CN112819900A - Method for calibrating internal azimuth, relative orientation and distortion coefficient of intelligent stereography - Google Patents
Method for calibrating internal azimuth, relative orientation and distortion coefficient of intelligent stereography Download PDFInfo
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Abstract
The invention belongs to the technical field of photogrammetry, and discloses an intelligent stereo photography internal direction, relative orientation and distortion coefficient calibration method. The method mainly comprises the following steps: the method is used for establishing a nonlinear control equation set calibrated by an internal orientation element, a relative orientation parameter and a lens distortion coefficient. The method comprises the following steps: measuring the length of a line segment in an object measurement region, collecting images, acquiring left and right image coordinates of end points of the line segment, and establishing a corresponding control equation set; feature point extraction, homonymy point matching method and corresponding control equation set establishment method. An initial value acquisition method of a nonlinear equation set. Based on the conditional adjustment theory with parameters, the characteristic points with larger errors are removed through iteration, and the characteristic points gradually approach to the true value. The invention has simple and practical calibration, and is suitable for short-distance small-area measurement and long-distance large-area measurement. The invention creatively provides a resolving method of the nonlinear equation set, and ensures the convergence of the equation and the precision of the calibration parameters.
Description
Technical Field
The invention belongs to the technical field of photogrammetry, and particularly relates to an intelligent method for calibrating an internal direction, relative orientation and a distortion coefficient in stereo photography.
Background
At present, a non-measurement camera is generally adopted for close-range measurement, and parameters such as internal orientation elements, relative orientation parameters, lens distortion coefficients and the like of the camera need to be calibrated in advance when the non-measurement camera performs photogrammetry. Common methods are two-dimensional target calibration methods, three-dimensional target calibration methods, and the like. The typical two-dimensional target calibration method is a checkerboard (dot) calibration method for Zhangyingyou, and the method generally comprises the steps of calibrating internal orientation elements and distortion coefficients indoors, then carrying out on-site measurement, and utilizing an on-site measurement image to calibrate relative orientation parameters. The method is commonly used for calibrating a camera with a short distance and a small field of view, and is difficult to calibrate the camera with a large CCD surface and a large focal length when measuring the camera with a long distance and a large field of view. Research institutions related to stereo photogrammetry often build professional three-dimensional camera calibration fields, the calibration precision of the three-dimensional camera calibration fields is high, but the three-dimensional camera calibration fields are only opened to some people, internal orientation elements and distortion coefficients need to be calibrated indoors and then measured on site, relative orientation parameters are calibrated by using images measured on site, and the three-dimensional camera calibration fields are difficult to process and are not suitable for long-distance large-view-field measurement.
Through the above analysis, the problems and defects of the prior art are as follows: the existing two-dimensional target and three-dimensional target calibration methods are usually used for calibrating cameras with short measurement distance and small view field, but calibration is difficult when measuring large scenes with large measurement distance.
The difficulty in solving the above problems and defects is: the construction of large-size two-dimensional and three-dimensional targets is one way to solve the problem of long-distance measurement and calibration of large scenes, but the method has high processing difficulty, high cost and difficult popularization.
The significance of solving the problems and the defects is as follows: aiming at the problems, the invention provides a photogrammetry calibration method based on a distance equation, which has the advantages of simple calibration, easy operation, time and labor saving and low cost, is suitable for short-distance small-area measurement and long-distance large-view-field measurement, and is favorable for promoting the development of long-distance large-view-field photogrammetry such as photography sea wave measurement.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an intelligent stereo photography internal direction, relative orientation and distortion coefficient calibration method.
The invention is realized in this way, a calibration method of inner direction, relative orientation and distortion coefficient of intelligent stereo photography, the calibration method of inner direction, relative orientation and distortion coefficient of intelligent stereo photography includes: selecting a small number of characteristic points, sequentially and directly solving the characteristic points to the solution of a 13-parameter control equation set in a relative orientation manner, and determining the initial value of the control equation set by the parameters from less to more; and expanding the number of the characteristic points, gradually eliminating the characteristic point pairs with lower matching quality in an iterative mode in sequence, gradually approaching the true value of the parameter to be solved, and finally obtaining the accurate internal orientation element, distortion coefficient and relative orientation parameter value.
Further, the method for calibrating the internal orientation, the relative orientation and the distortion coefficient of the intelligent stereography comprises the following steps:
measuring the length of a line segment in an object space measuring region, and preparing for a column distance equation;
acquiring left and right image coordinates of the end points of the acquired line segments of the image, and listing partial control equations;
uniformly generating 10 multiplied by 10 characteristic points, determining homonymous points of the characteristic points, and preparing for a column coplanarity equation;
establishing a nonlinear control equation set for calibrating the internal orientation element, the relative orientation parameter and the lens distortion coefficient;
step five, determining an initial value of an iterative solution of the nonlinear control equation set;
sixthly, performing accurate iterative solution of the nonlinear control equation set;
and seventhly, realizing accurate searching of the homonymy points by adopting a pyramid and least square matching method.
Further, in the first step, the measuring the length of the line segment in the object measurement region includes:
measuring the length of not less than 6 line segments which are not on the same plane in an object space observation area; and the texture around the end points of the line segments is clear and can be extracted as characteristic points.
Further, in step two, the acquiring of the left and right image coordinates of the end points of the image acquisition line segment lists part of control equations, including:
collecting images of a measurement area, displaying the measurement images by using a malab image command, manually identifying coordinates of each end point of a line segment in left and right images, and accurately obtaining coordinates of the same-name point of the end point of the line segment in the right image by using a pyramid image matching method and a least square matching method.
The coplanarity equation and the distance equation are part of a parameter control equation.
Further, in step three, the uniformly generating 10 × 10 feature points and determining the homonymous points of the feature points include:
averagely taking 3 multiplied by 3 pixels as one pixel to generate a 3-layer pyramid image which is sequentially called as a first layer image, a second layer image and a third layer image from bottom to top; uniformly dividing the left image into 10 multiplied by 10 areas, and extracting a characteristic point in each area; and extracting the characteristic points by utilizing a Moravec operator, and matching corresponding right image homonym points according to a seven homonym point matching method in the step.
Further, in the fourth step, the establishing of the nonlinear control equation set calibrated by the internal orientation element, the relative orientation parameter and the lens distortion coefficient includes:
the main optical axis of the left camera is taken as the z axis, the x axis and the y axis are respectively parallel to the row direction and the column direction of the CCD to establish a coordinate system o-xyz, which is called as a left camera coordinate system hereinafter, and a right camera coordinate system o '-x' y 'z' is established in the same way. One point A (x) on the object to be measuredA,yA,zA) With a picture point a (x) on each of the left and right camerasa,ya,-f)、a'(x'a',y'a'-f '), then the straight lines oa, o' a 'and oo' are coplanar, i.e.:
on the object to be measuredTwo points A (x)A,yA,zA)、B(xB,yB,zB) The distance between is l, then:
wherein, the equations (1) and (2) are control equations for calibrating the internal orientation elements, the relative orientation parameters and the lens distortion coefficients.
Further, in step five, the determining an initial value of the iterative solution of the nonlinear control equation system includes:
the system of equations (1) and (2) is a non-linear system of equations containing the left camera internal orientation element x0、y0F and right camera inner orientation element x0'、y0', f', first order radial distortion coefficient k of left camera1And the radial distortion coefficient k of the right camera1' and relative orientation parameters
ω、
ω ', κ' and a baseline length D. The distortion coefficient here satisfies the distortion equation that only 1 st order radial distortion is considered.
Wherein the content of the first and second substances,
a pair of homonymous points can be listed as an equation (1), and a distance between objects can be listed as an equation (2), and when the total number of equations is more than 14, the equation is solved by using a method of attaching adjustment of parameters. Dimensionless transformations are made for the convergence of the equations:
wherein f is0、f0' is the focal length of the camera lens, thetax、θy、θx'、θy' is a dimensionless quantity, and the physical meaning of the dimensionless quantity is the included angle between the components of the CCD center vector in the directions of the x-axis and the y-axis and the z-axis, and is a small quantity.
The selection of the initial value is the most important precondition for the convergence of the nonlinear equation system, and the initial value is selected from theta according to the following methodx、θy、θx'、θyThe initial value of f and f 'is zero, the focal length marked by the lens is taken as the initial value of f and f', and the length D of the base line measured by a meter ruler is taken as the initial value of f and f; and determining an initial value of the relative orientation parameter by adopting a relative orientation direct solution method. Directly solving according to the relative orientation, the control equation is:
wherein the content of the first and second substances,
therefore, the equation coefficients can be obtained only by 8 or more pairs of homonymous points
Relative orientation parameter and
the relationship is as follows:
ω'＝arcsin(-b3) (7)
βy、βzis determined by the following two equations.
Wherein the content of the first and second substances,
the relative orientation parameters are obtained as initial values using equations (7) to (11).
Uniformly dividing the left image into 10 multiplied by 10 areas, determining a characteristic point in each area, and finding out the homonymous point according to the method in the step (4), thereby obtaining 100 control equations with the type of the formula (1); secondly, not less than 6 equations with the type of the formula (2) are obtained through measurement; thereby constituting a control group. The system of equations uses the coordinates of the same-name point pairs as observed quantities, other 13 parameters except the base length D as adjustment parameters, and the adjustment values of the 13 parameters are obtained by using the determined parameter values as initial values and adopting a conditional adjustment method with parameters. And taking the adjustment value of the 13 parameters and the initial value of the base length D as the initial value of the iteration of the nonlinear equation set.
Further, in step six, the performing of the accurate iterative solution of the nonlinear control equation system includes:
the iterative process is a process of gradually removing homonymous point pairs with larger errors, reserving homonymous point pairs with high matching precision and gradually approaching parameters to true values, and the process is another core of the invention.
Firstly, expanding characteristic points, namely expanding the characteristic points to 30 multiplied by 30 on the basis of 10 multiplied by 10 characteristic points used by the initial value;
secondly, calculating the difference between the y coordinate of the same-name point of the right image and the epipolar line y coordinate corresponding to the x coordinate of the same-name point by using the initial value;
thirdly, eliminating homonymous point pairs with deviation larger than 0.15, taking the coordinates of the remaining homonymous point pairs as observed quantity, taking 14 parameters as adjustment parameters, and calculating the adjustment value of the 14 parameters by adopting a known initial value and a conditional adjustment method with parameters;
and fourthly, calculating the difference between the y coordinate of the same-name point of the right image and the epipolar line y coordinate corresponding to the x coordinate of the same-name point by using the result of the third step, eliminating the same-name point pairs with the deviation larger than 0.12, and repeating the third step to calculate more accurate 14 parameter values. And repeating the steps until all the same-name point pairs with the deviation larger than 0.1 pixel are removed, and obtaining the final 14 parameter values.
Further, in the seventh step, the accurate search of the homonymy point is realized by using a pyramid + least square matching method, which includes:
generating 3 layers of pyramid images by generating 3 multiplied by 3 pixels which are averagely one pixel, sequentially calling the images as a first layer image, a second layer image and a third layer image from bottom to top, and determining the same-name points on the images of the third layer, the second layer and the first layer in sequence by adopting a discrimination method with the maximum correlation coefficient.
The least square image matching method is an accurate image matching method, and if geometric distortion and radiation distortion are considered, the conjugate point should satisfy the surrounding gray function:
wherein h is0 h1Representing a radiation distortion parameter, a0 a1 a2 b0 b1 b2Representing the geometric distortion parameter.
In addition, the formula (12) is taken as an observation equation, an indirect adjustment method is adopted, and the radiation parameters and the geometric parameters can be obtained by utilizing a correlation coefficient maximum discrimination method, so that the homonymous point of one image point is accurately determined; the maximum correlation coefficient judging method is that when the correlation coefficient after iteration is smaller than the correlation coefficient after the last iteration, the iteration is stopped.
It is a further object of the invention to provide a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of: selecting a small number of characteristic points, sequentially and directly solving the characteristic points to the solution of a 13-parameter control equation set in a relative orientation manner, and determining the initial value of the control equation set by the parameters from less to more; and expanding the number of the characteristic points, gradually eliminating the characteristic point pairs with lower matching quality in an iterative mode in sequence, gradually approaching the true value of the parameter to be solved, and finally obtaining the accurate internal orientation element, distortion coefficient and relative orientation parameter value.
Another object of the present invention is to provide a new stereographic internal orientation, relative orientation and distortion coefficient calibration system applying the intelligent stereographic internal orientation, relative orientation and distortion coefficient calibration method, the new stereographic internal orientation, relative orientation and distortion coefficient calibration system comprising:
the line length measuring module is used for measuring the line length in the object space measuring region;
the image coordinate acquisition module is used for acquiring left and right image coordinates of end points of the image acquisition line segment and listing a part of control equations;
the homonymy point determining module is used for uniformly generating 10 multiplied by 10 feature points and determining homonymy points of the feature points;
the control equation set establishing module is used for establishing a nonlinear control equation set calibrated by the internal orientation element, the relative orientation parameter and the lens distortion coefficient;
an initial value determination module for determining an initial value of an iterative solution of the nonlinear control equation set;
the precise iterative solution module is used for performing precise iterative solution on the nonlinear control equation set;
and the homonym matching module is used for realizing the accurate searching of the homonym by adopting a pyramid and least square matching method.
By combining all the technical schemes, the invention has the advantages and positive effects that: the method for calibrating the internal direction, the relative orientation and the distortion coefficient of the intelligent stereo photography, provided by the invention, is simple and practical, and can calibrate the internal direction elements of the stereo camera by only knowing the distance of at least 6 object line segments, wherein the relative orientation parameters and the lens distortion coefficient are 14 parameters. The 14 parameters are the left camera inner orientation element x0、y0F and right camera inner orientation element x0'、y0', f', first order radial distortion coefficient k of left camera1And the radial distortion coefficient k of the right camera1' and relative orientation parameters
ω、
ω ', κ' and baseline length.
The invention has simple and practical calibration, and is suitable for short-distance small-area measurement and long-distance large-area measurement; the calibration method can directly calibrate according to the space point distance of the measured object, and the length of the base line is output during calibration, thereby avoiding the uncertainty of base line measurement and providing a new calibration selection for photogrammeters.
The method of the invention is simple in calibration, is suitable for both short-distance small-area measurement and long-distance large-area measurement, and is suitable for firstly calibrating the internal orientation elements and the distortion coefficients indoors and then carrying out field measurement; the method can also be used for directly carrying out on-site calibration according to the measured object, and the length of the base line is directly output during calibration, so that the length of the base line does not need to be measured manually. The invention creatively provides a resolving method of the nonlinear equation set, and ensures the convergence of the equation and the precision of the calibration parameters.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of an intelligent stereographic inner orientation, relative orientation, and distortion coefficient calibration method according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of an intelligent stereo photography internal orientation, relative orientation and distortion coefficient calibration method provided by the embodiment of the invention.
FIG. 3 is a block diagram of a new system for calibrating the azimuth, relative orientation and distortion coefficients in stereography according to an embodiment of the present invention;
in the figure: 1. a segment length measuring module; 2. an image coordinate acquisition module; 3. a homonymy point determination module; 4. a control equation set establishing module; 5. an initial value determining module; 6. a precise iterative solution module; 7. and a homonymy point matching module.
Fig. 4 is a schematic view of a geometric model of a stereographic measurement provided by an embodiment of the present invention.
Fig. 5 is a schematic diagram of distribution of differences between the homonymous points of the homonymous points and the y coordinates of the corresponding epipolar lines obtained by matching according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides an intelligent stereo photography internal direction, relative orientation and distortion coefficient calibration method, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the method for calibrating the internal orientation, relative orientation and distortion coefficient in the intelligent stereo photography provided by the embodiment of the present invention includes the following steps:
s101, measuring the length of a line segment in an object measurement area;
s102, collecting left and right image coordinates of an image acquisition line segment end point, and listing a part of control equations;
s103, uniformly generating 10 multiplied by 10 feature points, and determining homonymous points of the feature points;
s104, establishing a nonlinear control equation set calibrated by an internal orientation element, a relative orientation parameter and a lens distortion coefficient;
s105, determining an initial value of an iterative solution of the nonlinear control equation set;
s106, performing accurate iterative solution of the nonlinear control equation set;
and S107, realizing accurate searching of the homonymy points by adopting a pyramid and least square matching method.
A schematic diagram of an intelligent stereo photography internal direction, relative orientation and distortion coefficient calibration method provided by the embodiment of the invention is shown in fig. 2.
As shown in fig. 3, the new system for calibrating the azimuth, relative orientation and distortion coefficient in stereography provided by the embodiment of the present invention includes:
the line length measuring module 1 is used for measuring the line length in the object measurement area;
the image coordinate acquisition module 2 is used for acquiring left and right image coordinates of end points of the image acquisition line segment and listing a part of control equations;
the homonymy point determining module 3 is used for uniformly generating 10 multiplied by 10 feature points and determining homonymy points of the feature points;
the control equation set establishing module 4 is used for establishing a nonlinear control equation set calibrated by an internal orientation element, a relative orientation parameter and a lens distortion coefficient;
an initial value determining module 5, configured to determine an initial value of an iterative solution of the nonlinear control equation set;
the precise iterative solution module 6 is used for performing precise iterative solution on the nonlinear control equation set;
and the homonym matching module 7 is used for realizing the accurate searching of the homonym by adopting a pyramid and least square matching method.
The technical solution of the present invention is further described with reference to the following examples.
Example 1
The invention discloses a novel calibration method for internal orientation elements, distortion coefficients and relative orientation parameters of stereography. The method uses a coplanar equation and the distance and the orientation of a measuring area line segment to form a control equation of parameters to be solved, and only a conditional adjustment method with the parameters is used for solving. The determination of the initial value and the iterative algorithm of the control equation system are the technical core of the invention. Firstly, selecting a small number of characteristic points, sequentially and directly solving the characteristic points through relative orientation to the solution of a 13-parameter control equation set, and determining the initial value of the control equation set by one step from less to more parameters; and then, the number of the characteristic points is enlarged, the characteristic point pairs with lower matching quality are gradually eliminated in an iterative mode in sequence, so that the parameters to be solved gradually approach to the true value, and finally, the accurate internal orientation elements, distortion coefficients and relative orientation parameter values are obtained. The invention has the advantages that the calibration is simple and practical, and the method is suitable for short-distance small-area measurement and long-distance large-area measurement; the calibration method can directly calibrate according to the space point distance of the measured object, and the length of the base line is output during calibration, thereby avoiding the uncertainty of base line measurement and providing a new calibration selection for photogrammeters.
The technical scheme adopted by the invention is as follows:
(1) and establishing a control equation set calibrated by the internal orientation element, the relative orientation parameter and the lens distortion coefficient.
As shown in fig. 4, a coordinate system o-xyz, hereinafter referred to as a left camera coordinate system, is established with a left camera principal optical axis as a z-axis, and an x-axis and a y-axis parallel to a row direction and a column direction of the CCD, respectively, and a right camera coordinate system o '-x' y 'z' is established similarly. One point A (x) on the object to be measuredA,yA,zA) With a picture point a (x) on each of the left and right camerasa,ya,-f)、a'(x'a',y'a'-f '), then the straight lines oa, o' a 'and oo' are coplanar, i.e.:
setting two points A (x) on the measured objectA,yA,zA)、B(xB,yB,zB) The distance between is l, then:
the equations (1) and (2) are control equations for calibrating the internal orientation elements, the relative orientation parameters and the lens distortion coefficients.
(2) Initial values of an iterative solution of a system of nonlinear control equations
The initial value-dependent quality of the iterative solution of the multi-parameter nonlinear equation set is a very challenging subject, which is one of the main innovations of the present invention.
The system of equations (1) and (2) is a non-linear system of equations containing the left camera internal orientation element x0、y0F and right camera inner orientation element x0'、y0', f', first order radial distortion coefficient k of left camera1And the radial distortion coefficient k of the right camera1' and relative orientation parameters
ω、
ω ', κ' and a baseline length D. The distortion coefficient here satisfies the distortion equation that only 1 st order radial distortion is considered.
Wherein the content of the first and second substances,
a pair of homonymous points can be listed as an equation (1), and a distance between objects can be listed as an equation (2), and when the total number of equations is more than 14, the equation is solved by using a method of attaching adjustment of parameters. Dimensionless transformations are made for the convergence of the equations:
wherein f is0、f0' is the focal length of the camera lens, thetax、θy、θx'、θy' is a dimensionless quantity, and the physical meaning of the dimensionless quantity is the included angle between the components of the CCD center vector in the directions of the x-axis and the y-axis and the z-axis, and is a small quantity.
The selection of the initial value is the most important precondition for the convergence of the nonlinear equation system. The initial value of the invention selects theta according to the following methodx、θy、θx'、θyThe initial value of f and f 'is zero, the focal length marked by the lens is taken as the initial value of f and f', and the length D of the base line measured by a meter ruler is taken as the initial value of f and f; and determining an initial value of the relative orientation parameter by adopting a relative orientation direct solution method. The direct solution according to the relative orientation has the following control equation:
wherein the content of the first and second substances,
therefore, the equation coefficients can be obtained only by 8 or more pairs of homonymous points
Relative orientation parameter and
the relationship is as follows:
ω'＝arcsin(-b3) (6)
βy、βzis determined by the following two equations.
Wherein the content of the first and second substances,
the relative orientation parameters are obtained from equations (6) to (10) as initial values.
Since the nonlinear equation set contains 14 parameters and is very sensitive to the initial value, the initial value determined by the method may cause the iterative process not to converge. In order to improve the quality of an initial value, a left image is uniformly divided into 10 multiplied by 10 areas, a characteristic point is determined in each area, and a homonymy point is found out according to the method in the step (4), so that 100 control equations with the type of the formula (1) are obtained; secondly, not less than 6 equations with the type of the formula (2) are obtained through measurement; thereby constituting a control group. The system of equations uses the coordinates of the same-name point pairs as observed quantities, other 13 parameters except the base length D as adjustment parameters, and uses the determined parameter values as initial values to calculate the adjustment values of the 13 parameters by adopting a conditional adjustment method with parameters. And taking the adjustment value of the 13 parameters and the initial value of the base length D as the initial value of the iteration of the nonlinear equation set.
(3) Precise iterative solution of nonlinear control equations
The iterative process is a process of gradually removing homonymous point pairs with larger errors, reserving homonymous point pairs with high matching precision and gradually approaching parameters to true values, and the process is another core of the invention.
First, feature points are expanded to 30 × 30 feature points based on 10 × 10 feature points used for the initial value, in order to further increase the accuracy.
And secondly, calculating the difference between the y coordinate of the same-name point of the right image and the epipolar line y coordinate corresponding to the x coordinate of the same-name point by using the initial value. Fig. 5 is a case of the present invention, and the following case is taken as an example to illustrate the solving process for better explaining the present invention. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 5, theoretically, the difference between the y coordinate of the same-name point and the y coordinate of the epipolar line corresponding to the x coordinate of the same-name point is zero, and therefore, the larger the difference is, the larger the matching error is. As the precision of the matching mode adopted by people is 0.1 pixel, points with difference larger than 0.1 pixel are considered as points with larger error, and the points are removed step by step, so that the parameters gradually approach to the true value.
And thirdly, removing homonymous point pairs with deviation larger than 0.15, taking the coordinates of the remaining homonymous point pairs as observed quantity, taking 14 parameters as adjustment parameters, and calculating the adjustment value of the 14 parameters by adopting a known initial value and a conditional adjustment method with the parameters.
And fourthly, calculating the difference between the y coordinate of the same-name point of the right image and the epipolar line y coordinate corresponding to the x coordinate of the same-name point by using the result of the third step, eliminating the same-name point pairs with the deviation larger than 0.12, and repeating the third step to calculate more accurate 14 parameter values. And repeating the steps until all the same-name point pairs with the deviation larger than 0.1 pixel are removed, and obtaining the final 14 parameter values.
(4) Homonym point matching method
The invention adopts a pyramid and least square matching method to realize the accurate searching of the homonymy point. Generating 3 layers of pyramid images by generating 3 multiplied by 3 pixels which are averagely one pixel, sequentially calling the images as a first layer image, a second layer image and a third layer image from bottom to top, and determining the same-name points on the images of the third layer, the second layer and the first layer in sequence by adopting a discrimination method with the maximum correlation coefficient.
The least square image matching method is an accurate image matching method, and if geometric distortion and radiation distortion are considered, the conjugate point should satisfy the surrounding gray function:
wherein h is0 h1Representing a radiation distortion parameter, a0 a1 a2 b0 b1 b2Representing the geometric distortion parameter.
In addition, the formula (11) is taken as an observation equation, an indirect adjustment method is adopted, and the radiation parameter and the geometric parameter can be obtained by utilizing a correlation coefficient maximum discrimination method, so that the homonymous point of one image point can be accurately determined. The maximum correlation coefficient discrimination method means that iteration is stopped when the correlation coefficient after iteration is smaller than the correlation coefficient after the last iteration.
Example 2
FIG. 2 is a schematic flow diagram of the process of the present invention, which is described in detail below:
the first step is as follows: and measuring the length of the line segment in the object measurement region.
The length of not less than 6 line segments is measured in an object observation area, the line segments cannot be on the same plane, the texture around the end points of the line segments is clear, and the line segments can be extracted as feature points.
The second step is that: and collecting the left and right image coordinates of the end points of the image acquisition line segment, and listing partial control equations.
Collecting images of a measurement area, displaying the measurement images by using a malab image command, manually identifying coordinates of each end point of a line segment in left and right images, and accurately obtaining coordinates of the same-name point of the end point of the line segment in the right image by using a pyramid image matching method and a least square matching method.
Each homonym point pair is listed as a coplanar equation according to the formula (1) in the technical scheme, and each line segment is listed as a distance equation according to the formula (2), and the homonym point pairs and the distance equations are part of a parameter control equation.
The third step: uniformly generating 10 × 10 characteristic points, and determining homologous points thereof, which are called characteristic point pairs.
The 3-layer pyramid image is generated by averaging 3 × 3 pixels into one pixel, and is sequentially called as a first layer image, a second layer image and a third layer image from bottom to top. The left image is evenly divided into 10 × 10 regions, and a feature point is extracted in each region. Characteristic points can be extracted by using a Moravec operator, and corresponding right image homonymous points are matched according to a homonymous point matching method in the technical scheme (4).
The fourth step: a system of control equations is determined.
The homonymous point pair of each characteristic point is listed as a coplanar equation according to the formula (1) in the technical scheme, and the 100 equations and the equation listed in the second step form a control equation set with 14 parameters such as internal orientation elements, distortion coefficients and relative orientation parameters. And (3) taking the coordinates of the same-name point pairs as observed quantities and 14 parameters as adjustment parameters, linearizing the equation set, and expressing the equation set into a control equation set in a conditional adjustment form with the parameters.
The fifth step: and 14, determining initial values of the parameters.
According to the technical scheme (2), initial values of the parameters are determined 14.
And a sixth step: the exact solution of the parameters is iteratively determined 14.
According to the solution (3), the exact solution of the parameters is determined 14 by an iterative method.
The technical effects of the present invention will be described in detail with reference to experiments.
In order to verify the technology, a technology verification experiment is carried out on the first ocean research institute of the department of natural resources in 2018, 11 and 26. Two German CB200MG-CM industrial cameras are adopted in the experiment, and an EF35 f/1.4LII USM type 35mm lens is matched, wherein the pixel size of the camera is 6.4 mu m, and the resolution is 5120 multiplied by 3840.
Table 1 shows the 7 segment lengths measured according to step 1 and the pixel coordinates of the segment end points obtained according to step 2. I, J, indicating the number of rows and columns of line segment ends in the left image; i 'and J' represent the number of rows and columns, respectively, of line segment ends in the right image.
TABLE 1 coordinates of end point image of line segment (unit: unit pixel) and length of line segment (unit: mm)
Table 2 shows the initial values of the 14 parameters obtained according to step 5 and the accurate values of the 14 parameters obtained according to step 6. Wherein, the initial value 1 is a direct solution result of adopting 10 multiplied by 10 characteristic point pairs in relative orientation, the focal length is the focal length of the fixed-focus lens, the base length is the metric ruler measurement result, and other parameters are zero; the initial value 2 is obtained by utilizing 10 multiplied by 10 characteristic point pairs and the initial value 1, the length of a base line is used for obtaining a metric ruler measurement result, and other 13 parameters are used for obtaining a nonlinear equation system solution result; the adjustment value represents the 14 parameter accurate value obtained according to step 6.
Table 214 initial values and adjustment values of parameters
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. An intelligent stereo photography internal direction, relative orientation and distortion coefficient calibration method is characterized in that the intelligent stereo photography internal direction, relative orientation and distortion coefficient calibration method comprises the following steps: selecting a small number of characteristic points, sequentially and directly solving the characteristic points to the solution of a 13-parameter control equation set in a relative orientation manner, and determining the initial value of the control equation set by the parameters from less to more; and expanding the number of the characteristic points, gradually eliminating the characteristic point pairs with lower matching quality in an iterative mode in sequence, gradually approaching the true value of the parameter to be solved, and finally obtaining the accurate internal orientation element, distortion coefficient and relative orientation parameter value.
2. The intelligent stereographic internal orientation, relative orientation and distortion coefficient calibration method of claim 1, wherein said intelligent stereographic internal orientation, relative orientation and distortion coefficient calibration method comprises the steps of:
measuring the length of a line segment in an object measurement area;
acquiring left and right image coordinates of the end points of the acquired line segments of the image, and listing partial control equations;
uniformly generating 10 multiplied by 10 feature points, and determining homonymous points of the feature points;
establishing a nonlinear control equation set for calibrating the internal orientation element, the relative orientation parameter and the lens distortion coefficient;
step five, determining an initial value of an iterative solution of the nonlinear control equation set;
sixthly, performing accurate iterative solution of the nonlinear control equation set in the step six;
and seventhly, realizing accurate searching of the homonymy points by adopting a pyramid and least square matching method.
3. The method for calibrating azimuth, relative orientation and distortion coefficient in intelligent stereography according to claim 2, wherein in step one, the measuring the length of the line segment in the object space measuring region comprises: measuring the length of not less than 6 line segments which are not on the same plane in an object space observation area; and the texture around the end points of the line segments is clear and can be extracted as characteristic points.
4. The method for calibrating the azimuth, the relative orientation and the distortion coefficient in the intelligent stereography according to claim 2, wherein in the second step, the left and right image coordinates of the end points of the acquired image acquisition line segment list part of control equations, and the method comprises the following steps: collecting images of a measurement area, displaying the measurement images by using a malab image command, manually identifying coordinates of each end point of a line segment in left and right images, and accurately obtaining coordinates of homonymous points of the end points of the line segment in the right image by using a pyramid image matching method and a least square matching method;
the coplanarity equation and the distance equation are part of a parameter control equation.
5. The method for calibrating azimuth, relative orientation and distortion coefficient in intelligent stereography according to claim 2, wherein in step three, said uniformly generating a few, such as 10 x 10, feature points, determining the homonymous points of said feature points comprises: averagely taking 3 x 3 pixels as one pixel to generate a 3-layer pyramid image which is sequentially called as a first image, a second image and a third image from bottom to top; uniformly dividing the left image into 10 regions by 10, and extracting a feature point in each region; and extracting characteristic points by utilizing a Moravec operator, and matching corresponding right image homonymy points according to a pyramid and least square matching method.
6. The method for calibrating the internal orientation, relative orientation and distortion coefficient of intelligent stereography according to claim 2, wherein in step four, said establishing a nonlinear control equation system for calibrating the internal orientation element, the relative orientation parameter and the lens distortion coefficient comprises:
establishing a coordinate system o-xyz, hereinafter referred to as a left camera coordinate system, by taking a main optical axis of the left camera as a z axis, and respectively parallel to the row direction and the column direction of the CCD, and establishing a right camera coordinate system o '-x' y 'z' in the same way; one point A (x) on the object to be measuredA,yA,zA) With a picture point a (x) on each of the left and right camerasa,ya,-f)、a'(x'a',y'a'-f '), then the straight lines oa, o' a 'and oo' are coplanar, i.e.:
setting two points A (x) on the measured objectA,yA,zA)、B(xB,yB,zB) The distance between is l, then:
wherein the equation
Namely a control equation for calibrating the internal orientation element, the relative orientation parameter and the lens distortion coefficient.
7. The method for intelligent stereographic internal orientation, relative orientation, and distortion coefficient calibration according to claim 2, wherein in step five, said determining initial values for the iterative solution of the system of nonlinear control equations comprises:
equation of equation
The formed equation system is a nonlinear equation system and contains a left camera internal orientation element x0、y0F and right camera inner orientation element x0'、y0', f', first order radial distortion coefficient k of left camera1And the radial distortion coefficient k of the right camera1' and relative orientation parameters
ω、
ω ', κ' and baseline length D; the distortion coefficient here satisfies the distortion equation that only 1 st order radial distortion is considered;
wherein the content of the first and second substances,
a pair of homonymous points may list an equation
An equation can be listed for a distance of an object space
When the total number of the equations is more than 14, solving by adopting a method of adjustment with parameters; dimensionless transformations are made for the convergence of the equations:
wherein f is0、f0' is the focal length of the camera lens, thetax、θy、θx'、θyThe' is dimensionless quantity, the physical meaning is the included angle between the components of the CCD center vector in the directions of the x axis and the y axis and the z axis, and the physical meaning is small quantity;
the selection of the initial value is the most important precondition for the convergence of the nonlinear equation system, and the initial value is selected from theta according to the following methodx、θy、θx'、θyThe initial value of f and f 'is zero, the focal length marked by the lens is taken as the initial value of f and f', and the length D of the base line measured by a meter ruler is taken as the initial value of f and f; determining an initial value of a relative orientation parameter by adopting a relative orientation direct solution method; directly solving according to the relative orientation, the control equation is:
wherein the content of the first and second substances,
therefore, the equation coefficients can be obtained only by 8 or more pairs of homonymous points
Relative orientation parameter and
the relationship is as follows:
ω'＝arcsin(-b3)；
βy、βzis determined by the following two formulas;
wherein the content of the first and second substances,
calculating relative orientation parameters as initial values;
uniformly dividing the left image into 10 multiplied by 10 areas, determining a characteristic point in each area, and finding out the homonymy point of the characteristic point, thereby obtaining 100 control equations; secondly, measuring the length of the line segment to obtain not less than 6 control equations; thereby forming a control equation set; the coordinate of the homonymous point pair is used as an observed quantity, other 13 parameters except the base length D are used as adjustment parameters, and the adjustment values of the 13 parameters are obtained by using the determined parameter values as initial values and adopting a conditional adjustment method with the parameters; and taking the adjustment value of the 13 parameters and the initial value of the base length D as the initial value of the iteration of the nonlinear equation set.
8. The method for calibrating the azimuth, the relative orientation and the distortion coefficient in the intelligent stereography according to claim 2, wherein in the sixth step, the accurate iterative solution of the nonlinear control equation system is performed, and the method comprises the following steps:
firstly, expanding characteristic points, namely expanding the characteristic points to 30 multiplied by 30 on the basis of 10 multiplied by 10 characteristic points used by the initial value;
secondly, calculating the difference between the y coordinate of the same-name point of the right image and the epipolar line y coordinate corresponding to the x coordinate of the same-name point by using the initial value;
thirdly, eliminating homonymous point pairs with deviation larger than 0.15, taking the coordinates of the remaining homonymous point pairs as observed quantity, taking 14 parameters as adjustment parameters, and calculating the adjustment value of the 14 parameters by adopting a known initial value and a conditional adjustment method with parameters;
fourthly, calculating the difference between the y coordinate of the same-name point of the right image and the y coordinate of the epipolar line corresponding to the x coordinate of the same-name point by using the result of the third step, eliminating the same-name point pairs with the deviation larger than 0.12, and repeating the third step to calculate more accurate 14 parameter values; analogizing in turn until all the same-name point pairs with the deviation larger than 0.1 pixel are removed, and obtaining a final 14 parameter value;
in the seventh step, the accurate search of the homonymy point is realized by adopting a pyramid and least square matching method, which comprises the following steps: generating a 3-layer pyramid image by generating 3 multiplied by 3 pixels which are averagely one pixel, sequentially calling the image from bottom to top as a first layer image, a second layer image and a third layer image, and determining homonymy points on the third layer image, the second layer image and the first layer image in sequence by adopting a discrimination method with the maximum correlation coefficient;
the least square image matching method is an accurate image matching method, and if geometric distortion and radiation distortion are considered, the conjugate point should satisfy the surrounding gray function:
wherein h is0 h1Representing a radiation distortion parameter, a0 a1 a2 b0 b1 b2Representing a geometric distortion parameter;
in addition, the above formula is taken as an observation equation, an indirect adjustment method is adopted, and the radiation parameter and the geometric parameter can be solved by using a correlation coefficient maximum discrimination method, so that the homonymous point of one image point is accurately determined; the maximum correlation coefficient judging method is that when the correlation coefficient after iteration is smaller than the correlation coefficient after the last iteration, the iteration is stopped.
9. A computer device, characterized in that the computer device comprises a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to carry out the steps of: selecting a small number of characteristic points, sequentially and directly solving the characteristic points to the solution of a 13-parameter control equation set in a relative orientation manner, and determining the initial value of the control equation set by the parameters from less to more; and expanding the number of the characteristic points, gradually eliminating the characteristic point pairs with lower matching quality in an iterative mode in sequence, gradually approaching the true value of the parameter to be solved, and finally obtaining the accurate internal orientation element, distortion coefficient and relative orientation parameter value.
10. A new stereographic internal orientation, relative orientation and distortion coefficient calibration system applying the intelligent stereographic internal orientation, relative orientation and distortion coefficient calibration method as claimed in any one of claims 1-8, said new stereographic internal orientation, relative orientation and distortion coefficient calibration system comprising:
the line length measuring module is used for measuring the line length in the object space measuring region;
the image coordinate acquisition module is used for acquiring left and right image coordinates of end points of the image acquisition line segment and listing a part of control equations;
the homonymous point determining module is used for uniformly generating 10 multiplied by 10 characteristic points and determining homonymous points of the characteristic points, namely characteristic point pairs;
the control equation set establishing module is used for establishing a nonlinear control equation set calibrated by the internal orientation element, the relative orientation parameter and the lens distortion coefficient;
an initial value determination module for determining an initial value of an iterative solution of the nonlinear control equation set;
the precise iterative solution module is used for performing precise iterative solution on the nonlinear control equation set;
and the homonym matching module is used for realizing the accurate searching of the homonym by adopting a pyramid and least square matching method.
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