CN113012279B - A non-contact three-dimensional imaging measurement method, system and computer-readable storage medium - Google Patents

A non-contact three-dimensional imaging measurement method, system and computer-readable storage medium Download PDF

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CN113012279B
CN113012279B CN202110289260.5A CN202110289260A CN113012279B CN 113012279 B CN113012279 B CN 113012279B CN 202110289260 A CN202110289260 A CN 202110289260A CN 113012279 B CN113012279 B CN 113012279B
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王千
刘桦
房詠柳
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Shanghai Jiao Tong University
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Abstract

The invention relates to a non-contact three-dimensional imaging measurement method, which can accurately measure the three-dimensional change of a water surface in a large range, and can further eliminate various optical errors including lens distortion influence by using interpolation of multilayer still water surface reconstruction results as compensation of distortion errors; for one identification point, only the centroid is iteratively recalculated near the known position by using the corresponding result of the previous picture, and the whole picture does not need to be processed again; therefore, the calculation efficiency is greatly improved, more importantly, the centroid position of the identification point can be automatically tracked in the face of the dynamic change of the water wave surface, and therefore the position of the identification point in each camera is automatically matched.

Description

Non-contact three-dimensional imaging measurement method and system and computer readable storage medium
Technical Field
The invention relates to a non-contact three-dimensional imaging measurement method, a non-contact three-dimensional imaging measurement system and a computer readable storage medium.
Background
In the physical experiment research of hydrodynamics, often will measure the change of wave propagation in-process surface of water height, adopt the wave height appearance to measure surface of water height in traditional experiment wave pond. However, the wave height gauge has two disadvantages: one is that the wave height gauge is in contact with the water body, so that wave propagation is influenced to a certain extent; another is that the wave front height change can only be measured at one point, which is time consuming and laborious to perform in a large range and in an intensive measurement. If the non-contact multi-point measurement with a larger coverage area can be carried out, the height change of the free water surface during wave motion can be obtained more effectively, and more comprehensive data is provided for scientific research and production.
The prior art has the following problems:
firstly, in the prior art, the pictures taken by the camera at each moment are subjected to full-picture image analysis to obtain two-dimensional coordinates of the centroid of the identification point. Since the resolution of the picture is generally high, the amount of calculation for performing the image analysis of the full picture on each picture is large.
In the prior art, a perspective transformation algorithm is used for correcting the inclined light spot array into a rectangle. The algorithm of perspective transformation is to use the positions of four corners to perform graph transformation, so that the trapezoid is changed into a rectangle. However, when the local three-dimensional deformation of the waves is large, the inside of the light spot array cannot be regularly arranged after perspective transformation processing is carried out by utilizing the positions of the four vertex angles, and in order to solve the problem in the prior art, the number of the light spots cannot be excessively dense. Thus, when the local three-dimensional deformation of the waves is large, the light spot array after perspective transformation processing is irregular inside, but the light spots are few, and the light spot array can be sequenced according to a certain method. However, fewer spots will result in a reduced spatial resolution of the three-dimensional reconstruction technique, and a sufficiently dense spatial three-dimensional position measurement cannot be obtained.
And thirdly, when the measurement area is large, the distortion error of the camera lens is inevitably introduced, and the phenomena of large near objects and small far objects are generated. Although there is a lens distortion compensation coefficient in the calibration process, there are a variety of optical errors that may affect the measurement results in the actual measurement environment, and these optical errors including lens distortion are difficult to be handled all at once. If no other compensation correction is carried out, the high-precision measurement required by the hydrodynamic experiment cannot be met. Therefore, the three-dimensional reconstruction result of the wave surface in the prior art is difficult to be applied to scientific researches with higher precision requirements.
In conclusion, the prior art cannot perform rapid high-precision measurement on the water surface with large local deformation in a large measurement range.
Disclosure of Invention
Aiming at the problem that the prior art can not solve the problem of rapid high-precision measurement of the water surface with large local deformation in a large measurement range, the invention adopts the technical scheme that:
a non-contact three-dimensional imaging measurement method, the method comprising:
step 1, interpolating a reconstruction result of a multilayer still water plane to obtain a compensation value of lens distortion;
and 2, automatically inheriting the positions and the sequence of the identification points in the two adjacent pictures to realize the matching of the irregular light spot arrays, and obtaining the spatial three-dimensional coordinates of the identification points according to the compensation values.
Wherein, the step 1 specifically comprises:
step 1.1, calibrating a camera to obtain a mapping relation matrix R between a space three-dimensional coordinate and a two-dimensional pixel coordinate in a photo;
step 1.2, determining characteristic identification points on a static water surface;
step 1.3, calculating the centroid of the identification point based on the mapping relation matrix R, carrying out perspective transformation, changing the trapezoid image formed by the original light spot array into a rectangle, and completing automatic matching of the identification point;
step 1.4, solving three-dimensional coordinates of the identification points;
and step 1.5, subtracting the average value of the Z-direction height of all the identification points obtained in step 1.4, carrying out space surface fitting, and then calculating the error compensation value of the Z direction at the position.
The method according to claim 2, wherein the step 1 further comprises:
step 1.6, replacing the height of the water surface to obtain an error compensation value corresponding to each height;
and step 1.7, after the error compensation value is obtained, interpolating each space position (X, Y) in the Z direction by utilizing multiple planes.
Wherein, the step 1.5 specifically comprises:
deducting the average value of the Z-direction height of all the identification points obtained in the step 1.4, fitting based on a fitting formula, and fitting to obtain coefficients A-D to be determined; when the waiting coefficients A-D are determined;
the fitting formula shown is:
Figure GDA0003063852530000031
and solving a Z-direction value based on a fitting formula according to each point (X, Y) in a Z-direction plane of the space where the still water surface is positioned, wherein the value is an error compensation value of the lens distortion in the current plane.
Wherein the step 2 comprises:
step 2.1, acquiring a dynamic wave surface photo;
step 2.2, calculating the centroid of the first wave surface picture and carrying out perspective transformation;
2.3, searching the centroid of the next wave-front photo by adopting an iterative algorithm;
step 2.4, solving the three-dimensional coordinates of the identification points after automatic matching;
step 2.5, deducting an error compensation value;
step 2.6, repeat step repeat 2.3, 2.4 and 2.5 to process the picture at the next moment.
Wherein the step 2.3 comprises:
starting from the second picture taken at 2.1, when the picture at the new moment is processed, the centroid coordinates of the picture at the new moment, which are precisely determined for each identification point in the previous picture, are taken as the centroid coordinates of the picture at the new moment.
Wherein the step 2.4 comprises:
and solving the space three-dimensional coordinate of each identification point in the photo by combining the calibration result according to the centroid position and the automatically matched identification point.
The invention also provides a non-contact three-dimensional imaging measurement system, comprising:
the compensation value calculation module is used for interpolating the reconstruction result of the multilayer still water plane to obtain a compensation value of lens distortion;
and the coordinate calculation module is used for automatically inheriting the positions and the sequence of the identification points in the two adjacent pictures to realize the matching of the irregular light spot arrays and obtain the spatial three-dimensional coordinates of the identification points according to the compensation values.
The invention also provides a non-contact three-dimensional imaging measurement system, comprising:
a memory for storing a computer program,
a processor for invoking a computer program in memory to implement the method.
The invention also provides a computer-readable storage medium, which is characterized in that the storage medium stores a computer program; when invoked by a processor in a computing device, causes the computing device to perform the method.
The invention has the beneficial effects that:
1. the three-dimensional change of the water surface can be accurately measured in a large range. By utilizing the interpolation of the multi-layer still water surface reconstruction result as the compensation of the distortion error, various optical errors including the lens distortion influence can be further eliminated.
2. Can quickly process the larger local deformation of the water surface. For an identified point, only the centroid needs to be iteratively recalculated around the known position using the corresponding result of the previous picture, without having to reprocess the entire picture. Therefore, the calculation efficiency is greatly improved, and more importantly, the centroid position of the identification point can be automatically tracked in the face of the dynamic change of the water wave surface (when the position of the identification point is greatly deviated), so that the position of the identification point in each camera is automatically matched.
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The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a flow chart of a method of a preferred embodiment of the present invention;
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic views illustrating only the basic structure of the present invention in a schematic manner, and thus show only the constitution related to the present invention.
To facilitate the understanding of the invention, the terms involved are described:
hydrodynamics: the disciplines of water and other liquids' law of motion and its interaction with boundaries (e.g., structures) are studied.
Wave height instrument: an instrument for measuring and recording the height of waves at a given location. After the water surface is inserted into water, the feedback voltage values are different when the water surface heights are different.
Three-dimensional reconstruction of images: generally, at least 2 cameras are used for collecting the graphic features of the surface of an observed object, once the identification points are extracted from the graphic features, the three-dimensional position of each identification point on the surface of the object can be reconstructed in a computer by adopting an image processing algorithm, and therefore the three-dimensional shape of the object is obtained.
Marking points: this means that the camera captures the center position of the graphic features on the surface of the object when the image is reconstructed three-dimensionally. For the image processing algorithm, the graphic features are used to identify the surface of the object, so the center position of the graphic features is called an identification point.
Calibrating a camera: in image measurement processes and machine vision applications, in order to determine the correlation between the three-dimensional geometric position of a certain point on the surface of an object in space and the corresponding point in the image, a geometric model of camera imaging must be established, and the parameters of the geometric model are the parameters of the camera. The process of establishing the model to obtain the parameters is camera calibration.
And (3) centroid: the geometric center of the figure.
Image post-processing: the picture taken by the camera is digitized to obtain the desired graphical information. The conventional method comprises the following steps: noise reduction, binarization, opening and closing operation, centroid calculation and the like.
Perspective transformation: the method is characterized in that a perspective center, an image point and a target point are collinear, a bearing surface (perspective surface) rotates a certain angle around a trace line (perspective axis) according to a perspective rotation law, an original projection light beam is damaged, and the transformation of a projection geometric figure on the bearing surface can be still kept unchanged. Mathematically, it can be simply understood that: one graph is transformed into another graph according to a given formula.
Lens distortion: the perspective distortion inherent to the optical lens is a general term that makes it impossible to maintain the planar characteristic of the object image. For example, when an object is shot by a wide-angle lens, there is a phenomenon that "a near object is large and a far object is small", which is distortion caused by lens distortion.
Fitting: a series of points on a plane are connected by a smooth curve (surface).
Interpolation: the continuous function is interpolated on the basis of the discrete data such that the continuous curve passes through all given discrete data points. Here to fill the gaps between pixels in the image transformation.
As shown in fig. 1, a non-contact three-dimensional imaging measurement method of the present invention includes:
step 1, interpolating a reconstruction result of a multilayer still water plane to obtain a compensation value of lens distortion;
and 2, automatically inheriting the positions and the sequence of the identification points in the two adjacent pictures to realize the matching of the irregular light spot arrays, and obtaining the spatial three-dimensional coordinates of the identification points according to the compensation values.
The first step mainly aims to reduce optical errors by interpolating reconstruction results of a multilayer still water plane to obtain a compensation value of lens distortion, and the specific method comprises the following steps:
1.1 calibration. And (3) fixing at least two high-speed cameras above the wave pool to obtain a mapping relation matrix R between the space three-dimensional coordinates in the formula (1) and the two-dimensional pixel coordinates in the photo. A Zhangzhengyou calibration method is selected in the wave pool, so that calibration can be realized conveniently and quickly.
In order to carry out non-contact multi-point measurement with larger coverage area, an image three-dimensional reconstruction technology is adopted, namely, a plurality of cameras shoot the water surface from different angles, and the three-dimensional shape of the water surface can be reconstructed by carrying out image processing on the pattern with certain characteristic marks in the water surface picture.
The core technical principle of the image three-dimensional technology is shown in formula (1).
Figure GDA0003063852530000071
Wherein n represents the nth camera (n is not less than 2). The first step is "calibration". And calibrating the cameras to obtain a mapping relation matrix R of two-dimensional pixel coordinates (X, Y) and three-dimensional space coordinates (X, Y, Z) in the picture shot by each camera. The second step is "identify". After shooting a space object by a camera, determining an ith space identification point (X) through image processingi,Yi,Zi) Corresponding two-dimensional pixel coordinates (x) in all n camera imagesin,yin). The third step is "match". For each identification point, it is necessary to determine which of the many identification points of each camera takes a picture corresponds to. Once determined, the formula (1) can be solved in a row to obtain the three-dimensional coordinates of the ith space identification point (Xi,Yi,Zi)。
In the prior art, the first step of calibration is a normalized process, and has no special points. The performance effect of three-dimensional reconstruction is mainly determined by the second step "recognition" and the third step "matching". The stereo reconstruction of image three-dimensional technology for solid surface identification points has been widely used in many fields (such as widely used binocular stereo reconstruction technology), and the fundamental reason is that the graphic identification points of the solid surface are easy to capture (i.e. the two-dimensional pixel coordinates of the solid surface in all photos are easy to determine). However, in the field of hydrodynamics, the surface movement causes the surface identification point to have a strong dynamic course. The irregular deformation and movement of the identification points makes it difficult to efficiently capture and match them, making conventional three-dimensional techniques of images difficult to apply. Moreover, when the shooting range and the surface deformation are large, the wide-angle camera matched with the camera can introduce lens distortion which cannot be completely eliminated, so that the target at the center of the lens is closer, and the targets at the periphery of the lens are farther. Although the lens distortion error is eliminated to some extent during the "calibration" process. However, when the water wave surface is deformed greatly, the lens error will still cause the measurement accuracy to be reduced.
1.2 shoot still water surface. All cameras shoot the water level in the water surface static state synchronously. Note that, at this time, a characteristic mark point is required on the still water surface, and can be obtained by a laser or a projector transmission method.
1.3 calculate the centroid and perform perspective transformation. Obtaining the two-dimensional coordinates of the centroid of each identification point in the picture, namely (x) in formula (1), by using a traditional image post-processing algorithmin,yin). At the moment, the water surface is static, and the arrangement of the identification points is regular, so that the pictures can be subjected to perspective transformation by using the formulas (2) and (3), the trapezoid images formed by the original light spot arrays are changed into rectangles, and the automatic matching of the identification points is completed.
Figure GDA0003063852530000081
Figure GDA0003063852530000082
In the formula (2), xn,ynIs the two-dimensional coordinates of the four vertexes of the light spot array in the original picture,
Figure GDA0003063852530000083
four vertexes of the rectangle are designated after transformation, and undetermined global transformation coefficients a-h can be obtained. Substituting a-h into formula (3) to transform the original quadrilateral light spot array into a rectangular array. In the formula (3), xi,yiIs the two-dimensional coordinates of any pixel of the original photograph,
Figure GDA0003063852530000084
for the perspective transformed pixel coordinates, w is an arbitrary scale factor used to enlarge or reduce the image.
And 1.4, solving the three-dimensional coordinates of the identification points. Substituting the calibration result of 1.1 and the matching result of 1.3 into the formula (1) to obtain a solution, and obtaining the three-dimensional space position (Xi, Yi, Zi) of each identification point
1.5 fitting the space surface. Since one of the main sources of optical errors is that the distortion caused by the lens can cause the near-far situation in the depth of field direction (generally, the Z direction), and the shape of the camera negative is rectangular, the error value caused by the lens distortion can be approximately regarded as an elliptic paraboloid in space. I.e. the three-dimensional spatial position (Xi, Yi, Zi) of each identified point solved in 1.4, will not perfectly lie in the same plane, but will be distributed on an elliptic paraboloid similar to the form of equation (4). And subtracting the average value of the Z-direction height of all the identification points obtained in the step 1.4, and substituting all the identification points near a zero reference surface in the Z direction into a formula (4) for fitting to obtain undetermined coefficients A-D. After the coefficients A to D to be determined are determined, for each point (X, Y) in the Z-direction plane of the space where the current still water surface is located, the Z-direction value at the position can be obtained through a formula (4), and the value is an error compensation value of the lens distortion in the current plane. In other words, in practical use, after three-dimensional reconstruction obtains the spatial coordinates of one identification point, if the Z-direction height of the coordinates is equal to the Z-direction height of the current still water surface, an elliptic paraboloid equation should be fitted according to this step, and the corresponding Z-direction compensation value at X, Y coordinates of the elliptic paraboloid equation is subtracted, so that the optical error mainly caused by lens distortion is reduced.
Figure GDA0003063852530000091
1.6 changing the water level. Section 1.5 is only to compensate for optical errors in the reconstruction of one still surface. When the surface of water fluctuates greatly, need carry out optical error's compensation to a plurality of still water levels in the height range to improve the reconstruction precision when the surface of water fluctuates greatly.
1.7 multiple hydrostatic interpolation. To further reduce optical errors, a multi-plane interpolation correction method is used. Because the actually reconstructed Z-direction height does not exactly fall in the water surface height selected in 1.6, after obtaining a plurality of groups of error compensation values of the water surface, interpolating each space position (X, Y) in the Z direction by utilizing a plurality of planes, and obtaining the error compensation value at any Z-direction height.
And after the first step is completed, the reconstruction of the fluctuating three-dimensional water surface can be started. The main method of the second step is that the positions and the sequence of the identification points are automatically inherited in two adjacent pictures, so that the matching of the irregular light spot array can be quickly realized, and the space three-dimensional coordinates of the identification points are obtained. The method comprises the following concrete steps:
2.1 shooting dynamic wave surface. After the first step is completed, the dynamic wave surface with wave motion is shot by a high-speed camera without changing the position of the camera. Note that at least it is ensured that in the initial state, one picture is taken from the time the water surface is still, i.e. the state of fig. 1. The choice of using a high speed camera is 2.3 in preparation for ensuring that the dynamic course of the water wave surface does not change significantly in successive photographs.
2.2 centroid is calculated for the first sheet and perspective transformed. As in 1.3, but only one of the still water surfaces was calculated in all pictures taken at 2.1. For this sheet, the array of identification points is transformed into a rectangle by a perspective transformation. After this sheet, the array of marker points will gradually be out of alignment with the perspective transformation due to the water surface fluctuation.
2.3 search for the centroid for the next one using an iterative algorithm. Starting from the second picture taken at 2.1, when processing a new picture at a time, there is no need to search through the whole picture to retrieve the position of each identified point, but an iterative algorithm is used. The method is realized by taking the centroid coordinate of each identification point in the previous picture which is accurately determined as an estimation value, and only needing to search again by a graphical processing method within a range which is larger than the size of each identification point by taking the estimation value as the center in the new picture. The iterative algorithm can be used for processing the dynamic process because a high-speed camera is used, so that the position of the identification point does not move greatly in two continuous photos, and the shape of the identification point does not change obviously.
And 2.4, solving the three-dimensional coordinates of the identification points after automatic matching. The iterative algorithm of 2.3 not only simplifies the searching and identifying process of the centroid of the identification point, but also can realize the matching process without perspective change. Since the position of each identification point is iteratively calculated from the position of the last corresponding point, the recording order of the identification points in the computer is inherited. This allows each identification point in the new picture to automatically achieve a match in each camera picture. Therefore, even if the identification point array is locally shifted due to the dynamic motion of the waves, the use of the centroid iteration algorithm of 2.3 can still ensure that the identification points are automatically matched. And substituting the centroid position and the automatically matched identification points into a formula (1) in combination with the calibration result, so that the spatial three-dimensional coordinate of each identification point in the new sheet can be obtained through solving.
2.5 deduct the error compensation value. For the spatial three-dimensional coordinate value of each identification point obtained in 2.4, the error compensation value at the corresponding position is found in 1.7, and the final measurement value can be obtained after deduction.
2.6 processing the picture at the next moment. Repeat 2.3, 2.4 and 2.5. All processing is completed until the last picture taken in 2.1 is processed.
The invention adopts an iterative identification method to track and capture the dynamic position of each identification point. Meanwhile, before three-dimensional wave surface reconstruction, an elliptic paraboloid equation is used for fitting a reconstruction result of the still water surface, and interpolation of multiple layers of still water surfaces is used as compensation of optical errors. Therefore, a three-dimensional reconstruction algorithm can be rapidly and accurately realized, the three-dimensional position of the water surface identification point is obtained by utilizing the formula (1), and large-range and high-precision three-dimensional wave surface data are provided for a hydrodynamic experiment.
The invention also provides a non-contact three-dimensional imaging measurement system, comprising:
the compensation value calculation module is used for interpolating the reconstruction result of the multilayer still water plane to obtain a compensation value of lens distortion;
and the coordinate calculation module is used for automatically inheriting the positions and the sequence of the identification points in the two adjacent pictures to realize the matching of the irregular light spot arrays and obtain the spatial three-dimensional coordinates of the identification points according to the compensation values.
The invention also provides a non-contact three-dimensional imaging measurement system, comprising:
a memory for storing a computer program,
a processor for invoking a computer program in memory to implement the method.
The invention also provides a computer-readable storage medium, which is characterized in that the storage medium stores a computer program; when invoked by a processor in a computing device, causes the computing device to perform the method.
The invention has the beneficial effects that:
1. the three-dimensional change of the water surface can be accurately measured in a large range. By utilizing the interpolation of the multi-layer still water surface reconstruction result as the compensation of the distortion error, various optical errors including the lens distortion influence can be further eliminated.
2. Can quickly process the larger local deformation of the water surface. For an identified point, only the centroid needs to be iteratively recalculated around the known position using the corresponding result of the previous picture, without having to reprocess the entire picture. Therefore, the calculation efficiency is greatly improved, more importantly, the centroid position of the identification point can be automatically tracked in the face of the dynamic change of the water wave surface, and therefore the position of the identification point in each camera is automatically matched.
In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.

Claims (10)

1.一种非接触三维成像测量方法,其特征在于,所述方法包括:1. A non-contact three-dimensional imaging measurement method, wherein the method comprises: 步骤1,通过对多层静水面的重构结果进行插值,得到镜头畸变的补偿值;Step 1: Obtain the compensation value of lens distortion by interpolating the reconstruction result of the multi-layer still water surface; 步骤2,通过将标识点位置和顺序在相邻两张图片中自动继承,实现不规则光斑阵列的匹配,根据补偿值计算标识点的空间三维坐标;Step 2, by automatically inheriting the position and order of the identification points in two adjacent pictures, to realize the matching of the irregular light spot array, and to calculate the spatial three-dimensional coordinates of the identification points according to the compensation value; 其中,所述步骤1具体包括:Wherein, the step 1 specifically includes: 步骤1.1,相机标定,获取空间三维坐标与照片中二维像素坐标之间的映射关系矩阵R;Step 1.1, the camera is calibrated, and the mapping relationship matrix R between the three-dimensional spatial coordinates and the two-dimensional pixel coordinates in the photo is obtained; 步骤1.2,确定静水面上的特征标识点,其中,静水面为水面静止状态下的水平面;Step 1.2, determine the characteristic identification points on the still water surface, wherein the still water surface is the horizontal plane under the static state of the water surface; 步骤1.3,基于映射关系矩阵R计算标识点形心并进行透视变换,将原始光斑阵列构成的不规则四边形图像改变为矩形,完成标识点的自动匹配;Step 1.3, based on the mapping relationship matrix R, calculate the centroid of the marking point and perform perspective transformation, change the trapezoidal image formed by the original light spot array into a rectangle, and complete the automatic matching of the marking point; 步骤1.4,求解标识点三维坐标;Step 1.4, solve the three-dimensional coordinates of the identification point; 步骤1.5,将步骤1.4中的所有标识点扣除其Z向高度的平均值,进行空间曲面拟合,然后求出此位置处Z向的误差补偿值;Step 1.5, deduct the average value of its Z-direction height from all the identification points in step 1.4, perform space surface fitting, and then obtain the Z-direction error compensation value at this position; 步骤1.6,更换水面高度,获取各个高度对应的误差补偿值;Step 1.6, replace the water surface height, and obtain the error compensation value corresponding to each height; 步骤1.7,获取误差补偿值后,对每个空间位置(X,Y)在Z向上利用多平面进行插值。Step 1.7, after obtaining the error compensation value, use multi-plane interpolation for each spatial position (X, Y) in the Z direction. 2.如权利要求1所述的方法,其特征在于,所述步骤1.5具体包括:2. The method of claim 1, wherein the step 1.5 specifically comprises: 将步骤1.4中的所有标识点扣除其Z向高度的平均值,基于拟合公式进行拟合,拟合得到待定系数A~D;其中,All identification points in step 1.4 are deducted from the average value of their Z-direction heights, and the fitting is performed based on the fitting formula, and the undetermined coefficients A to D are obtained by fitting; wherein, 所述拟合公式为:
Figure FDA0003385478430000011
The fitting formula is:
Figure FDA0003385478430000011
当待定系数A~D确定后,根据静水面所处在的空间Z向平面中的每个点(X,Y),基于拟合公式求出Z向的值,将所述Z向的值确定为镜头畸变在当前平面的误差补偿值。After the undetermined coefficients A to D are determined, according to each point (X, Y) in the space Z-direction plane where the still water surface is located, the Z-direction value is obtained based on the fitting formula, and the Z-direction value is determined. The error compensation value for the lens distortion in the current plane.
3.如权利要求1或2所述的方法,其特征在于,所述步骤2包括:3. The method of claim 1 or 2, wherein the step 2 comprises: 步骤2.1,获取动态波面照片;Step 2.1, obtain dynamic wavefront photos; 步骤2.2,对第一张波面照片计算形心并进行透视变换;Step 2.2, calculate the centroid of the first wavefront photo and perform perspective transformation; 步骤2.3,对下一张波面照片采用迭代算法搜索形心;Step 2.3, using an iterative algorithm to search the centroid for the next wavefront photo; 步骤2.4,自动匹配后求解标识点三维坐标;Step 2.4, solve the three-dimensional coordinates of the identification point after automatic matching; 步骤2.5,扣除误差补偿值;Step 2.5, deduct the error compensation value; 步骤2.6,重复步骤2.3、步骤2.4和步骤2.5,以处理下一时刻的照片。Step 2.6, repeat step 2.3, step 2.4 and step 2.5 to process the photo for the next moment. 4.如权利要求3所述的方法,其特征在于,所述步骤2.3包括:4. The method of claim 3, wherein the step 2.3 comprises: 从步骤2.1拍摄的第二张照片开始,在处理新一个时刻的照片时,将前一张照片中每个标识点已精确确定的形心坐标作为新一个时刻照片的形心坐标。Starting from the second photo taken in step 2.1, when processing a photo at a new moment, the centroid coordinates of each identification point in the previous photo that have been accurately determined are taken as the centroid coordinates of the photo at a new moment. 5.如权利要求4所述的方法,其特征在于,所述步骤2.4包括:5. The method of claim 4, wherein the step 2.4 comprises: 根据形心坐标和自动匹配的标识点,结合标定结果求解照片中每个标识点的空间三维坐标。According to the centroid coordinates and the automatically matched identification points, combined with the calibration results, the spatial three-dimensional coordinates of each identification point in the photo are solved. 6.如权利要求3所述的方法,其特征在于,所述步骤2.1具体包括:6. The method of claim 3, wherein the step 2.1 specifically comprises: 用高速相机对有波浪运动的动态波面进行拍摄,获取动态波面照片。Use a high-speed camera to shoot dynamic wavefronts with wave motion to obtain dynamic wavefront photos. 7.一种非接触三维成像测量系统,其特征在于,所述系统包括:7. A non-contact three-dimensional imaging measurement system, wherein the system comprises: 补偿值计算模块,通过对多层静水面的重构结果进行插值,得到镜头畸变的补偿值;The compensation value calculation module obtains the compensation value of lens distortion by interpolating the reconstruction results of the multi-layer still water surface; 坐标计算模块,通过将标识点位置和顺序在相邻两张图片中自动继承,实现不规则光斑阵列的匹配,根据补偿值得到标识点的空间三维坐标;The coordinate calculation module realizes the matching of irregular light spot arrays by automatically inheriting the position and order of the identification points in two adjacent pictures, and obtains the spatial three-dimensional coordinates of the identification points according to the compensation value; 其中,所述补偿值计算模块具体用于执行:Wherein, the compensation value calculation module is specifically used to execute: 相机标定,获取空间三维坐标与照片中二维像素坐标之间的映射关系矩阵R;The camera is calibrated, and the mapping relationship matrix R between the three-dimensional coordinates in space and the two-dimensional pixel coordinates in the photo is obtained; 确定静水面上的特征标识点,其中,静水面为水面静止状态下的水平面;Determine the feature identification points on the still water surface, wherein the still water surface is the horizontal plane under the static state of the water surface; 基于映射关系矩阵R计算标识点形心并进行透视变换,将原始光斑阵列构成的不规则四边形图像改变为矩形,完成标识点的自动匹配;Based on the mapping relationship matrix R, the centroid of the identification point is calculated and perspective transformation is performed, and the irregular quadrilateral image formed by the original light spot array is changed into a rectangle, and the automatic matching of the identification point is completed; 求解标识点三维坐标;Solve the three-dimensional coordinates of the identification point; 将求解的所有标识点扣除其Z向高度的平均值,进行空间曲面拟合,然后求出此位置处Z向的误差补偿值;The average value of the Z-direction height is deducted from all the identified points to be solved, and the space surface fitting is performed, and then the Z-direction error compensation value at this position is obtained; 更换水面高度,获取各个高度对应的误差补偿值;Change the water surface height and obtain the error compensation value corresponding to each height; 获取误差补偿值后,对每个空间位置(X,Y)在Z向上利用多平面进行插值。After obtaining the error compensation value, use multi-plane interpolation for each spatial position (X, Y) in the Z direction. 8.如权利要求7所述的非接触三维成像测量系统,其特征在于,所述坐标计算模块具体用于:8. The non-contact three-dimensional imaging measurement system according to claim 7, wherein the coordinate calculation module is specifically used for: 获取动态波面照片;Get dynamic wavefront photos; 对第一张波面照片计算形心并进行透视变换;Calculate the centroid and perform perspective transformation on the first wavefront photo; 对下一张波面照片采用迭代算法搜索形心;Use an iterative algorithm to search the centroid for the next wavefront photo; 自动匹配后求解标识点三维坐标;After automatic matching, solve the three-dimensional coordinates of the identification point; 扣除误差补偿值;Deduct the error compensation value; 重复执行对下一张波面照片采用迭代算法搜索形心、自动匹配后求解标识点三维坐标和扣除误差补偿值,以处理下一时刻的照片。Repeatedly execute the iterative algorithm to search the centroid of the next wavefront photo, solve the three-dimensional coordinates of the identification point after automatic matching, and deduct the error compensation value to process the photo at the next moment. 9.一种非接触三维成像测量系统,其特征在于,所述系统包括:9. A non-contact three-dimensional imaging measurement system, wherein the system comprises: 存储器,用于存储计算机程序,memory for storing computer programs, 处理器,用于调用存储器中的计算机程序以实现权利要求1-6任一项所述的方法。A processor for invoking a computer program in the memory to implement the method of any one of claims 1-6. 10.一种计算机可读存储介质,其特征在于,所述存储介质中存储有计算机程序;当所述计算机程序被计算设备中的处理器调用时,使得所述计算设备执行如权利要求1-6任一项所述的方法。10. A computer-readable storage medium, characterized in that, a computer program is stored in the storage medium; when the computer program is called by a processor in a computing device, the computing device is made to execute the method according to claim 1- 6 The method of any one.
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