibration parameters;
and combining the characteristic equation with the corresponding height value, and fitting the laser plane equation.
Alternatively, the processor 1001 may call the detection program of the profile measurement system stored in the memory 1005, and also perform the following operations:
determining a main conversion matrix of a main contour measuring instrument to a system coordinate system based on calibration plate data in the system coordinate system and main calibration plate picture data acquired by the main contour measuring instrument;
determining an auxiliary conversion matrix of the auxiliary contour measuring instrument to the main contour measuring instrument based on the main calibration plate picture data and the auxiliary calibration plate picture data acquired by the auxiliary contour measuring instrument;
and performing matrix calculation according to the auxiliary conversion matrix and the main conversion matrix to obtain the pose conversion matrix.
Alternatively, the processor 1001 may call the detection program of the profile measurement system stored in the memory 1005, and also perform the following operations:
the method comprises the steps of processing first point cloud coordinates acquired by a main profile measuring instrument according to a main transformation matrix to obtain three-dimensional coordinates of a first detection point;
processing the second point cloud coordinates acquired by the auxiliary profile measuring instrument according to the pose conversion matrix to obtain three-dimensional coordinates of a second detection point;
and determining a three-dimensional image of the object to be detected based on the three-dimensional coordinates of the first detection point and the three-dimensional coordinates of the second detection point.
Alternatively, the processor 1001 may call the detection program of the profile measurement system stored in the memory 1005, and also perform the following operations:
determining a nonlinear function based on the error transfer coefficient;
iterating the nonlinear function based on a preset camera pose distribution;
determining the pose of the target camera according to the approach value of the error overall evaluation value corresponding to the iteration value;
and outputting the prompting information of pose adjustment according to the pose of the target camera and the pose information of the contour measuring instrument.
Alternatively, the processor 1001 may call the detection program of the profile measurement system stored in the memory 1005, and also perform the following operations:
Determining an overall deviation value corresponding to the error transfer coefficient;
and outputting prompt information of finishing setting the erection position when the total deviation value is smaller than a preset threshold value.
In addition, the embodiment of the application further provides a computer readable storage medium, wherein the computer readable storage medium stores a detection program of the profile measuring system, and the detection program of the profile measuring system realizes the relevant steps of any embodiment of the detection method of the profile measuring system when being executed by a processor.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flowchart and/or block of the flowchart illustrations and/or block diagrams, and combinations of flowcharts and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The application may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (10)
1. A method for detecting a profile measuring system, the profile measuring system including at least two profile measuring instruments disposed at different positions, the method comprising:
determining reference coordinate distribution of a reference point group according to the camera optical axis included angle, the base line distance and the horizontal view angle of the profile measuring instrument;
determining the difference distribution of the reference coordinate distribution and the real coordinate distribution as an error transfer coefficient;
The error transfer coefficient is determined as a detection value of the profile measuring system.
2. The method of detecting a contour measurement system as defined in claim 1, wherein said step of determining a difference distribution between said reference coordinate distribution and said true coordinate distribution as an error transfer coefficient includes, after said step of:
determining calibration parameters through nonlinear optimization based on the internal parameter initial value and the external parameter initial value of the profile measuring instrument;
fitting a laser plane equation based on the calibration parameters according to the collected calibration plate picture data of a plurality of heights;
and determining a pose conversion matrix based on the calibration plate picture data acquired by the profile measuring instrument and the laser plane equation.
3. The method of detecting a profile measuring system according to claim 2, wherein the step of determining the calibration parameter by nonlinear optimization based on the internal parameter initial value and the external parameter initial value of the profile measuring instrument includes:
determining the initial value of the external parameter according to the pose information of the contour measuring instrument;
extracting characteristic points of a preset number of calibration pictures based on the internal parameter initial value and the external parameter initial value;
establishing a corresponding relation between the calibration pictures based on the characteristic points;
And calculating the calibration parameters based on nonlinear optimization based on the corresponding relation, the internal parameter and the external parameter.
4. The method of claim 2, wherein the step of fitting a laser plane equation based on the calibration parameters from the collected calibration plate picture data for a plurality of heights comprises:
determining characteristic point data corresponding to the calibration plate picture data of a preset height sequence;
establishing a characteristic equation based on the characteristic point data and the calibration parameters;
and combining the characteristic equation with the corresponding height value, and fitting the laser plane equation.
5. The method of claim 2, wherein determining a pose conversion matrix based on the calibration plate picture data acquired by the camera and the laser plane equation comprises:
determining a main conversion matrix of a main contour measuring instrument to a system coordinate system based on calibration plate data in the system coordinate system and main calibration plate picture data acquired by the main contour measuring instrument;
determining an auxiliary conversion matrix of the auxiliary contour measuring instrument to the main contour measuring instrument based on the main calibration plate picture data and the auxiliary calibration plate picture data acquired by the auxiliary contour measuring instrument;
And performing matrix calculation according to the auxiliary conversion matrix and the main conversion matrix to obtain the pose conversion matrix.
6. The method of detecting a profile measuring system according to claim 2, wherein after the step of determining a pose conversion matrix based on the calibration plate picture data acquired by the profile measuring instrument and the laser plane equation, the method comprises:
the method comprises the steps of processing first point cloud coordinates acquired by a main profile measuring instrument according to a main transformation matrix to obtain three-dimensional coordinates of a first detection point;
processing the second point cloud coordinates acquired by the auxiliary profile measuring instrument according to the pose conversion matrix to obtain three-dimensional coordinates of a second detection point;
and determining a three-dimensional image of the object to be detected based on the three-dimensional coordinates of the first detection point and the three-dimensional coordinates of the second detection point.
7. The method of detecting a contour measurement system as defined in claim 1, wherein said step of determining a difference distribution between said reference coordinate distribution and said true coordinate distribution as an error transfer coefficient includes, after said step of:
determining a nonlinear function based on the error transfer coefficient;
iterating the nonlinear function based on a preset camera pose distribution;
Determining the pose of the target camera according to the approach value of the error overall evaluation value corresponding to the iteration value;
and outputting the prompting information of pose adjustment according to the pose of the target camera and the pose information of the contour measuring instrument.
8. The method of detecting a contour measurement system as defined in claim 1, wherein said step of determining a difference distribution between said reference coordinate distribution and said true coordinate distribution as an error transfer coefficient includes, after said step of:
determining an overall deviation value corresponding to the error transfer coefficient;
and outputting prompt information of finishing setting the erection position when the total deviation value is smaller than a preset threshold value.
9. A detection device of a contour measurement system, characterized by comprising a memory, a processor and a detection program of the contour measurement system stored on the memory and executable on the processor, the processor implementing the steps of the detection method of the contour measurement system according to any of claims 1 to 8 when executing the detection program of the contour measurement system.
10. A computer-readable storage medium, on which a detection program of a contour measurement system is stored, which, when being executed by a processor, carries out the steps of the detection method of a contour measurement system according to any one of claims 1 to 8.
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