CN112179292A - Projector-based line structured light vision sensor calibration method - Google Patents
Projector-based line structured light vision sensor calibration method Download PDFInfo
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- CN112179292A CN112179292A CN202011305166.6A CN202011305166A CN112179292A CN 112179292 A CN112179292 A CN 112179292A CN 202011305166 A CN202011305166 A CN 202011305166A CN 112179292 A CN112179292 A CN 112179292A
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- projector
- laser line
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
- G01B11/2504—Calibration devices
Abstract
The invention relates to a calibration method of a linear structured light vision sensor based on a projector, which comprises the following steps of firstly carrying out distortion correction on a camera and the projector; calibrating a binocular vision system of a camera and a projector, specifically comprising acquiring two or more checkerboard images under different visual angles, and solving parameters through matching points between the two cameras; building a plane target on the movable guide rail, projecting phase shift stripes and decoding through a projector, and calculating the corresponding space coordinates of each pixel point by using a binocular vision principle; opening a laser device to emit a laser line and collecting an image, extracting and determining a spatial coordinate of the laser line, and determining whether laser line calibration is finished or not according to the coordinate; and adjusting the position of the plane target according to the calibration condition until the laser line calibration processing is completed. The invention can provide the projector-based line-structured light vision sensor calibration method which is simple to operate, high in working efficiency and capable of realizing calibration processing of the whole laser line at one time.
Description
Technical Field
The invention relates to the technical field of visual three-dimensional measurement, in particular to a calibration method of a line structured light visual sensor based on a projector.
Background
The three-dimensional measurement scheme based on the line structured light is widely applied to the fields of reverse engineering, industrial automation, test measurement, ancient cultural relic protection and the like, and is used as precision measurement equipment, and the precision and the production efficiency of the structured light visual sensor are directly influenced by a calibration method. The traditional calibration method adopts a three-dimensional target, and the structured light is calibrated through three-dimensional structural features on the three-dimensional target. The processing technology of the three-dimensional target is complex and high in cost, and the application of the method is greatly limited. The invention adopts the structure light calibration method based on the projector, realizes the calibration of the structure light by using the projector and the plane target, has simple manufacture and flexible use of the target, effectively expands the calibration method of the structure light sensor and improves the calibration efficiency. The conventional checkerboard calibration method needs the camera to be capable of seeing a complete checkerboard, otherwise, the checkerboard corner points in the camera visual field range cannot be accurately positioned, the camera in the near field visual field range is often only one fourth of a far field or even smaller, the calibration requirements of the near field and the far field are often difficult to be considered simultaneously by adopting the conventional checkerboard calibration method, and the problem of relative positioning errors between two different calibration plates can be caused by replacing the calibration plates. The projector can be used for projecting horizontal and vertical phase shift stripes to realize the space coding of each pixel point in the visual field range of the camera, and the projector and the camera can form a binocular vision model so as to calculate the space coordinate of each pixel point.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a projector-based line structured light vision sensor calibration method which is simple to operate, high in working efficiency and capable of realizing calibration processing of the whole laser line at one time.
In order to achieve the purpose, the invention adopts the following technical scheme.
A line structured light vision sensor calibration method based on a projector specifically comprises the following steps:
step S1: firstly, distortion correction is carried out on a camera and a projector, the distortion of the camera is the nonlinear imaging characteristic introduced by the optical characteristic of a lens, and the projector is regarded as an inverse camera and adopts a camera distortion calculation model to carry out distortion correction;
step S2: calibrating a binocular vision system of a camera and a projector, specifically comprising collecting two or more checkerboard images under different visual angles, and solving external parameters of the binocular vision system through matching points between the two cameras, namely a spatial transformation coordinate corresponding relation between the two cameras;
step S3: building a plane target on the movable guide rail, projecting phase shift stripes through a projector, decoding the phase shift stripes, and calculating corresponding space coordinates of each pixel point by using a binocular vision principle;
step S4: then opening a laser device to emit a laser line and collecting an image, extracting the laser line and determining the spatial coordinates of each pixel point of the laser line, and determining whether laser line calibration is finished according to each extracted spatial coordinate;
step S5: if the step S4 determines that the laser line calibration is completed, recording laser line calibration information, and ending the laser line calibration; if the laser line calibration is not completed in the step S4, the planar target position on the moving guide rail is re-processed in the steps S3 and S4 until the laser line calibration process is completed, and the process is ended.
As a further improvement of the present invention, the phase shift stripe decoding of step S3 adopts a three-step phase shift method for decoding.
As a further improvement of the present invention, the laser line extraction in step S4 is calculated and extracted by using a fitting method or a gravity center method.
As a further improvement of the invention, the fitting method is to fit pixels vertical to the laser line by setting the brightness of the laser line to be in Gaussian distribution and adopting a Gaussian function; the center of gravity method is to perform center of gravity extraction by using a width range pixel value perpendicular to the laser line direction.
As a further improvement of the present invention, the distortion calculation model of step S1 specifically includes a radial distortion model and a tangential distortion model.
Due to the application of the technical scheme, the technical scheme of the invention has the following beneficial effects: according to the technical scheme, a camera can be calibrated by using a common projector without a complex high-precision three-dimensional target; according to the technical scheme, a binocular vision system is formed by a camera and a projector, the phase shift stripe projected by the projector can uniquely determine the coordinate of each point on a projection plane, and the mapping relation between a camera pixel plane and a light plane is established; the technical scheme adopts a fitting method or a gravity center method to extract the center of the laser line, so that the algorithm is stable and the anti-interference capability is strong; the technical scheme can realize the calibration treatment of the whole laser line at one time, and has the beneficial technical effects of simple and convenient operation and high working efficiency.
Drawings
FIG. 1 is a schematic diagram of the overall flow structure of the present invention.
FIG. 2 is a schematic diagram of the calibration principle of the present invention.
FIG. 3 is a schematic diagram of a phase-shift fringe decoding pattern and intensity curve according to the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and the examples.
As shown in fig. 1 to 3, a calibration method for a line structured light vision sensor based on a projector specifically includes the following steps:
step S1: firstly, distortion correction is carried out on a camera and a projector, the distortion of the camera is the nonlinear imaging characteristic introduced by the optical characteristic of a lens, and the projector is regarded as an inverse camera and adopts a camera distortion calculation model to carry out distortion correction;
step S2: calibrating a binocular vision system of a camera and a projector, specifically comprising collecting two or more checkerboard images under different visual angles, and solving external parameters of the binocular vision system through matching points between the two cameras, namely a spatial transformation coordinate corresponding relation between the two cameras;
step S3: building a plane target on the movable guide rail, projecting phase shift stripes through a projector, decoding the phase shift stripes, and calculating corresponding space coordinates of each pixel point by using a binocular vision principle;
step S4: then opening a laser device to emit a laser line and collecting an image, extracting the laser line and determining the spatial coordinates of each pixel point of the laser line, and determining whether laser line calibration is finished according to each extracted spatial coordinate;
step S5: if the step S4 determines that the laser line calibration is completed, recording laser line calibration information, and ending the laser line calibration; if the laser line calibration is not completed in the step S4, the planar target position on the moving guide rail is re-processed in the steps S3 and S4 until the laser line calibration process is completed, and the process is ended.
The phase shift stripe decoding of the step S3 adopts a three-step phase shift method for decoding; the laser line extraction in the step S4 adopts a fitting method or a gravity center method to carry out calculation and extraction processing; the fitting method is to fit pixels vertical to the laser line by setting the brightness of the laser line to be in Gaussian distribution and adopting a Gaussian function; the gravity center method is to extract the gravity center by using the width range pixel value perpendicular to the laser line direction; the distortion calculation model of step S1 specifically includes a radial distortion model and a tangential distortion model.
As shown in fig. 2, the laser is turned on and the camera captures an image and determines the coordinates of the pixels of the points of the laser line. And closing the laser, forming a binocular vision system by the camera and the projector, projecting the phase shift stripes by the projector, and determining the world coordinates of each pixel point on the laser line through stripe decoding to finish the calibration of the laser line. And moving the projection plane, and calibrating the laser lines at different heights until the calibration is completed.
1. Distortion correction for camera and projector
The distortion of the camera refers to the non-linear imaging characteristic introduced by the optical characteristic of the lens, and the projector generally considers the non-linear imaging characteristic as an 'inverse camera' and adopts a camera calibration model for distortion correction, so that only the camera distortion model is introduced here. The distortion of the camera can be generally classified into radial distortion and tangential distortion. The mathematical model of radial distortion can be expressed as:
wherein
，
Is the pixel coordinates in the case of no distortion,
for the distorted pixel coordinates, it can be known from the above expression that the radial distortion needs to be solved
Three parameters.
The mathematical model of the tangential distortion can be expressed as:
；
the tangential distortion model contains 2 parameters
Solving for
And calibrating by using a checkerboard.
Distortion correction also requires the use of an imaging model of the camera:
wherein the content of the first and second substances,
is the coordinates of the image plane and is,
and acquiring images of a plurality of checkerboards under different angles for the space coordinates corresponding to the image points under the camera coordinate system, and establishing a camera imaging model and a distortion model, namely solving the camera distortion parameters.
2. Binocular vision calibration of camera and projector
The binocular vision calibration collects checkerboard images under different visual angles, the external parameters (namely the space transformation relation between the two cameras) of the binocular vision system are solved through the multiple matching point pairs between the two cameras, and the projector is regarded as an 'inverse camera', so that the calibration of the binocular vision system between the projector and the cameras can be realized.
3. Phase-shifted fringe decoding for projector projection
Here, the three-step phase shift method is taken as an example to describe the decoding principle of the phase shift stripes, and the pattern of the phase shift stripes and their intensity profile are shown in fig. 3 below, which shows the stripes and their intensity profile.
The three-step phase shift method requires the projection of three cosine-varying fringes, the light intensity formula of which is:
wherein x, y are pixel coordinates,
as the phase, f is the fringe variation frequency, a is the base intensity of the fringe, and B is the fringe intensity variation amplitude. The phase decoding formula of the three-step phase shift stripe is as follows:
the positioning in the x direction can be realized by using the formula, namely, the x coordinate corresponding to each point is calculated. Similarly, the y-direction coordinate positioning can be realized by projecting the y-direction stripes.
4. Laser line extraction
The laser line extraction algorithm can be mainly classified into a fitting method and a gravity center method at present. The fitting method generally assumes that the laser line brightness is gaussian distributed, and adopts a gaussian function to fit pixels perpendicular to the laser line. The gravity center method utilizes the pixel value with a certain width vertical to the direction of the laser line to extract the gravity center, and has the advantages of simple calculation, strong anti-interference capability, small noise influence and the like. The formula of the center of gravity method is:
wherein
And the pixel value in the direction perpendicular to the laser line, i is the pixel coordinate, and c is the center coordinate of the laser line.
The above is only a specific application example of the present invention, and the protection scope of the present invention is not limited in any way. All the technical solutions formed by equivalent transformation or equivalent replacement fall within the protection scope of the present invention.
Claims (5)
1. A line structured light vision sensor calibration method based on a projector is characterized by comprising the following steps:
step S1: firstly, distortion correction is carried out on a camera and a projector, the distortion of the camera is the nonlinear imaging characteristic introduced by the optical characteristic of a lens, and the projector is regarded as an inverse camera and adopts a camera distortion calculation model to carry out distortion correction;
step S2: calibrating a binocular vision system of a camera and a projector, specifically comprising collecting two or more checkerboard images under different visual angles, and solving external parameters of the binocular vision system through matching points between the two cameras, namely a spatial transformation coordinate corresponding relation between the two cameras;
step S3: building a plane target on the movable guide rail, projecting phase shift stripes through a projector, decoding the phase shift stripes, and calculating corresponding space coordinates of each pixel point by using a binocular vision principle;
step S4: then opening a laser device to emit a laser line and collecting an image, extracting the laser line and determining the spatial coordinates of each pixel point of the laser line, and determining whether laser line calibration is finished according to each extracted spatial coordinate;
step S5: if the step S4 determines that the laser line calibration is completed, recording laser line calibration information, and ending the laser line calibration; if the laser line calibration is not completed in the step S4, the planar target position on the moving guide rail is re-processed in the steps S3 and S4 until the laser line calibration process is completed, and the process is ended.
2. The calibration method of the line structured light vision sensor based on the projector as claimed in claim 1, wherein: and the phase shift stripe decoding of the step S3 adopts a three-step phase shift method for decoding.
3. The calibration method of the line structured light vision sensor based on the projector as claimed in claim 1, wherein: and the laser line extraction in the step S4 adopts a fitting method or a gravity center method to carry out calculation and extraction processing.
4. The calibration method of the line structured light vision sensor based on the projector as claimed in claim 1, wherein: the fitting method is to fit pixels vertical to the laser line by setting the brightness of the laser line to be in Gaussian distribution and adopting a Gaussian function; the center of gravity method is to perform center of gravity extraction by using a width range pixel value perpendicular to the laser line direction.
5. The calibration method of the line structured light vision sensor based on the projector as claimed in claim 1, wherein: the distortion calculation model of step S1 specifically includes a radial distortion model and a tangential distortion model.
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| CN115082538A (en) * | 2022-06-20 | 2022-09-20 | 南京理工大学 | System and method for three-dimensional reconstruction of surface of multi-view vision balance ring part based on line structure light projection |
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