CN109102545A - A kind of distortion correction method based on nonmetric - Google Patents
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Abstract
A kind of distortion correction method based on nonmetric of the present invention belongs to computer vision measurement field, is related to a kind of distortion correction method based on nonmetric.This method designs a kind of characteristic point calibration object based on collinear nature first, and the characteristic point for demarcating object is distributed in two non-co-planar planes, collinear feature point is designed in non-co-planar plane, and collinear lines will keep being parallel to each other；Then by reference object image designed by binocular camera and workstation collection, and the automatic identification of collinear feature point is completed, finally pattern distortion is effectively corrected based on line constraint.This method demarcates the characteristic information of object merely with the straight line information architecture of characteristic point, the calibration object of distance between need not have accurate feature point, and the operating time of calibration is reduced by the automatic identification of collinear feature point, improves stability, quick, the precise calibration for realizing pattern distortion have the characteristics that demarcating object is simple to manufacture, demarcates that high-efficient, robustness is good.
Description
Technical field
The invention belongs to computer vision measurement fields, are related to a kind of distortion correction method based on nonmetric.
Background technique
With the variation of modern industry scene parts measurement demand, it is desirable that the geometric sense accurate measurement no longer office of view-based access control model
It is limited to the measurement of small size part under controllable environment, but needs to realize that the accurate of heavy parts under big visual field complex environment is surveyed
Amount.Due to the hardware manufacturing deviation such as camera lens in image acquisition process, cause image that there is certain distortion.Especially for big
Wide-angle lens employed in visual field test, pattern distortion become apparent.Characteristic point due to the influence of lens distortion, in image
It will deviate from the theoretical position in ideal pinhole imaging system, to influence final measurement accuracy, it is therefore necessary to carry out to image effective
Distortion correction.
In conventional method, usually using the Euclidean distance information between characteristic point in calibration object, constraint condition is established, realizes figure
The distortion correction of picture.But it is limited by the limitation of calibration object manufacturing process and expense, large view field measurement is difficult to manufacture large scale
Calibration object with distance between accurate feature point.Therefore, it realizes based on the nonmetric distortion correction for not utilizing distance between characteristic point
It is of great significance.Zhou Fuqiang of BJ University of Aeronautics & Astronautics et al. is in mechanical engineering journal, 2009,45 (8), P228-232.
The isolated camera model that distorts is established in " based on the non-camera marking method for measuring distortion correction " text, based on conllinear
The perspective projection invariance of point, is demarcated using distortion parameter of a large amount of collinear feature points to tight shot.This method simplifies
Camera calibration process, improves calibration speed.But the method in the paper is not suitable for the biggish wide-angle lens of distortion degree
Head.
Liu Lu of Peking University et al., in the patent No.: CN201110070230.1, patent " high-precision wide visual field camera lens
Distortion in real time antidote and system " in the camera lens of wide visual field angle there are problems that Severe distortion, propose a kind of advanced
Row just correction, the distortion correction method that then deviation in first correction is corrected again by Optimization Steps.The method energy
High-precision distortion correction is carried out to wide-angle lens, but needs the calibrating template of larger size, and is needed from different directions and angle
It is repeatedly shot.
Summary of the invention
The invention solves technical problem be that pattern distortion is big under practical big field of view industrial environment, traditional scaling method institute
The problems such as large scale high-precision calibrating object manufacture needed is difficult, at high cost, invents a kind of distortion correction method based on nonmetric.
This method designs a kind of characteristic point calibration object based on collinear nature, then the characteristic point designed by camera acquisition first
Image and the automatic identification for completing collinear feature point finally effectively correct pattern distortion based on line constraint.The method,
The characteristic information of object is demarcated merely with the straight line information architecture of characteristic point, the calibration object of distance between need not have accurate feature point,
And the operating time of calibration is reduced by the automatic identification of collinear feature point, improves stability, realize fast and accurately image
Distortion correction.
The technical solution adopted by the present invention is that a kind of distortion correction method based on nonmetric, characterized in that this method is first
A kind of characteristic point calibration object based on collinear nature is first designed, calibration object characteristic point is distributed in two non-co-planar planes, non-total
Collinear feature point is designed on facial plane, and the collinear lines formed will keep being parallel to each other；Then pass through binocular camera and work
It stands and acquires designed reference object image, and complete the automatic identification of collinear feature point, it is finally abnormal to image based on line constraint
Change is effectively corrected；Specific step is as follows for method:
The first step demarcates the characteristic point distribution design of object
To guarantee that characteristic point has certain depth information, characteristic point is distributed in two non-co-planar planes, non-co-planar flat
Collinear feature point is designed on face, and the collinear lines formed will keep being parallel to each other, every row characteristic point data amount is identical；Demarcate object
4 characteristic point reasonably selects n collinear feature point of every row, total N according to the field range of measure field using circular index point
A characteristic point；Designed feature point image is acquired using left and right camera 1,2 and work station 3；
Second step, the automatic identification of collinear feature point
To identify collinear points, using the collinear feature point method of identification based on region circle inner iteration optimization, detailed process is as follows:
1) feature point set the N [(x obtained from image1, y1),(x2, y2),...,(xq, yq),...,(xN, yN)] in, appoint and takes
One point q (xq, yq), straight line b=-x is constituted in hough space by Hough transformationqa+yq；
2) straight line b=-xqa+yqIt is (a with constituted straight line difference intersection point of remaining the N-1 point in hough spaceq1,
bq1),(aq2, bq2),...,(aq(q-1), bq(q-1)),(aq(q+1), bq(q+1)),...,(aqN, bqN)；
3) with wherein certain point (aqi, bqi), i ∈ [1, N] and i ≠ q are the center of circle, and making radius outward is RqiCircle so that this
When there are n-2 remaining intersection point to be comprised in the circle, include circular arc；
4) R all in the case of traversal i=1 to i=N, i ≠ qqi, calculate least radius Rqm, save corresponding circle
The heart (aqm, bqm) with include n-2 intersection point [(a in smallest circleqin1, bqin1),(aqin2, bqin2),...,(aqin(n-2),
bqin(n-2))]；Then, the point [(x under cartesian coordinate system corresponding to this n-1 intersection pointq, yq),(xin1, yin1),(xin2,
yin2),...,(xin(n-2), yin(n-2))] be identify with (xq, yq) conllinear characteristic point；
5) by second step 4) in the collinear feature point that identifies deleted from total characteristic point set, repeat in second step
1) -4) step, until identifying each row collinear feature point；
Third step, the distortion correction based on line constraint
To big view field image, its distortion is mainly made of radial distortion and tangential distortion, therefore this method is directed to the diameter of image
It is corrected to tangential distortion；Assuming that the point for projecting to imaging plane is p', due to distortion effects, actual extracting institute invocation point
For p；Wherein, polar coordinates of the p point under optical center coordinate system areCartesian coordinate isP' under optical center coordinate system
Polar coordinates beCartesian coordinate isIts distortion model is as follows:
For radial distortion: radial distortion only makes the point in image radially generate distortion, shows as to put along diameter
To pulling to or far from optical center, radial distortion is indicated with formula (1) under cartesian coordinate:
Wherein, Δ r (p) is the radial distortion on the position p；C2i+1For coefficient of radial distortion, since high-order term is for abnormal
It is too small to become influence, has ignored the high-order term greater than 5 times, then radial distortion becomes following form:
Δr(p)≈C3r3+C5r5 (2)
For tangential distortion: tangential distortion is to be retouched as produced by the nonorthogonality construction of camera lens using Conrady model
State tangential distortion:
Wherein, Δ TxWith Δ TyRespectively along the tangential distortion in the direction x and y at p point；P1、P2、Pi+2For tangential distortion system
Number；Similarly, high-order term Pi+2It is negligible；
According to the straight line information of designed characteristic point, introduces line constraint and distortion correction is carried out to feature point for calibration；Choosing
A line is taken not yet to carry out the parallel collinear points of nonmetric correctionAnd enable distortion factor initial value [C3,C5,P1,P2]=
[0,0,0,0] obtains new point set after correcting by above-mentioned distortion modelIt is fitted using least square methodBe total to linear equation { l }, according to collinear feature point arrangement, it is known that shared N/n group collinear points, every group n
Characteristic point is lain mutually in line；By Iterative search algorithm, each group collinear points are minimizedWith putting down for its fitting a straight line { l }
Square sum of the distance el, distortion factor [C is finally obtained using formula (5)3,C5,P1,P2]；
Wherein,It is the angle of fitting a straight line l Yu optical center coordinate system horizontal axis, rlIt is real for the distance of fitting a straight line l to optical center
The distortion correction of existing image.
The beneficial effects of the invention are as follows this method to demarcate object using a kind of characteristic point based on collinear nature, then passes through phase
Feature point image designed by machine and workstation collection, and realize the automatic identification of collinear feature point, finally it is based on line constraint
Pattern distortion is effectively corrected.The method overcomes merely with the characteristic information of the straight line information architecture calibration object of characteristic point
The problems such as manufacture of large scale high-precision calibrating object needed for traditional scaling method is difficult, at high cost has standard without large scale
The calibration object of distance between true characteristic point.And the operating time of calibration is reduced by the automatic identification of characteristic point, improves stability, it is real
Quick, the precise calibration for having showed pattern distortion have the characteristics that demarcating object is simple to manufacture, demarcates that high-efficient, robustness is good.
Detailed description of the invention
Fig. 1 is nonmetric distortion correction system schematic, wherein the left camera of 1-, the right camera of 2-, 3- work station, 4- calibration
Object.
Fig. 2 is the flow chart of the distortion correction method based on nonmetric.
Specific embodiment
A specific embodiment of the invention is described in detail below in conjunction with technical solution and attached drawing.
Left and right camera is the VC-12MC-M/C of South Korea Vieworks company production in the binocular vision system of the present embodiment
65 cameras, resolution ratio: 4096 × 3072, imaging sensor: CMOS, frame per second: silent frame, highest 64.3fps.Camera lens model
EF16-35mmf/2.8LIIUSM, lens focus: f=16-35, APS focal length: 25.5-52.5, aperture: F2.8.Shooting condition is such as
Under: picture pixels are 4096 × 3072, and lens focus 35mm, operating distance 1.5m, visual field size is about 1000 × 1200mm.
The present invention designs a kind of characteristic point calibration object 4 based on collinear nature first, to guarantee that characteristic point has centainly
Depth information, characteristic point are distributed in two non-co-planar planes, design collinear feature point in non-co-planar plane, formation it is conllinear straight
Line keeps being parallel to each other as far as possible, and every row characteristic point data amount is identical.In the present embodiment, demarcate object characteristic point be distributed in two it is non-
Coplanar flat, as shown in Figure 1.The characteristic point of calibration object uses diameter for the circular index point of 6mm, and every row characteristic point is 19,
Calibration object shares 304 characteristic points, and designed feature point image is then acquired by left and right camera 1,2 and work station 3, and
The automatic identification of collinear feature point is completed, finally pattern distortion is effectively corrected based on line constraint.
Fig. 2 is the flow chart of the distortion correction method based on nonmetric, and specific step is as follows for method:
The first step demarcates the characteristic point distribution design of object
Collinear feature point is designed in non-co-planar plane, and to guarantee that collinear lines are parallel to each other, every row characteristic point quantity
It is identical.According to the field range of measure field, n=19 collinear feature point of every row is selected, there are 16 row collinear points, amounts to N=304
A characteristic point；Using the designed feature point image of binocular camera and workstation synchronization acquisition.
Second step, the automatic identification of collinear feature point
The image pixel coordinates that the characteristic point center of circle is extracted using grey scale centre of gravity method, it is complete based on region circle inner iteration optimization method
At the identification and matching of collinear feature point, detailed process is as follows:
1) feature point set the N [(x obtained from image1, y1),(x2, y2),...,(xq, yq),...,(xN, yN)] in, appoint and takes
One point q (xq, yq), straight line b=-x is constituted in hough space by Hough transformationqa+yq；
2) straight line b=-xqa+yqIt is (a with constituted straight line difference intersection point of remaining the N-1 point in hough spaceq1,
bq1),(aq2, bq2),...,(aq(q-1), bq(q-1)),(aq(q+1), bq(q+1)),...,(aqN, bqN)；
3) with wherein certain point (aqi, bqi) (i ∈ [1, N] and i ≠ q) be the center of circle, make outward radius be RqiCircle so that
There are n-2 remaining intersection points to be comprised in the circle at this time, includes circular arc；
4) R all in the case of traversal i=1 to i=N, i ≠ qqi, calculate least radius Rqm, save corresponding circle
The heart (aqm, bqm) with include n-2 intersection point [(a in smallest circleqin1, bqin1),(aqin2, bqin2),...,(aqin(n-2),
bqin(n-2))].Then, the point [(x under cartesian coordinate system corresponding to this n-1 intersection pointq, yq),(xin1, yin1),(xin2,
yin2),...,(xin(n-2), yin(n-2))] be identify with (xq, yq) conllinear characteristic point；
5) by second step 4) in the collinear feature point that identifies deleted from total characteristic point set, repeat in second step
1) -4) step, until identifying each row collinear feature point；
Third step, the distortion correction based on line constraint
Radial distortion model is established according to formula (1), (2), establishes tangential distortion model according to formula (3), (4).
According to the straight line information of designed characteristic point, introduces line constraint and distortion correction is carried out to feature point for calibration；Choosing
A line is taken not yet to carry out the parallel collinear points of nonmetric correctionAnd enable distortion factor initial value [C3,C5,P1,P2]=
[0,0,0,0] obtains new point set after correcting by above-mentioned distortion modelIt is fitted using least square methodBe total to linear equation { l }, according to collinear feature point arrangement, it is known that share 16 row collinear points, every row 19
Characteristic point is lain mutually in line；Each group collinear points are minimized by Iterative search algorithm according to formula (5)It is quasi- with it
Close the sum of the squared-distance of straight line { l } el, can finally obtain distortion factor [C3,C5,P1,P2].Using above method respectively to a left side
The distortion factor of right camera is demarcated, and realizes the distortion correction of image.
The results are shown in Table 1 for characteristic point coordinate after characteristic point coordinate extracts result and nonmetric correction before distortion correction:
Table 1
This method realizes the fast of pattern distortion merely with the characteristic information of the straight line information architecture calibration object of characteristic point
Speed, precise calibration.
Claims (1)
1. a kind of distortion correction method based on nonmetric, characterized in that this method designs a kind of based on collinear nature first
Characteristic point demarcates object, and the characteristic point for demarcating object is distributed in two non-co-planar planes, designs collinear feature point in non-co-planar plane,
And the collinear lines formed will keep being parallel to each other；Then pass through calibration object figure designed by binocular camera and workstation collection
Picture, and the automatic identification of collinear feature point is completed, finally pattern distortion is effectively corrected based on line constraint；The tool of method
Steps are as follows for body:
The first step demarcates the characteristic point distribution design of object
To guarantee that characteristic point has certain depth information, the characteristic point of calibration object (4) is distributed in two non-co-planar planes,
Collinear feature point is designed in non-co-planar plane, and the collinear lines formed will keep being parallel to each other, the data volume of every row characteristic point
It is identical；The characteristic point for demarcating object uses circular index point, according to the field range of measure field, reasonably selects every row n collinearly
Characteristic point, total N number of characteristic point；Designed feature point image is acquired using left and right camera (1,2) and work station (3)；
Second step, the automatic identification of collinear feature point
To identify collinear feature point, using the collinear feature point method of identification based on region circle inner iteration optimization, detailed process is as follows:
1) feature point set the N [(x obtained from image1,y1),(x2,y2),...,(xq,yq),...,(xN,yN)] in, appoint and takes a point q
(xq,yq), straight line b=-x is constituted in hough space by Hough transformationqa+yq；
2) straight line b=-xqa+yqIt is (a with constituted straight line difference intersection point of remaining the N-1 point in hough spaceq1,bq1),
(aq2,bq2),...,(aq(q-1),bq(q-1)),(aq(q+1),bq(q+1)),...,(aqN,bqN)；
3) with wherein certain point (aqi,bqi), i ∈ [1, N] and i ≠ q are the center of circle, and making radius outward is RqiCircle so that having at this time
N-2 remaining intersection points are comprised in the circle, include circular arc；
4) R all in the case of traversal i=1 to i=N, i ≠ qqi, calculate least radius Rqm, save the corresponding center of circle
(aqm,bqm) with include n-2 intersection point [(a in smallest circleqin1,bqin1),(aqin2,bqin2),...,(aqin(n-2),
bqin(n-2))]；Then, the point [(x under cartesian coordinate system corresponding to this n-1 intersection pointq,yq),(xin1,yin1),(xin2,
yin2),...,(xin(n-2),yin(n-2))] be identify with (xq,yq) conllinear characteristic point；
5) by second step 4) in the collinear feature point that identifies deleted from total characteristic point set, repeat 1 in second step)-
4) step, until identifying each row collinear feature point；
Third step, the distortion correction based on line constraint
To big view field image, it distorts is made of radial distortion and tangential distortion, carries out school for the radial direction and tangential distortion of image
Just；Assuming that the point for projecting to imaging plane is p', due to distortion effects, actual extracting institute's invocation point is p；Wherein, p point is in optical center
Polar coordinates under coordinate system areCartesian coordinate isThe polar coordinates under optical center coordinate system of p' areFlute
Karr coordinate is
For radial distortion: radial distortion only makes the point in image radially generate distortion, shows as to put along radial drawing
To or far from optical center, the radial distortion Δ r (p) under cartesian coordinate are as follows:
Wherein, Δ r (p) is the radial distortion on the position p；C2i+1For coefficient of radial distortion, since high-order term is for distortion effects
It is too small, the high-order term greater than 5 times is had ignored, then radial distortion becomes following form:
Δr(p)≈C3r3+C5r5 (2)
For tangential distortion: tangential distortion is to be cut as produced by the nonorthogonality construction of camera lens using the description of Conrady model
To distortion:
Wherein, Δ TxWith Δ TyRespectively along the tangential distortion in the direction x and y at p point；P1、P2、Pi+2For tangential distortion coefficient；Together
Sample, high-order term Pi+2It ignores；
According to the straight line information of designed characteristic point, introduces line constraint and distortion correction is carried out to feature point for calibration；Choose one
Row not yet carries out the parallel collinear points of nonmetric correctionAnd enable distortion factor initial value [C3,C5,P1,P2]=[0,0,
0,0], new point set is obtained after correcting by above-mentioned distortion modelIt is fitted using least square method
Be total to linear equation { l } shares N/n group collinear points according to collinear feature point arrangement, and every group of n characteristic point is lain mutually in line；
By Iterative search algorithm, each group collinear points are minimizedWith the sum of the squared-distance of its fitting a straight line { l } el, benefit
Distortion factor [C is finally obtained with formula (5)3,C5,P1,P2]；
Wherein,It is the angle of fitting a straight line l Yu optical center coordinate system horizontal axis, rlFor the distance of fitting a straight line l to optical center, realize
The distortion correction of image.
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