A method and system for high-precision positioning of object surface

Abstract

The present invention discloses a method and system for high-precision positioning of an object surface, the method comprising: making marks with a preset distribution density on the surface of the object; photographing the marked object and numbering the marks in the image; obtaining the relative position information of each mark on the surface of the object and establishing a corresponding relationship between the mark number and the mark position information; obtaining a real-time image to be measured and detecting the marks in the real-time image to be measured; and calculating the surface position of the object corresponding to the current real-time image to be measured. The system comprises: a mark making module, a numbering module, a mark position relationship module, a measured image module and a physical quantity solving module. By using the present invention, it is possible to achieve high-precision measurement of parameters such as two-dimensional translation, three-dimensional translation, and two-dimensional rotation of the object by photographing the inherent features or fabricated texture features of the surface of the object through a single camera. The present invention can be widely used in the field of measurement technology.

Description

Technical Field

[0001] The present invention relates to the field of measurement technology, and in particular to a high-precision positioning method and system for an object surface. Background Art

[0002] High-precision positioning of the surface of an object is an important part of the measurement field. Through high-precision positioning of the surface of an object, the displacement or rotation of the object can be directly measured with high precision, and then high-precision displacement or rotation angle data can be provided for precision instruments, precision equipment or high-precision weapons and equipment. This type of technology can be widely used in the fields of robots, aerospace equipment, photoelectric theodolites, radars, CNC machine tools and various industrial automation equipment, and is of great significance to the defense, aerospace, precision manufacturing, automation industry and other industries.

[0003] At present, the main method of high-precision positioning of the surface of an object mostly relies on gratings. Grating measurement technology is a technology that uses moiré fringes for precision measurement. The measurement principle is: when two gratings overlap, moiré fringes will be generated. Moiré fringes can amplify the relative small displacement of the two gratings. By measuring the relevant information of the moiré fringes, high-precision positioning of the grating can be achieved, thereby achieving high-precision measurement of displacement or angle. Although grating measurement technology has the advantages of small size, high precision, and strong anti-interference ability, it has very high requirements for materials and processes, and is difficult to manufacture and process. Even if the processing and manufacturing of high-precision gratings is completed, in actual application, grating measurement technology will still be restricted by many factors, and the actual measurement accuracy will be greatly affected, such as the influence of the encoder optical part such as the motherboard error and the line error of the code disk, the influence of the mechanical part such as the bearing and structure, the influence of the electrical part such as the light emitting source and the receiving unit, and the influence of the signal delay in the use of the encoder. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a method and system for high-precision positioning of the surface of an object. This algorithm is a semi-supervised learning method, which can achieve high-precision measurement of parameters such as two-dimensional translation, three-dimensional translation, and two-dimensional rotation of the object by capturing the inherent features or fabricated texture features of the object surface with a single camera.

[0005] The first technical solution adopted by the present invention is: a method for high-precision positioning of an object surface, comprising the following steps:

[0006] Marks with a preset distribution density are made on the surface of the object to obtain a marked object;

[0007] The produced marks need to meet the following settings: 1. Ensure that after imaging the surface of the object, the background images of different marks in the image have a certain degree of distinction, so that the marks can be quickly and reliably detected and identified from the image; 2. The marks need to reach a certain distribution density on the surface of the object to ensure that when the camera shoots any part of the object surface to be measured, there is at least one complete mark in the imaging field of view.

[0008] Photographing the marked object and numbering the marks in the image to obtain an image with numbered marks;

[0009] There are three different naming and numbering methods, and you can choose one of them according to the actual situation: 1. Naming and numbering based on the image feature information of the mark itself; 2. Naming and numbering based on the random texture image information around the mark; 3. Naming and numbering based on the mark itself information combined with the image information of the surrounding texture.

[0010] Obtaining relative position information of each mark on the surface of the object according to the image with numbered marks and establishing a corresponding relationship between the mark number and the mark position information;

[0011] Acquire a real-time image to be tested and detect a mark in the real-time image to be tested to obtain a mark to be tested;

[0012] According to the position of the mark to be measured in the real-time image to be measured and the object surface position information corresponding to the mark, the object surface position corresponding to the current real-time image to be measured is calculated.

[0013] Furthermore, the step of making marks with a preset distribution density on the surface of the object to obtain the marked object specifically includes:

[0014] Using a mark of a preset style, engraving the mark on the surface through a mark making method to obtain a marked object;

[0015] The marks of the preset styles include line segments, dots, circles, squares, crosses and their combined shapes;

[0016] The marking production method includes laser engraving, printing and etching;

[0017] The engraving interval of the marks is less than half of the image frame.

[0018] Furthermore, the step of photographing the marked object and numbering the marks in the image to obtain the surface image with the numbered marks specifically includes:

[0019] The surface of the marked object is photographed and imaged to obtain a surface image;

[0020] The surface image is processed by threshold segmentation to detect the target centers of all the marks in the surface image;

[0021] Taking the target center as the reference point, intercepting an image of a preset pixel size as a marking feature image corresponding to the mark;

[0022] The principal component analysis method is used to establish the corresponding relationship between the marker feature image and the marker number, the marker feature image is reduced to a low dimension, and the first 10 principal components of the principal component matrix are taken as a one-dimensional vector representing the marker to determine the unique number;

[0023] Get a surface image with numbered labels.

[0024] Furthermore, the step of obtaining the relative position information of each mark on the surface of the object according to the image with numbered marks and establishing the corresponding relationship between the mark number and the mark position information specifically includes:

[0025] The images with number marks are stitched together by an image stitching method to obtain a complete surface image;

[0026] Taking the complete surface image as a reference image and establishing the relationship between the image pixel coordinates of the reference image and the surface coordinates of the actual object;

[0027] The markers are identified and located on the reference image, and the corresponding relationship between each marker and the object surface coordinates is determined based on the relationship between the reference image pixel coordinates and the actual object surface coordinates.

[0028] Furthermore, the step of acquiring the real-time image to be tested and detecting the mark in the real-time image to be tested to obtain the mark to be tested specifically includes:

[0029] Determine the precise position of each marking center point on the surface of the object according to the transformation formula;

[0030] Perform real-time imaging on the surface of the object to obtain a real-time image to be measured;

[0031] Perform marker detection on the real-time image to be tested, and confirm the marker number corresponding to the marker in the real-time image to be tested based on vector comparison.

[0032] Further, the transformation formula is as follows:

[0033]

[0034] In the above formula, s is the Z coordinate of the center point in the camera coordinate system, (u,v) is the center image coordinate, (f x ,f y ) is the equivalent focal length of the camera, (c x ,c y ) is the principal point of the image, r ij (i,j=1,2,3) is the element of the rotation matrix R, t i (i=1,2,3) is the translation vector, (xw ,y w ,z w ) represents the three-dimensional point coordinates on the object surface corresponding to the center of the marker.

[0035] Further, the step of calculating the surface position of the object corresponding to the current real-time image to be measured according to the position of the mark to be measured in the real-time image to be measured and the surface position information of the object corresponding to the mark specifically includes:

[0036] Obtain the corresponding coordinates of the center of the real-time image on the reference image according to the marking number;

[0037] According to the correspondence between the pixel coordinates of the reference image and the surface parameters of the object and the coordinates of the center of the real-time image on the reference image, the surface point of the object corresponding to the center of the real-time image is determined;

[0038] According to the object surface point corresponding to the center of the real-time image, the object surface position corresponding to the current real-time image to be measured is obtained;

[0039] The object surface position corresponding to the current real-time image to be measured includes one-dimensional coordinates, two-dimensional coordinates, three-dimensional coordinates, one-dimensional rotation angle and two-dimensional rotation angle.

[0040] Further, the step of calculating the surface position of the object corresponding to the current real-time image to be measured according to the position of the mark to be measured in the real-time image to be measured and the surface position information of the object corresponding to the mark specifically includes:

[0041]

[0042] In the above formula, θ is the rotation angle of the rotating body to be measured, y0 is the origin of the circumference of the outer surface of the rotating body, and y c is the center coordinate point of the unfolded outer surface of the revolution, and L is the circumference length of the unfolded outer surface of the revolution.

[0043] Furthermore, the calculation formula of the two-dimensional rotation angle is as follows:

[0044]

[0045] In the above formula, the image center coordinates (u, v) correspond to the world coordinates on the surface of the sphere to be measured (x w ,y w ,z w ), α is the longitude of the sphere to be measured, and β is the latitude of the sphere to be measured.

[0046] The second technical solution adopted by the present invention is: a high-precision positioning system for an object surface, comprising:

[0047] A marking making module, used to make marks with a preset distribution density on the surface of an object to obtain a marked object;

[0048] A numbering module is used to photograph the marked object and number the marks in the image to obtain an image with numbered marks;

[0049] A marking position relationship module is used to obtain the relative position information of each mark on the surface of the object according to the image with numbered marks and establish a corresponding relationship between the mark number and the mark position information;

[0050] The image module to be tested is used to obtain the real-time image to be tested and detect the mark in the real-time image to be tested to obtain the mark to be tested;

[0051] The physical quantity settlement module is used to calculate the surface position of the object corresponding to the current real-time image to be measured according to the position of the mark to be measured in the real-time image to be measured and the surface position information of the object corresponding to the mark.

[0052] The beneficial effects of the method and system of the present invention are as follows: the present invention uses a single camera to shoot the inherent features or fabricated texture features of the object surface, thereby realizing high-precision measurement of parameters such as two-dimensional translation, three-dimensional translation, and two-dimensional rotation angle of the object. By measuring the manufactured marks, the actual position of each mark relative to the object to be measured is obtained with high precision, and then the surface of the object is positioned and measured according to the actual position of the mark (rather than the theoretical position), thereby avoiding the influence of factors such as machining error and installation error of the mark on the measurement accuracy; and the present invention does not need to manufacture and install information rings, and does not need to process and manufacture coding marks with high precision, so the method is simpler and more economical. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flow chart of steps of a method for high-precision positioning of an object surface according to the present invention;

[0054] Figure 2 It is a structural block diagram of a high-precision positioning system for an object surface of the present invention;

[0055] Figure 3 is a schematic diagram of camera imaging according to a specific embodiment of the present invention;

[0056] Figure 4 It is a schematic diagram of marking production according to a specific embodiment of the present invention;

[0057] Figure 5 It is a schematic diagram of naming and numbering of specific embodiments of the present invention;

[0058] Figure 6 It is a schematic diagram of physical quantity calculation in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0059] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The step numbers in the following embodiments are only provided for the convenience of explanation and description, and the order between the steps is not limited in any way. The execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0060] The present invention takes a single linear array camera scanning and imaging the side of a truncated cone, and the truncated cone surface lacks obvious random natural texture as an example to further illustrate the implementation manner of the present invention in detail.

[0061] Reference Figure 1 The present invention provides a method for high-precision positioning of an object surface, the method comprising the following steps:

[0062] S1. Making marks with a preset distribution density on the surface of an object to obtain a marked object;

[0063] Specifically, if Figure 4 As shown, through laser engraving technology, line segment style marks are used to engrave line segments on the surface of an object that has been made with a random texture. The engraving spacing of the line segments is less than half of the image frame, ensuring that there is at least one complete mark in the image when imaging the surface of the object to be measured.

[0064] S2, photographing the marked object and numbering the marks in the image to obtain an image with numbered marks;

[0065] Specifically, all the marks on the surface of the object are imaged, and then all images are segmented by threshold to detect the marks, and the centroid method is used to determine the coordinates of the mark image; and the image of a certain range (such as 200×200 pixels) is intercepted with the center of the mark as the reference point as the feature image corresponding to the mark (due to the randomness of texture information, the feature image of each mark is different); finally, the principal component analysis (PCA) method is used to distinguish the feature images of the marks and number them. The numbering diagram is shown in the figure. Figure 5 .

[0066] S3, obtaining relative position information of each mark on the surface of the object according to the image with number marks and establishing a corresponding relationship between the mark number and the mark position information;

[0067] Specifically, if Figure 3 As shown in the figure, for a frustum without obvious random natural textures on the surface, firstly, metal paint is sprayed on the surface of the frustum to be tested. The size of the metal particles is determined according to the physical resolution of the image pixels, so that a random pattern in the shape of speckle is produced after the surface of the object is imaged. Then, each part of the side of the frustum is imaged with a certain degree of overlap, and the image stitching technology is used to obtain a complete image of the frustum around the frustum, which is used as a reference image. The corresponding relationship between the image pixel coordinates of the reference image and the two-dimensional coordinates of the local area of ​​the frustum surface is established.

[0068] The coordinates of each mark on the surface of the object can be directly measured using a three-dimensional coordinate measuring machine or stereo vision measurement technology to determine the corresponding relationship between each mark and the coordinates of the object surface.

[0069] S4, acquiring a real-time image to be tested and detecting a mark in the real-time image to be tested to obtain a mark to be tested;

[0070] S5. Calculate the surface position of the object corresponding to the current real-time image to be measured according to the position of the mark to be measured in the real-time image to be measured and the surface position information of the object corresponding to the mark.

[0071] Specifically, the physical quantity solution refers to Figure 6 .

[0072] As a further preferred embodiment of the method, the step S2, photographing the marked object and numbering the marks in the image to obtain the numbered marked image, specifically includes:

[0073] S21, photographing and imaging the surface of the marked object to obtain a surface image;

[0074] S22, processing the surface image by threshold segmentation, detecting the target centers of all the marks in the surface image; specifically, performing binary segmentation on the image by threshold:

[0075]

[0076] In the formula, f(x,y) is the gray value of the image, x,y is the pixel coordinates, and Th is the threshold. Then, the pixel points with a gray value of 255 are region-grown, and the target is confirmed based on the area of ​​the target. If the number of points with a pixel value of 255 connected around the current pixel point is less than the threshold Ts, the current point is not the target; on the contrary, if the number of points with a pixel value of 255 is greater than the threshold Ts, the current point is confirmed to be the target:

[0077]

[0078] The center of the target is obtained by locating the centroid of the confirmed target. The centroid is the coordinate center of each point with a pixel value of 255:

[0079]

[0080] Where n is the number of points with a pixel value of 255 in the current target, (x i ,y i ) are the image coordinates of each point.

[0081] S23, taking the target center as a reference point, intercepting an image of a preset pixel size as a marking feature image corresponding to the marking;

[0082] Specifically, taking the target center as a reference point, an image of 200×200 pixels is intercepted as a feature image of the mark, and different marks can be distinguished by the feature image.

[0083] S24, using principal component analysis to establish a correspondence between the marker feature image and the marker number, reducing the marker feature image to a preset 10-dimensional dimension, and taking the first 10 principal components of the principal component matrix as a one-dimensional vector representing the marker, and determining a unique number;

[0084] Specifically, the principal component analysis method is used to establish the corresponding relationship between the marker feature image and the marker number, and the marker feature image of 200×200 pixels is reduced to a one-dimensional vector represented by 10 components, and the one-dimensional vector is used as the displacement number of the marker.

[0085] S25, obtaining a surface image with number marks.

[0086] As a further preferred embodiment of the method, the step S24 specifically includes:

[0087] S241, subtract the mean of each row vector (each variable) of the 200×200 matrix, so that the mean of the new row vector is 0, and obtain a new data set matrix X;

[0088] S242, find the covariance matrix of X, and find the eigenvalue λ and the unit eigenvector e of the covariance matrix;

[0089] S243, arranging the unit eigenvectors into a matrix in descending order of eigenvalues ​​to obtain a transformation matrix P, and calculating the principal component matrix according to PX;

[0090] S244, reduce the feature image to a specific 10 dimensions, and directly take the first 10 principal components of the principal component matrix; if there is no fixed requirement for the target dimension of the image, the variance contribution rate and the cumulative variance contribution rate can be calculated using the eigenvalues, and the first 10 principal components with the largest cumulative variance contribution rate are taken. These 10 principal components are the one-dimensional vectors representing the mark, and this vector is used as the feature information of the mark to determine the unique number.

[0091] As a further preferred embodiment of the method, the step of obtaining the relative position information of each mark on the surface of the object according to the image with numbered marks and establishing the corresponding relationship between the mark number and the mark position information specifically includes:

[0092] S31, stitching the images with number marks by an image stitching method to obtain a complete surface image;

[0093] S32, taking the complete surface image as a reference image and establishing a relationship between the image pixel coordinates of the reference image and the surface coordinates of the actual object;

[0094] S33, identifying and locating the markers on the reference image, and determining the correspondence between each marker and the object surface coordinates according to the relationship between the reference image pixel coordinates and the actual object surface coordinates.

[0095] Specifically, assuming that the local area of ​​the frustum surface is an approximate plane, the relationship between the image plane point and the two-dimensional point on the local area of ​​the object surface can be expressed as:

[0096]

[0097] Among them, a, b, c, d, e, and f are six parameters describing the deformation between two planes, (u, v) are the image pixel coordinates, and (x, y) are the coordinates on the approximate plane of the frustum surface. The deformation parameters can be obtained by controlling the surface points (u i ,v i ) and the corresponding point (x i ,y i ) Combine the following equations to calculate:

[0098]

[0099] The v direction of the reference image corresponds to the axis height direction of the rotating body, and the u direction of the reference image corresponds to the rotation angle of the rotating body. The surface point of the truncated cone is represented by its corresponding axis height and rotation angle as (θ, h). The corresponding relationship between the image coordinates (u, v) and the cylindrical side surface coordinates (θ, h) is:

[0100]

[0101] Among them, a and b are scale parameters, which can be obtained through camera calibration or through the control points on the surface of the object (θ i ,h i ) and the corresponding point in the image (u i ,v i ) is combined to obtain the following set of equations:

[0102]

[0103] Each mark is identified and located on the reference image, and the corresponding relationship between each mark and the object surface coordinates is determined based on the relationship between the reference image pixel coordinates and the actual object surface coordinates.

[0104] As a further preferred embodiment of the method, the step of acquiring the real-time image to be tested and detecting the mark in the real-time image to be tested to obtain the mark to be tested specifically includes:

[0105] S41, determining the precise position of each marking center point on the surface of the object according to the transformation formula;

[0106] Specifically, the precise position of the truncated cone surface corresponding to each mark center point is measured, such as a two-dimensional coordinate or a three-dimensional coordinate. c ,y c ) and three-dimensional coordinates (x w ,y w ,z w ) can be directly measured by a two-dimensional or three-dimensional coordinate measuring instrument; or a three-dimensional scanner can be used to scan and obtain a three-dimensional point cloud of the marking point and other parts of the frustum surface, thereby obtaining the three-dimensional coordinates (x w ,y w ,z w ).

[0107] Using image measurement technology, the position of the frustum surface corresponding to the center point of the mark can be determined according to the imaging parameters: let the image coordinates of the center of the mark be (u, v), then its coordinates with the world coordinates (x w ,y w ,z w ) is as follows:

[0108]

[0109] As shown in the above formula, the first matrix on the right is the camera intrinsic parameter matrix, and the second matrix is ​​the camera extrinsic parameter matrix. The camera intrinsic parameter matrix and extrinsic parameter matrix can be obtained through camera calibration methods such as Zhang Zhengyou calibration method. w ,y w ,z w ) represents the coordinates of the three-dimensional point on the frustum surface corresponding to the center of the mark. s is the Z coordinate of the center point in the camera coordinate system, (u, v) is the center image coordinate, (f x ,f y ) is the equivalent focal length of the camera, (c x ,c y ) is the principal point of the image, r ij (i,j=1,2,3) is the element of the rotation matrix R, t i (i=1,2,3) is the translation vector, (x w ,y w ,z w ) represents the three-dimensional point coordinates on the object surface corresponding to the center of the marker.

[0110] S42, performing real-time imaging on the surface of the object to obtain a real-time image to be measured;

[0111] S43, performing mark detection on the real-time image to be tested, and confirming the mark number corresponding to the mark in the real-time image to be tested based on vector comparison.

[0112] Specifically, the truncated cone surface is imaged in real time, and the real-time image is marked and positioned (the detection process is the same as S3), the mark number corresponding to the current mark is confirmed, and the corresponding coordinates of the center of the real-time image on the reference image are calculated. The specific steps are as follows:

[0113] Mark detection and confirmation: According to the PCA dimensionality reduction criterion, the feature image of the current mark is reduced in dimension to obtain a one-dimensional vector with 10 components. This vector is compared with the one-dimensional vectors of all the marks in the reference image, and the mark number with the largest similarity in the reference image is used as the current mark number. i}、{b i The similarity C of} is expressed as:

[0114]

[0115] According to the marker positioning, determine the position of the center of the real-time image on the reference image: Let the coordinates of the marker detected on the real-time image on the real-time image be (u r ,v r ), according to the similarity of the marker vector, it is judged as the nth marker on the reference image. The coordinates of the nth marker (center) on the reference image are (x n ,y n ), then the coordinates of the center of the real-time image on the reference image are obtained according to the mark (u c ,v c )for

[0116]

[0117] Among them, width and height are the pixel width and height of the real-time image respectively.

[0118] Further as a preferred embodiment of the method, the step of calculating the surface position of the object corresponding to the current real-time image to be measured according to the position of the mark to be measured in the real-time image to be measured and the surface position information of the object corresponding to the mark, specifically includes this step, specifically including:

[0119] S51 . Obtain corresponding coordinates of the center of the real-time image on the reference image according to the marking number.

[0120] S52, determining the object surface point corresponding to the center of the real-time image according to the correspondence between the reference image pixel coordinates and the object surface parameters and the coordinates of the center of the real-time image on the reference image;

[0121] S53, obtaining the object surface position corresponding to the current real-time image to be measured according to the object surface point corresponding to the center of the real-time image;

[0122] Specifically, the coordinates of the center of the real-time image on the reference image (u c ,v c ), the object surface point corresponding to the center of the real-time image can be determined based on the correspondence between the pixel coordinates of the reference image and the object surface parameters.

[0123] When the object surface is flat, the real-time image center (u c ,v c ) corresponds to the two-dimensional coordinates (x c ,y c ) can be expressed as:

[0124]

[0125] According to the two-dimensional coordinates (x c ,y c ), the displacement and other parameters of the corresponding point in the real-time graph center can be directly calculated.

[0126] For a truncated cone, the v direction of the reference image corresponds to the height direction of the rotation axis of the truncated cone, and the u direction of the reference image corresponds to the rotation angle of the truncated cone. The center of the real-time image (u c ,v c ) corresponds to the object surface point (θ c ,h c ) is expressed as:

[0127]

[0128] The object surface position corresponding to the current real-time image to be measured includes one-dimensional coordinates, two-dimensional coordinates, three-dimensional coordinates, one-dimensional rotation angle and two-dimensional rotation angle.

[0129] According to the real-time graph center (u c ,v c ) corresponds to the object surface point (θ c ,h c ), the change of one-dimensional angle and two-dimensional angle can be calculated:

[0130] The corresponding relationship between the image position and the one-dimensional rotation angle of the object: Let the circumference of the frustum be L, the direction of the axis of the frustum be the x direction, the direction of the circumference of the frustum be the y direction, let the pixel coordinates of the center of the image be (u, v), and the corresponding two-dimensional coordinates of the object surface be (x c ,y c ), then the rotation angle corresponding to this point is:

[0131]

[0132] In the above formula, θ is the rotation angle of the rotating body to be measured, y0 is the origin of the circumference of the outer surface of the rotating body, and y c is the center coordinate point of the unfolded outer surface of the revolution, and L is the circumference length of the unfolded outer surface of the revolution.

[0133] The corresponding relationship between the image position and the two-dimensional rotation angle (latitude and longitude) of the spherical surface: the image center coordinates are (u, v) and the corresponding world coordinates on the spherical surface are (x w ,y w ,z w ), assuming that the world coordinate system is based on the center of the sphere as the origin, the longitude and latitude are:

[0134]

[0135] In the above formula, the image center coordinates are (u, v) and the corresponding world coordinates on the surface of the sphere to be measured are (x w ,y w ,z w ), α is the longitude of the sphere to be measured, and β is the latitude of the sphere to be measured.

[0136] One-dimensional angle change: The one-dimensional angle change of the object corresponding to the center of the image during two real-time imaging is calculated as follows:

[0137] Δθ=θ c1 -θ c2 =au c1 -au c2

[0138] Two-dimensional angle change: The two-dimensional angle change of the sphere surface corresponding to the center of the image during two real-time imaging (assuming that the origin is at the center of the sphere and the radius of the sphere is r) is calculated as follows:

[0139]

[0140] The present invention has the following advantages:

[0141] 1. Compared with grating technology and imaging encoder technology, which measure based on the theoretical position of scales and marks, the measurement basis of the present invention is the real position of the mark on the surface of the object to be measured. The present invention measures the random texture information and marks after production, obtains the actual position of each mark relative to the object to be measured with high precision, and then locates and measures the surface of the object based on the actual position of the mark (rather than the theoretical position), thereby avoiding the influence of factors such as processing error and installation error of the mark on the measurement accuracy. Such measurement is not only accurate and reliable, but also greatly reduces the requirements for processing technology and device materials.

[0142] 2. Compared with the information ring recognition technology, the present invention can directly produce random speckle information and marks (spraying, pasting) on ​​the surface of the object, without the need to produce and install information rings, high-precision processing and production of coding marks, and the method is simpler and more economical.

[0143] 3. Compared with the information ring, which can only measure cylinders, the angle measurement is performed by measuring the one-dimensional displacement of the cylinder side. The present invention can be directly applied to the surface displacement measurement and angle measurement of truncated cones (side surfaces and upper and lower bottom surfaces), cones, disks and any irregular rotating bodies.

[0144] 4. Compared with the information ring recognition and dual-camera measurement technology, the traversal search image positioning method adopted by them is inefficient and difficult to use for real-time rapid measurement. The present invention proposes a method for directly detecting and identifying the mark for image positioning, which does not require traversal search of all pixels of the reference image during image positioning, and has the advantages of high execution efficiency, good real-time performance, simplicity and reliability.

[0145] 5. Compared with the single identification coding measurement method adopted by imaging encoders and information ring identification, the present invention adopts simple patterns without coding (such as dots, lines, crosshairs, etc.), and can also be compatible with coded identification. This not only makes the processing and production of the identification simpler and more convenient, completely gets rid of the high-precision processing requirements, but also can make the camera imaging range smaller, thereby obtaining higher measurement accuracy.

[0146] 6. Compared with the dual-camera measurement solution, the present invention only needs a single camera to realize the recognition and positioning of the marking points on the surface of the object, making the entire measurement process simpler and more efficient.

[0147] 7. Compared with the existing technology that can only perform high-precision measurement of one-dimensional rotation angle and one-dimensional displacement, the present invention can also be used to measure parameters such as two-dimensional translation, three-dimensional translation, and two-dimensional rotation angle.

[0148] like Figure 2 As shown, a high-precision positioning system for an object surface comprises:

[0149] A marking making module, used to make marks with a preset distribution density on the surface of an object to obtain a marked object;

[0150] A numbering module is used to photograph the marked object and number the marks in the image to obtain an image with numbered marks;

[0151] A marking position relationship module is used to obtain the relative position information of each mark on the surface of the object according to the image with numbered marks and establish a corresponding relationship between the mark number and the mark position information;

[0152] The image module to be tested is used to obtain the real-time image to be tested and detect the mark in the real-time image to be tested to obtain the mark to be tested;

[0153] The physical quantity solving module is used to calculate the surface position of the object corresponding to the current real-time image to be measured according to the position of the mark to be measured in the real-time image to be measured and the surface position information of the object corresponding to the mark.

[0154] The contents of the above method embodiments are all applicable to the present system embodiments. The functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0155] The above is a specific description of the preferred implementation of the present invention, but the invention is not limited to the embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for high-precision positioning of an object surface, characterized in that: The following steps are involved: Marks with a preset distribution density are made on the surface of the object to obtain a marked object; Photographing the marked object and numbering the marks in the image to obtain an image with numbered marks; Obtaining relative position information of each mark on the surface of the object according to the image with numbered marks and establishing a corresponding relationship between the mark number and the mark position information; Acquire a real-time image to be tested and detect a mark in the real-time image to be tested to obtain a mark to be tested; According to the position of the mark to be measured in the real-time image to be measured and the surface position information of the object corresponding to the mark, the surface position of the object corresponding to the current real-time image to be measured is calculated; The step of photographing the marked object and numbering the marks in the image to obtain the image with the numbered marks specifically includes: The surface of the marked object is photographed and imaged to obtain a surface image; The surface image is processed by threshold segmentation to detect the target centers of all the marks in the surface image; Taking the target center as the reference point, intercepting an image of a preset pixel size as a marking feature image corresponding to the mark; The principal component analysis method is used to establish the corresponding relationship between the marker feature image and the marker number, the marker feature image is reduced to a low dimension, and the first 10 principal components of the principal component matrix are taken as a one-dimensional vector representing the marker to determine the unique number; Get a surface image with numbered labels.

2. The method for high-precision positioning of an object surface according to claim 1, characterized in that: The step of making marks with a preset distribution density on the surface of the object to obtain the marked object specifically includes: Using a mark of a preset style, engraving the mark on the surface through a mark making method to obtain a marked object; The marks of the preset styles include line segments, dots, circles, squares, crosses and their combined shapes; The marking production method includes laser engraving, printing and etching; The engraving interval of the marks is less than half of the image frame.

3. The method for high-precision positioning of an object surface according to claim 2, characterized in that: The step of obtaining the relative position information of each mark on the surface of the object according to the image with numbered marks and establishing the corresponding relationship between the mark number and the mark position information specifically includes: The images with number marks are stitched together by an image stitching method to obtain a complete surface image; Taking the complete surface image as a reference image and establishing the relationship between the image pixel coordinates of the reference image and the surface coordinates of the actual object; The markers are identified and located on the reference image, and the corresponding relationship between each marker and the object surface coordinates is determined based on the relationship between the reference image pixel coordinates and the actual object surface coordinates.

4. The method for high-precision positioning of an object surface according to claim 3, characterized in that: The step of acquiring a real-time image to be tested and detecting a mark in the real-time image to be tested to obtain the mark to be tested specifically includes: Determine the precise position of each marking center point on the surface of the object according to the transformation formula; Perform real-time imaging on the surface of the object to obtain a real-time image to be measured; Perform marker detection on the real-time image to be tested, and confirm the marker number corresponding to the marker in the real-time image to be tested based on vector comparison.

5. A method for high-precision positioning of an object surface according to claim 4, characterized in that: The transformation formula is as follows: In the above formula, s is the Z coordinate of the center point in the camera coordinate system, (u,v) is the center image coordinate, (f x ,f y ) is the equivalent focal length of the camera, (c x ,c y ) is the principal point of the image, r ij (i,j=1,2,3) is the element of the rotation matrix R, t i (i=1,2,3) is the translation vector, (x w ,y w ,z w ) represents the three-dimensional point coordinates on the object surface corresponding to the center of the marker.

6. A method for high-precision positioning of an object surface according to claim 5, characterized in that: The step of calculating the surface position of the object corresponding to the current real-time image to be measured according to the position of the mark to be measured in the real-time image to be measured and the surface position information of the object corresponding to the mark specifically includes: Obtain the corresponding coordinates of the center of the real-time image on the reference image according to the marking number; According to the correspondence between the pixel coordinates of the reference image and the surface parameters of the object and the coordinates of the center of the real-time image on the reference image, the surface point of the object corresponding to the center of the real-time image is determined; According to the object surface point corresponding to the center of the real-time image, the object surface position corresponding to the current real-time image to be measured is obtained; The object surface position corresponding to the current real-time image to be measured includes one-dimensional coordinates, two-dimensional coordinates, three-dimensional coordinates, one-dimensional rotation angle and two-dimensional rotation angle.

7. A method for high-precision positioning of an object surface according to claim 6, characterized in that: The calculation formula of the one-dimensional rotation angle is as follows: In the above formula, θ is the rotation angle of the rotating body to be measured, y0 is the origin of the circumference of the outer surface of the rotating body, and y c is the center coordinate point of the unfolded outer surface of the revolution, and L is the circumference length of the unfolded outer surface of the revolution.

8. A method for high-precision positioning of an object surface according to claim 7, characterized in that: The calculation formula of the two-dimensional rotation angle is as follows: In the above formula, the image center coordinates are (u, v) and the corresponding world coordinates on the surface of the sphere to be measured are (x w ,y w ,z w ), α is the longitude of the sphere to be measured, and β is the latitude of the sphere to be measured.

9. A high-precision positioning system for an object surface, characterized in that: The method for high-precision positioning of an object surface according to claim 1 comprises: A marking making module, used to make marks with a preset distribution density on the surface of an object to obtain a marked object; A numbering module is used to photograph the marked object and number the marks in the image to obtain an image with numbered marks; A marking position relationship module is used to obtain the relative position information of each mark on the surface of the object according to the image with numbered marks and establish a corresponding relationship between the mark number and the mark position information; The image module to be tested is used to obtain the real-time image to be tested and detect the mark in the real-time image to be tested to obtain the mark to be tested; The physical quantity solving module is used to calculate the surface position of the object corresponding to the current real-time image to be measured according to the position of the mark to be measured in the real-time image to be measured and the surface position information of the object corresponding to the mark.

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