CN106500619A - The camera internal imageing sensor alignment error separation method of view-based access control model measurement - Google Patents

The camera internal imageing sensor alignment error separation method of view-based access control model measurement Download PDF

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CN106500619A
CN106500619A CN201610920947.3A CN201610920947A CN106500619A CN 106500619 A CN106500619 A CN 106500619A CN 201610920947 A CN201610920947 A CN 201610920947A CN 106500619 A CN106500619 A CN 106500619A
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imageing sensor
camera
axis
coordinate
offset
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CN106500619B (en
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乔玉晶
范宇琪
曹岩
谭世征
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Harbin University of Science and Technology
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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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D3/00—Indicating or recording apparatus with provision for the special purposes referred to in the subgroups
    • G01D3/028—Indicating or recording apparatus with provision for the special purposes referred to in the subgroups mitigating undesired influences, e.g. temperature, pressure
    • G01D3/032—Indicating or recording apparatus with provision for the special purposes referred to in the subgroups mitigating undesired influences, e.g. temperature, pressure affecting incoming signal, e.g. by averaging; gating undesired signals

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  • General Physics & Mathematics (AREA)
  • Studio Devices (AREA)
  • Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)

Abstract

The invention belongs to optical measurement and field of visual inspection, and in particular to a kind of camera internal imageing sensor alignment error separation method of view-based access control model measurement；The method sets up three coordinate eikonal equations of actual imaging point and ideal image point in imageing sensor by analyzing the migration included angle error, offset distance error and offsetting rotational angle error that camera internal imageing sensor actual installation position is present with ideal mounting position；Migration included angle, offset distance and offset rotation angle and coordinate difference relation graphics are drawn again；Then camera calibration, coordinates computed side-play amount are carried out；Lens distortion error is calculated simultaneously；Imageing sensor migration included angle optimal solution, offset distance optimal solution and offset rotation angle optimal solution are finally found out；The present invention has considered lens distortion error and camera internal imageing sensor error in mounting position, and produced error that imageing sensor actual installation position and ideal mounting position are shifted is analyzed and calibration, and then improves reconstruction accuracy.

Description

The camera internal imageing sensor alignment error separation method of view-based access control model measurement
Technical field
The invention belongs to optical measurement and field of visual inspection, and in particular to a kind of camera internal figure of view-based access control model measurement As sensor alignment error separation method.
Background technology
In recent years, machine vision technique is widely applied in many fields with vision detection technology, such as aerial mapping, The fields such as medical imaging, large complicated carved three-dimensional values, the automatic identification of machine components and dimensional measurement.Vision-based detection is not But accuracy of detection, effectively solving approach when even more a lot of common detection methods cannot be realized can be improved.
The acquisition of object to be detected image is the basis of vision-based detection research.Vision detection system should be able to be obtained from industrial camera The image for taking sets out, by determining two-dimentional picture point and actual object point correspondence in image, the thus object in environment-identification, So as to carry out three-dimensional reconstruction.
In being detected using industrial camera, the error produced by camera is the main error in system, and it affects system The certainty of measurement of system.Due to the restriction of manufacture level, actual camera position of image sensor can offset ideal image sensor position Putting causes pixel to shift so as to existence position alignment error, makes shooting result inaccurate.In industrial camera work, especially During which is for large sized object measurement, object distance is hundred times even thousand times of focal length, and alignment error may be put in the measurement results Thousands of times greatly, so camera image sensor alignment error has a strong impact on certainty of measurement, it is necessary to the mistake produced by industrial camera Difference is analyzed, to evaluate to the precision of system.
In existing detection technique, consideration camera lens distortion error, seldom considers camera internal imageing sensor mostly Pixel skew caused by error in mounting position, the present invention carry out mathematical modeling for existing vision measurement technical deficiency, derive Go out to exist the error model and imaging model of alignment error, camera image sensor error in mounting position has been carried out compared with system and In-depth study.
Content of the invention
For the problems referred to above, the invention discloses a kind of camera internal imageing sensor alignment error of view-based access control model measurement Separation method, the method have considered lens distortion error and camera internal imageing sensor error in mounting position, to camera Internal image sensor actual installation position and ideal mounting position shift produced by error be analyzed and calibration, enter And improve reconstruction accuracy.
The object of the present invention is achieved like this：
The camera internal imageing sensor alignment error separation method of view-based access control model measurement, comprises the following steps：
Step a, the skew by analyzing camera internal imageing sensor actual installation position and ideal mounting position presence Angle error, carries out mathematical modeling, sets up the first coordinate eikonal equation of actual imaging point and ideal image point in imageing sensor；
Step b, the skew by analyzing camera internal imageing sensor actual installation position and ideal mounting position presence Range error, carries out mathematical modeling, sets up the second coordinate eikonal equation of actual imaging point and ideal image point in imageing sensor；
Step c, the skew by analyzing camera internal imageing sensor actual installation position and ideal mounting position presence Anglec of rotation error, carries out mathematical modeling, sets up the 3rd coordinate difference of actual imaging point and ideal image point in imageing sensor Equation；
Step d, the first coordinate eikonal equation that is set up using step a, draw migration included angle and coordinate difference relation graphics；
Step e, the second coordinate eikonal equation that is set up using step b, draw offset distance and coordinate difference relation graphics；
The 3rd coordinate eikonal equation that step f, abbreviation step c are set up, draws offset rotation angle and coordinate difference relation graphics；
Step g, camera calibration is carried out, a certain for scaling board calibration point is set to index point, inside and outside the camera for calibrating Parameter is counter to release the calibration point coordinate value, is contrasted with true coordinate value, coordinates computed side-play amount；
Step h, calculate camera lens distortion error；
Step i, the coordinate offset amount obtained using step g deduct the lens distortion error that step h is obtained, using step d Offset distance and coordinate difference relation graphics and step f that the migration included angle for obtaining is obtained with coordinate difference relation graphics, step e The offset rotation angle for obtaining and coordinate difference relation graphics, find out imageing sensor migration included angle optimal solution, offset distance optimum Solution and offset rotation angle optimal solution.
The camera internal imageing sensor alignment error separation method of above-mentioned view-based access control model measurement, step a are specially：
Camera coordinates system O-XYZ is set up as origin using the photocentre of camera, Z axis are overlapped with camera optical axis, X, Y-axis and image Sensor parallel, o are Z axis and imageing sensor intersection point, and Oo is the focal length f of camera；Then in imageing sensor, actual imaging point is sat Mark and ideal image point coordinates Y-axis offset Δ Y in camera coordinates system1With Z axis offset Δ Z1Respectively：
In formula, f represents camera focus, φ1Represent that incident ray and z-axis angle, λ represent imageing sensor actual installation position Put the angle with ideal mounting position.
The camera internal imageing sensor alignment error separation method of above-mentioned view-based access control model measurement, step b are specially：
Camera coordinates system O-XYZ is set up as origin using the photocentre of camera, Z axis are overlapped with camera optical axis, X, Y-axis and image Sensor parallel, o are Z axis and imageing sensor intersection point；Then in imageing sensor, actual imaging point coordinates is sat with ideal image point It is marked on Y-axis offset Δ Y in camera coordinates system2With Z axis offset Δ Z2Respectively：
ΔY2=Δ f tan φ2
ΔZ2=Δ f
In formula, Δ f represents the bias of imageing sensor actual installation position and ideal mounting position, φ2Represent incident Light and Z axis angle.
The camera internal imageing sensor alignment error separation method of above-mentioned view-based access control model measurement, step c are specially：
Camera coordinates system O-XYZ is set up as origin using the photocentre of camera, Z axis are overlapped with camera optical axis, X, Y-axis and image Sensor parallel, o are Z axis and imageing sensor intersection point；Intersection point of the camera optical axis with imageing sensor is defined as ideal image Face and actual imaging areal coordinate axle origin, o-xy is ideal image areal coordinate system, and o-x ' y ' are actual imaging areal coordinate system, x, y Axle, x ', y ' axle are parallel with imageing sensor；Then in imageing sensor actual imaging point coordinates with ideal image point coordinates in phase Y-axis offset Δ Y in machine coordinate system3With X-axis offset Δ X1Respectively：
In formula,A, b are the resonable ideal image coordinate being thought of as in image coordinates system o-xy of imaging point, For deviateing the anglec of rotation.
Step f is specially：
Order：
B=a tan k
r2=a2+b2=a2+a2·tan2K=b2·cot2k+b2
Then：
And then draw Δ X1, Δ Y3With k,Curve distribution figure.
Beneficial effect：The present invention has considered lens distortion error and camera internal imageing sensor installation site is missed Difference, produced error that camera internal imageing sensor actual installation position and ideal mounting position are shifted are analyzed With calibration, and then improve reconstruction accuracy.
Description of the drawings
Fig. 1 is the flow chart of the camera internal imageing sensor alignment error separation method of view-based access control model measurement of the present invention.
Fig. 2 is the corresponding relation figure between camera coordinates system and imageing sensor coordinate system.
The mathematical representation that Fig. 3 is ideal image face when there is angle error with actual imaging face.
The mathematical representation that Fig. 4 is ideal image face when there is biased error with actual imaging face.
The mathematical representation that Fig. 5 is ideal image face when there is anglec of rotation biased error with actual imaging face.
Fig. 6 is migration included angle and coordinate difference relation graphics one.
Fig. 7 is migration included angle and coordinate difference relation graphics two.
Fig. 8 is offset distance and coordinate difference relation graphics.
Fig. 9 is offset rotation angle and coordinate difference relation graphics one.
Figure 10 is offset rotation angle and coordinate difference relation graphics two.
Specific embodiment
Below in conjunction with the accompanying drawings the specific embodiment of the present invention is described in further detail.
Specific embodiment one
The camera internal imageing sensor alignment error separation method of the view-based access control model measurement of the present embodiment, flow chart is as schemed Shown in 1, the method is comprised the following steps：
Step a, the skew by analyzing camera internal imageing sensor actual installation position and ideal mounting position presence Angle error, carries out mathematical modeling, sets up the first coordinate eikonal equation of actual imaging point and ideal image point in imageing sensor；
Step b, the skew by analyzing camera internal imageing sensor actual installation position and ideal mounting position presence Range error, carries out mathematical modeling, sets up the second coordinate eikonal equation of actual imaging point and ideal image point in imageing sensor；
Step c, the skew by analyzing camera internal imageing sensor actual installation position and ideal mounting position presence Anglec of rotation error, carries out mathematical modeling, sets up the 3rd coordinate difference of actual imaging point and ideal image point in imageing sensor Equation；
Step d, the first coordinate eikonal equation that is set up using step a, draw migration included angle and coordinate difference relation graphics；
Step e, the second coordinate eikonal equation that is set up using step b, draw offset distance and coordinate difference relation graphics；
The 3rd coordinate eikonal equation that step f, abbreviation step c are set up, draws offset rotation angle and coordinate difference relation graphics；
Step g, camera calibration is carried out, a certain for scaling board calibration point is set to index point, inside and outside the camera for calibrating Parameter is counter to release the calibration point coordinate value, is contrasted with true coordinate value, coordinates computed side-play amount；
Step h, calculate camera lens distortion error；
Step i, the coordinate offset amount obtained using step g deduct the lens distortion error that step h is obtained, using step d Offset distance and coordinate difference relation graphics and step f that the migration included angle for obtaining is obtained with coordinate difference relation graphics, step e The offset rotation angle for obtaining and coordinate difference relation graphics, find out imageing sensor migration included angle optimal solution, offset distance optimum Solution and offset rotation angle optimal solution.
Specific embodiment two
The camera internal imageing sensor alignment error separation method of the view-based access control model measurement of the present embodiment, is being embodied as On the basis of example one, further limit step a and be specially：
Camera coordinates system O-XYZ is set up as origin using the photocentre of camera, Z axis are overlapped with camera optical axis, X, Y-axis and image Sensor parallel, o are Z axis and imageing sensor intersection point, and Oo is the focal length f of camera；Then in imageing sensor, actual imaging point is sat Mark and ideal image point coordinates Y-axis offset Δ Y in camera coordinates system1With Z axis offset Δ Z1Respectively：
In formula, f represents camera focus, φ1Represent that incident ray and z-axis angle, λ represent imageing sensor actual installation position Put the angle with ideal mounting position.
Specific embodiment three
The camera internal imageing sensor alignment error separation method of the view-based access control model measurement of the present embodiment, is being embodied as On the basis of example one, further limit step b and be specially：
Camera coordinates system O-XYZ is set up as origin using the photocentre of camera, Z axis are overlapped with camera optical axis, X, Y-axis and image Sensor parallel, o are Z axis and imageing sensor intersection point；Then in imageing sensor, actual imaging point coordinates is sat with ideal image point It is marked on Y-axis offset Δ Y in camera coordinates system2With Z axis offset Δ Z2Respectively：
ΔY2=Δ f tan φ2
ΔZ2=Δ f
In formula, Δ f represents the bias of imageing sensor actual installation position and ideal mounting position, φ2Represent incident Light and Z axis angle.
Specific embodiment four
The camera internal imageing sensor alignment error separation method of the view-based access control model measurement of the present embodiment, is being embodied as On the basis of example one, further limit step c and be specially：
Camera coordinates system O-XYZ is set up as origin using the photocentre of camera, Z axis are overlapped with camera optical axis, X, Y-axis and image Sensor parallel, o are Z axis and imageing sensor intersection point；Intersection point of the camera optical axis with imageing sensor is defined as ideal image Face and actual imaging areal coordinate axle origin, o-xy is ideal image areal coordinate system, and o-x ' y ' are actual imaging areal coordinate system, x, y Axle, x ', y ' axle are parallel with imageing sensor；Then in imageing sensor actual imaging point coordinates with ideal image point coordinates in phase Y-axis offset Δ Y in machine coordinate system3With X-axis offset Δ X1Respectively：
In formula,A, b are the resonable ideal image coordinate being thought of as in image coordinates system o-xy of imaging point, For deviateing the anglec of rotation.
Specific embodiment five
The camera internal imageing sensor alignment error separation method of the view-based access control model measurement of the present embodiment, is being embodied as On the basis of example four, further limit step f and be specially：
Order：
B=a tan k
r2=a2+b2=a2+a2·tan2K=b2·cot2k+b2
Then：
And then draw Δ X1, Δ Y3With k,Curve distribution figure.
In order to explanation is further explained in detail to above example, append a few width figures, wherein：
Fig. 2 is the corresponding relation figure between camera coordinates system and imageing sensor coordinate system；
The mathematical representation that Fig. 3 is ideal image face when there is angle error with actual imaging face；
The mathematical representation that Fig. 4 is ideal image face when there is biased error with actual imaging face；
The mathematical representation that Fig. 5 is ideal image face when there is anglec of rotation biased error with actual imaging face；
Fig. 6 and Fig. 7 are migration included angle and coordinate difference relation graphics；
Fig. 8 is offset distance and coordinate difference relation graphics；
Fig. 9 and Figure 10 are offset rotation angle and coordinate difference relation graphics.
Additionally, in step h, coordinate of the picture point in camera under lens distortion can be expressed as：
Wherein, (xu,yu) it is the image point coordinates (x calculated by camera linear modeld,yd) it is real image point Coordinate；δxAnd δyIt is nonlinear distortion value, is represented by：
In formula, k1、k2、p1、p2、s1、s2For nonlinear distortion variable element.

Claims (5)

1. the camera internal imageing sensor alignment error separation method that view-based access control model is measured, it is characterised in that including following step Suddenly：
Step a, the migration included angle by analyzing camera internal imageing sensor actual installation position and ideal mounting position presence Error, carries out mathematical modeling, sets up the first coordinate eikonal equation of actual imaging point and ideal image point in imageing sensor；
Step b, the offset distance by analyzing camera internal imageing sensor actual installation position and ideal mounting position presence Error, carries out mathematical modeling, sets up the second coordinate eikonal equation of actual imaging point and ideal image point in imageing sensor；
Step c, the offset rotation by analyzing camera internal imageing sensor actual installation position and ideal mounting position presence Angular error, carries out mathematical modeling, sets up the 3rd coordinate eikonal equation of actual imaging point and ideal image point in imageing sensor；
Step d, the first coordinate eikonal equation that is set up using step a, draw migration included angle and coordinate difference relation graphics；
Step e, the second coordinate eikonal equation that is set up using step b, draw offset distance and coordinate difference relation graphics；
The 3rd coordinate eikonal equation that step f, abbreviation step c are set up, draws offset rotation angle and coordinate difference relation graphics；
Step g, camera calibration is carried out, a certain for scaling board calibration point is set to index point, using the camera inside and outside parameter for calibrating Counter release the calibration point coordinate value, contrasted with true coordinate value, coordinates computed side-play amount；
Step h, calculate camera lens distortion error；
Step i, the coordinate offset amount obtained using step g deduct the lens distortion error that step h is obtained, and are obtained using step d The offset distance that obtains with coordinate difference relation graphics, step e of migration included angle and coordinate difference relation graphics and step f obtain Offset rotation angle and coordinate difference relation graphics, find out imageing sensor migration included angle optimal solution, offset distance optimal solution and Offset rotation angle optimal solution.
2. the camera internal imageing sensor alignment error separation method that view-based access control model according to claim 1 is measured, its It is characterised by, step a is specially：
Camera coordinates system O-XYZ is set up as origin using the photocentre of camera, Z axis are overlapped with camera optical axis, X, Y-axis and image sensing Device is parallel, and o is Z axis and imageing sensor intersection point, and Oo is the focal length f of camera；Then in imageing sensor actual imaging point coordinates with Ideal image point coordinates Y-axis offset Δ Y in camera coordinates system1With Z axis offset Δ Z1Respectively：
ΔY 1 = f · cosφ 1 · sinφ 1 · s i n λ c o s ( φ 1 + λ )
ΔZ 1 = f sinφ 1 s i n λ c o s ( φ 1 + λ )
In formula, f represents camera focus, φ1Represent incident ray and z-axis angle, λ represent imageing sensor actual installation position with The angle of ideal mounting position.
3. the camera internal imageing sensor alignment error separation method that view-based access control model according to claim 1 is measured, its It is characterised by, step b is specially：
Camera coordinates system O-XYZ is set up as origin using the photocentre of camera, Z axis are overlapped with camera optical axis, X, Y-axis and image sensing Device is parallel, and o is Z axis and imageing sensor intersection point；Then in imageing sensor, actual imaging point coordinates is existed with ideal image point coordinates Y-axis offset Δ Y in camera coordinates system2With Z axis offset Δ Z2Respectively：
ΔY2=Δ f tan φ2
ΔZ2=Δ f
In formula, Δ f represents the bias of imageing sensor actual installation position and ideal mounting position, φ2Represent incident ray with Z axis angle.
4. the camera internal imageing sensor alignment error separation method that view-based access control model according to claim 1 is measured, its It is characterised by, step c is specially：
Camera coordinates system O-XYZ is set up as origin using the photocentre of camera, Z axis are overlapped with camera optical axis, X, Y-axis and image sensing Device is parallel, and o is Z axis and imageing sensor intersection point；By the intersection point of camera optical axis and imageing sensor be defined as ideal image face with Actual imaging areal coordinate axle origin, o-xy be ideal image areal coordinate system, o-x ' y ' be actual imaging areal coordinate system, x, y-axis, X ', y ' axle is parallel with imageing sensor；Then in imageing sensor actual imaging point coordinates and ideal image point coordinates in camera Y-axis offset Δ Y in coordinate system3With X-axis offset Δ X1Respectively：
In formula,A, b are the resonable ideal image coordinate being thought of as in image coordinates system o-xy of imaging point,For deviateing The anglec of rotation.
5. the camera internal imageing sensor alignment error separation method that view-based access control model according to claim 4 is measured, its It is characterised by, step f is specially：
Order：
arctan b a = k
tan k = b a
B=a tan k
r2=a2+b2=a2+a2·tan2K=b2·cot2k+b2
Then：
And then draw Δ X1, Δ Y3With k,Curve distribution figure.
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CN109550649A (en) * 2017-09-25 2019-04-02 深圳市腾盛工业设备有限公司 A kind of dispensing localization method and device based on machine vision
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CN111780689A (en) * 2020-07-13 2020-10-16 四川大学 Optimal rotation angle determination method based on cross-correlation structured light 360-degree measurement
CN111951340A (en) * 2020-08-26 2020-11-17 珠海广浩捷科技股份有限公司 Non-contact optical vision calibration method
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CN109550649A (en) * 2017-09-25 2019-04-02 深圳市腾盛工业设备有限公司 A kind of dispensing localization method and device based on machine vision
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CN117490571A (en) * 2024-01-02 2024-02-02 中国石油大学(华东) Double-plane mirror installation error measurement method for mirror image vision measurement system
CN117490571B (en) * 2024-01-02 2024-03-22 中国石油大学(华东) Double-plane mirror installation error measurement method for mirror image vision measurement system

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