CN118097039A - Surface structured light three-dimensional point cloud reconstruction method and system based on discrete projection light - Google Patents
Surface structured light three-dimensional point cloud reconstruction method and system based on discrete projection light Download PDFInfo
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Abstract
The invention discloses a surface structured light three-dimensional point cloud reconstruction method based on discretized projection light, which comprises the following steps: projecting sinusoidal stripe patterns in two directions to N calibration plates with known different height positions through a projector, calibrating a camera according to images captured by the camera, calculating quadrature absolute phase information of N groups of images, and storing the quadrature absolute phase information; discretizing the stripe structure light of the projector and calculating a phase distribution diagram corresponding to the group of discretized light rays; performing straight line fitting to obtain a fitting projection light parameter equation of each discrete light and creating a lookup table; and placing the object to be measured on a reference surface, projecting and calculating phase information of an image of the object to be measured, looking up a table to find a parameter equation of fitting projection light corresponding to an image point, determining three-dimensional coordinates of object points in different directions of fitting projection light, and finally generating a three-dimensional point cloud of the object to be measured. The invention improves the speed and the precision of three-dimensional reconstruction.
Description
Technical Field
The invention relates to the technical field of grating projection three-dimensional detection, in particular to a surface structured light three-dimensional point cloud reconstruction method and system based on discretized projection light rays.
Background
In recent decades, with the continuous development of key fields such as micro optics, microelectronics and integration technology, industrial product designs gradually move to high precision and miniaturization. This trend has not only significantly affected many fields such as circuit boards, micromachines, semiconductor devices, and precision instruments, but has also prompted our more intensive research into automated geometric inspection techniques for high-density micro-products. In this context, the emerging three-dimensional point cloud reconstruction technology based on surface structured light presents great potential, and can provide a reliable solution for applications in complex scenes, meeting the high standard requirements of modern manufacturing industry for accuracy and efficiency.
In the conventional reconstruction method based on the plane structured light three-dimensional reconstruction technology of grating projection, there are two main classical categories: phase-height mapping and stereo vision. However, the currently employed phase-height mapping approximation polynomial method does not make strict deductions based on the imaging model, which results in that the degree of the polynomial cannot be reasonably determined. Since the polynomial degree is selected closely related to the lens distortion model, and the distortion characteristics of the lens are not sufficiently considered in this method, there is a limitation in accuracy of the method. Another stereoscopic model is effective in considering lens distortion. However, there is a non-negligible time cost to the process consumption of the homology search.
Disclosure of Invention
The invention mainly aims to provide a surface structured light three-dimensional point cloud reconstruction method and system based on discretized projection light, which can improve the speed and precision of three-dimensional reconstruction.
The technical scheme adopted by the invention is as follows:
The surface structured light three-dimensional point cloud reconstruction method based on the discretized projection light rays comprises the following steps:
S1, projecting sinusoidal stripe patterns in two directions to N calibration plates with known different height positions through a projector, calibrating a camera according to images captured by the camera, calculating quadrature absolute phase information of N groups of images, and storing the quadrature absolute phase information, wherein N is more than or equal to 10;
S2, discretizing stripe structure light of the projector according to quadrature absolute phase information of N groups of images to form a group of discretized light rays, and calculating a phase distribution diagram corresponding to the group of discretized light rays;
s3, performing straight line fitting on intersection points of the discrete light rays and different height planes according to N different height positions to obtain a fitting projection light ray parameter equation of each discrete light ray;
S4, creating a lookup table L according to a parameter equation of each fitting projection ray;
S5, placing the object to be measured on a reference surface, projecting sinusoidal fringe patterns in two directions on the object by using a projector, shooting images by using a camera, calculating phase information of the image of the object to be measured, searching image points with the same phase in a phase distribution diagram corresponding to the discretized light, finding a parameter equation of fitting projection light corresponding to the image points in a lookup table L, determining three-dimensional coordinates of the object points in different fitting projection light directions, and finally generating three-dimensional point cloud of the object to be measured.
In step S1, the N sets of quadrature absolute phase diagrams obtained by calculation are first distorted and then stored.
With the above technical solution, the specific method in step S2 is as follows:
Searching out the phase maximum value in the horizontal direction in N groups of quadrature absolute phase diagrams And minimum/>Vertical phase maximum/>And minimum/>Assuming that the projector resolution is row-col, the horizontal sampling interval isVertical sampling interval is/>Each light corresponds to a phase value, and a phase distribution diagram corresponding to the discretized light is obtained.
With the above technical solution, the specific method in step S3 is as follows:
retrieving image points in N sets of quadrature absolute phase maps that are in the same phase as in the discretized ray phase profile Image point/>, determined by a camera calibrated parameter matrixCorresponding back-projected ray/>Back projected ray/>Plane with the calibration plateIntersection to obtain the coordinates of each intersection point as/>，/>，…，/>; And performing straight line fitting on the plurality of intersection points.
With the above technical solution, the parameters of each ray in the lookup table L are stored in a structured manner, so that specific ray parameters can be directly retrieved through the image point index.
By adopting the technical scheme, the calibration plate is a round calibration plate.
According to the technical scheme, the calibration plate is placed and the height position of the calibration plate is adjusted through the Z-axis moving platform.
By adopting the technical scheme, the method further comprises the following steps:
S0, building a surface structured light three-dimensional point cloud reconstruction system based on discrete projection light, wherein the system comprises an industrial camera, a projector, a Z-axis moving platform and a calibration plate, and the calibration plate adjusts N different height positions through the Z-axis moving platform.
The invention also provides a surface structured light three-dimensional point cloud reconstruction system based on the discretized projection light, which comprises an industrial camera, a projector, a Z-axis moving platform, a computer and a calibration plate.
The invention has the beneficial effects that: the invention relates to a plane structured light three-dimensional point cloud reconstruction method based on discretized projection light, which comprises the steps of obtaining quadrature absolute phase information of N groups of images by adjusting N calibration plates with known different height positions, discretizing stripe structured light of a projector to form a group of discretized light, and calculating a phase distribution diagram corresponding to the group of discretized light; the space coordinates corresponding to the projection light rays are searched by fitting the parameter equation of the discrete light rays, so that the internal and external parameters of the projector do not need to be calibrated, the time consumption of searching the homologous points during calibrating the projector is avoided, the three-dimensional reconstruction speed and the three-dimensional reconstruction precision are improved, the requirement of high-precision object detection is met, and the detection of the defects of the precise object is realized.
Of course, it is not necessary for any one product to practice the invention to achieve all of the advantages set forth above at the same time.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for reconstructing a three-dimensional point cloud of surface structured light based on discretized projection light rays according to an embodiment of the present invention;
FIG. 2 is a discrete projected ray distribution diagram of an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating the intersection of discretized light rays with a plane in accordance with an embodiment of the present invention;
FIG. 4 is a diagram of a circuit board according to an embodiment of the present invention;
FIG. 5 is a three-dimensional point cloud image of a circuit board subjected to rendering according to an embodiment of the present invention;
FIG. 6 is a partially enlarged three-dimensional point cloud of static memory (SARM) in a circuit board according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
It should be noted that the illustrations provided in the embodiments of the invention are merely schematic illustrations of the basic concepts of the invention, and thus only the components related to the invention are shown in the drawings, rather than being drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of each component in actual implementation may be arbitrarily changed, and the layout of the components may be more complex.
In the present application, it should also be noted that, as terms such as "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", and the like are used, the indicated orientation or positional relationship is based on the orientation or positional relationship shown in the drawings, only for convenience of describing the present application and simplifying the description, and does not indicate or imply that the indicated apparatus or element must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first," "second," and the like, as used herein, are used for descriptive and distinguishing purposes only and are not to be construed as indicating or implying a relative importance.
As shown in fig. 1, the planar structured light three-dimensional point cloud reconstruction method based on discretized projection light in the embodiment of the invention mainly comprises the following steps:
S1, projecting sinusoidal stripe patterns in two directions to N calibration plates with known different height positions through a projector, calibrating a camera according to images captured by the camera, calculating quadrature absolute phase information of N groups of images, and storing the quadrature absolute phase information, wherein N is more than or equal to 10;
S2, discretizing stripe structure light of the projector according to quadrature absolute phase information of N groups of images to form a group of discretized light rays, and calculating a phase distribution diagram corresponding to the group of discretized light rays;
s3, performing straight line fitting on intersection points of the discrete light rays and different height planes according to N different height positions to obtain a fitting projection light ray parameter equation of each discrete light ray;
S4, creating a lookup table L according to a parameter equation of each fitting projection ray;
S5, placing the object to be measured on a reference surface, projecting sinusoidal fringe patterns in two directions on the object by using a projector, shooting images by using a camera, calculating phase information of the image of the object to be measured, searching image points with the same phase in a phase distribution diagram corresponding to the discretized light, finding a parameter equation of fitting projection light corresponding to the image points in a lookup table L, determining three-dimensional coordinates of the object points in different fitting projection light directions, and finally generating three-dimensional point cloud of the object to be measured.
The surface structured light three-dimensional point cloud reconstruction system based on the discretized projection light rays can be built in advance, and comprises an industrial camera, a projector, a Z-axis moving platform and a calibration plate, wherein the calibration plate adjusts N different height positions through the Z-axis moving platform. The Z-axis moving platform can move up and down and is mainly used for calibrating a camera, the camera can use large-scale star series MER2-1220-32U3C, and the resolution of a shot image is 4024 multiplied by 3036; the projector may be a DLP4500 manufactured by TI corporation of America, which has a resolution of 912×1140, and the object to be measured is a circuit board (as shown in FIG. 4).
In step S1, camera calibration may be performed by using a manner equipped with a Z-axis moving platform that can move up and down. The calibration plate is placed on the Z-axis moving platform, which can be precisely adjusted to N known different heights (typically N. Gtoreq.10) in the vertical direction. At each height position, a projector may be used to project two orthogonal sinusoidal fringe patterns on the calibration plate and calculate an orthogonal absolute phase map. In one embodiment of the invention, 10 sets of quadrature absolute phase maps are de-distorted and stored, each set corresponding to phase data of calibration plate positions of different heights.
The formula according to which the camera is calibrated is as follows:
Wherein, Representing homogeneous coordinates; /(I) T Is the position of an object point in the World Coordinate System (WCS); /(I) T For the position of an object point in the Camera Coordinate System (CCS), i.e./>Is a three-dimensional point of a camera coordinate system; r c is a rotation matrix; t c is a translation matrix; /(I)Is a scale factor; i is an identity matrix, 0 is a zero vector; /(I)Is the projected image point; /(I)Is an uncorrected image point; /(I)Wherein/>Is a radial distortion parameter,/>Is a tangential distortion parameter; the delta function represents a distortion correction function; /(I)Is a camera parameter matrix, m c is pixel coordinates.
As shown in fig. 2, in step S2, the fringe structure light of the projector is discretized, and the horizontal phase maximum value is searched out in the N sets of quadrature absolute phase diagramsAnd minimum/>Vertical phase maximum/>And minimum valueIf the projector resolution is 912×1140, the horizontal sampling interval is/>Vertical sampling interval is/>Each light corresponds to a phase value, and a phase distribution diagram corresponding to the discretized light is obtained.
As shown in FIG. 3, in step S3, 10 sets of quadrature absolute phase diagrams are obtained by adjusting the Z-axis moving platform to 10 different heights, and image points with the same phase as that in the discretized light phase distribution diagram are searched in the 10 sets of quadrature absolute phase diagramsThese image points/>, are determined by means of the parameter matrix calibrated by the camera in step S1Corresponding back-projected ray/>These back-projected rays/>With the plane/>, of the calibration plateIntersection to obtain the coordinates of each intersection point as/>，/>，…，/>. Let the object plane be denoted/>, in World Coordinate System (WCS)Expressed as/>, in the Camera Coordinate System (CCS). Based on a rigid transformation between two coordinate systems,/>The formula according to is:
the PCA algorithm (principal component analysis algorithm) is adopted for intersecting points ，/>，…，/>And (3) performing straight line fitting, wherein in the PCA algorithm, the straight line fitting comprises the following steps of:
first calculate the centroid of all intersection coordinates The formula according to is:
Constructing a covariance matrix C, wherein the covariance matrix C is based on the difference value between each point and the centroid according to the following formula:
Extracting a feature vector corresponding to the maximum feature value by performing feature decomposition on the covariance matrix C This represents the principal direction of the projected light. Since the expression of a straight line in three-dimensional space generally requires two variables, the parameterized form of the projected ray is further converted into a function about the Z-axis, as follows:
Wherein the slope is And/>Intercept/>And/>The formula is as follows:
After the single projection ray parameter equation is determined, all projection rays are repeatedly processed. For each ray, its direction in three-dimensional space can be determined by Principal Component Analysis (PCA) and the slope and intercept parameters corresponding thereto calculated. Specifically, the slope of each ray is calculated And/>Intercept/>And/>These parameters define the path of the ray in three dimensions.
In step S4, after obtaining the corresponding parameters of all projection light rays, they may be stored in a lookup table L. The parameters of each ray are stored in a structured manner so that specific ray parameters can be retrieved directly from the image point index. The look-up table L is based on the formula:
wherein/> For each ray of light, a corresponding phase value.
In step S5: and placing the object to be measured on a reference surface, projecting sinusoidal stripe patterns in two directions on the object through a projector, and shooting images by using a camera. The phase information in the camera image is obtained by a phase solution Bao Suanfa, and the image points with the same phase as the phase distribution map are searched by utilizing the phase distribution map corresponding to the discretized light，/>I.e. a two-dimensional coordinate point on the camera image plane, the phase value passing through this point/>Searching a parameter equation of corresponding light in a lookup table to determine three-dimensional coordinates of an object point in different projection light directions, wherein a formula for generating a three-dimensional coordinate point cloud basis is as follows:
In the embodiment of the invention, fig. 4 shows a physical photographed image of a circuit board, and fig. 5 shows a three-dimensional point cloud image of the circuit board after three-dimensional reconstruction. FIG. 6 is a partially enlarged three-dimensional point cloud of static memory (SARM) in a circuit board. The surface structured light three-dimensional point cloud reconstruction method and system based on the discretized projection light can clearly and accurately capture the structural details of the circuit board, and prove the effectiveness of the invention in the aspect of reconstructing the three-dimensional point cloud of the precise object.
The surface structured light three-dimensional point cloud reconstruction system based on the discretized projection light mainly comprises an industrial camera, a projector, a Z-axis moving platform, a computer and a calibration plate, and the surface structured light three-dimensional point cloud reconstruction method based on the discretized projection light model of the method embodiment is realized through the system and is not described in detail herein.
In summary, the surface structured light three-dimensional point cloud reconstruction method and system based on the discretized projection light can effectively generate circuit board point cloud data with accurate three-dimensional coordinates. The method avoids the time consumption of the homologous point search when calibrating the internal and external parameters of the projector. Through the discretization of projector light, each light corresponds to a specific phase value, the height of the Z-axis moving platform is adjusted, straight line fitting is carried out on the intersection points of the discrete light and the planes of the Z-axis moving platforms with different heights, and the parameter equation of the projection light is calibrated and fitted and stored in a lookup table. And (3) understanding phase information of the acquired image of the object to be detected, searching image points with the same phase as the phase of the projection light by combining the lookup table, determining three-dimensional coordinates of the object points on different projection light according to a parameter equation of the light, and finally generating three-dimensional point cloud of the object. Therefore, the invention improves the accuracy and efficiency of the detection of the precise object by precisely positioning the geometric position and the three-dimensional shape of the component, and provides powerful technical support for the quality control of the precise object. The method can effectively detect whether the components of the precise object have common defects such as dislocation, desoldering and the like by comparing with the detection standard.
It should be noted that each step/component described in the present application may be split into more steps/components, or two or more steps/components or part of operations of the steps/components may be combined into new steps/components, according to the implementation needs, to achieve the object of the present application.
The sequence numbers of the steps in the above embodiments do not mean the execution sequence, and the execution sequence of the processes should be determined according to the functions and internal logic, and should not limit the implementation process of the embodiments of the present application.
It will be understood that modifications and variations will be apparent to those skilled in the art from the foregoing description, and it is intended that all such modifications and variations be included within the scope of the following claims.
Claims (9)
1. The surface structured light three-dimensional point cloud reconstruction method based on the discretized projection light is characterized by comprising the following steps of:
S1, projecting sinusoidal stripe patterns in two directions to N calibration plates with known different height positions through a projector, calibrating a camera according to images captured by the camera, calculating quadrature absolute phase information of N groups of images, and storing the quadrature absolute phase information, wherein N is more than or equal to 10;
S2, discretizing stripe structure light of the projector according to quadrature absolute phase information of N groups of images to form a group of discretized light rays, and calculating a phase distribution diagram corresponding to the group of discretized light rays;
s3, performing straight line fitting on intersection points of the discrete light rays and different height planes according to N different height positions to obtain a fitting projection light ray parameter equation of each discrete light ray;
S4, creating a lookup table L according to a parameter equation of each fitting projection ray;
S5, placing the object to be measured on a reference surface, projecting sinusoidal fringe patterns in two directions on the object by using a projector, shooting images by using a camera, calculating phase information of the image of the object to be measured, searching image points with the same phase in a phase distribution diagram corresponding to the discretized light, finding a parameter equation of fitting projection light corresponding to the image points in a lookup table L, determining three-dimensional coordinates of the object points in different fitting projection light directions, and finally generating three-dimensional point cloud of the object to be measured.
2. The method for reconstructing the three-dimensional point cloud of the surface structured light based on the discretized projection light according to claim 1, wherein in the step S1, the N groups of the calculated orthogonal absolute phase maps are firstly distorted removed and then stored.
3. The method for reconstructing the three-dimensional point cloud of the surface structured light based on the discretized projection light rays according to claim 1, wherein the specific method in the step S2 is as follows:
Searching out the phase maximum value in the horizontal direction in N groups of quadrature absolute phase diagrams And minimum/>Vertical phase maximum/>And minimum/>Assuming that the projector resolution is row-col, the horizontal sampling interval isVertical sampling interval is/>Each light corresponds to a phase value, and a phase distribution diagram corresponding to the discretized light is obtained.
4. The method for reconstructing the three-dimensional point cloud of the surface structured light based on the discretized projection light rays according to claim 1, wherein the specific method in the step S3 is as follows:
retrieving image points in N sets of quadrature absolute phase maps that are in the same phase as in the discretized ray phase profile Image point/>, determined by a camera calibrated parameter matrixCorresponding back-projected ray/>Back projected ray/>With the plane/>, of the calibration plateIntersection to obtain the coordinates of each intersection point as/>，/>，…，/>; And performing straight line fitting on the plurality of intersection points.
5. The method of claim 1, wherein the parameters of each ray in the lookup table L are stored in a structured manner to directly retrieve specific ray parameters via the image point index.
6. The method for reconstructing the three-dimensional point cloud of the surface structured light based on the discretized projection light rays according to any one of claims 1 to 5, wherein the calibration plate is a circular calibration plate.
7. The method for reconstructing a three-dimensional point cloud of surface structured light based on discrete projection light rays according to any one of claims 1 to 5, wherein the calibration plate is placed and the height position of the calibration plate is adjusted by a Z-axis moving platform.
8. The method for reconstructing a three-dimensional point cloud of surface structured light based on discretized projection light of claim 1, further comprising the steps of:
S0, building a surface structured light three-dimensional point cloud reconstruction system based on discrete projection light, wherein the system comprises an industrial camera, a projector, a Z-axis moving platform and a calibration plate, and the calibration plate adjusts N different height positions through the Z-axis moving platform.
9. The surface structured light three-dimensional point cloud reconstruction system based on the discretized projection light is characterized by comprising an industrial camera, a projector, a Z-axis moving platform, a computer and a calibration plate, wherein the surface structured light three-dimensional point cloud reconstruction method based on the discretized projection light model as claimed in any one of claims 1-5 is realized through the system.
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