CN107133985A - A kind of vehicle-mounted vidicon automatic calibration method for the point that disappeared based on lane line - Google Patents
A kind of vehicle-mounted vidicon automatic calibration method for the point that disappeared based on lane line Download PDFInfo
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Abstract
The present invention proposes a kind of vehicle-mounted vidicon automatic calibration method for the point that disappeared based on lane line, including：Obtain vehicle and be located at the image that video camera is shot when in the middle of track, image includes clearly left and right lane line；Image is handled, left and right lane line equation in image is obtained, the intersection point P of left and right lane line in image is calculated0And the intersection point P of left and right lane line respectively with image lower sideline1、P2Coordinate in image coordinate system；World coordinate system is set up, image midpoint P is obtained0、P1、P2Corresponding real space point P0'、P1'、P2' coordinate in world coordinate system；According to image midpoint P0、P1、P2Coordinate and corresponding real space point P in image coordinate system0'、P1'、P2' coordinate in world coordinate system, ask for calibration matrix.The inventive method vehicle need to only hit exactly traveling in track or be parked in the middle of track, you can the automatic image to shooting is handled, and inquiry, which is currently located after lane width, tries to achieve calibration matrix, stated accuracy is high, it is simple to operate, manual intervention is not required to, can be demarcated in real time.
Description
Technical field
The present invention relates to automobile image process field, more particularly to a kind of vehicle-mounted vidicon based on lane line disappearance point is certainly
Dynamic scaling method.
Background technology
In recent years, automobile assistant driving (Advanced Driver Assistance Systems) technology was developed rapidly,
Vehicle front collision early warning (Forward Collision Warning) and lane departure warning (Lane Departure
Warning) it is wherein pith.This two functions belong to computer vision application, the image mainly obtained from video camera
Information set out calculate three dimensions in object geological information, with determine vehicle and front obstacle distance and vehicle whether
Run-off-road line, and realize above-mentioned functions premise be need to vehicle-mounted vidicon carry out accurate calibration.Generally assume that video camera
There is a kind of following simple linear relationship between object in taken image and three dimensions：[as]=M [thing], its
The parameter that middle matrix M can regard in the geometrical model of video camera imaging, matrix M as is exactly camera parameters, camera calibration
Process is just to solve for this matrix M process, and matrix M is calibration matrix.
Some existing scaling methods are by putting given shape and the instrument of size on vehicle front or road surface, entering
Calibration matrix is obtained after row image procossing, this kind of method needs to use instrument always in calibration process, and need to manually participate in, and operates
It is inconvenient.What is had extracts the obliquity information of camera by GPS chip inside video camera, is calculated, is marked by a series of complex
Set matrix, this kind of method is relatively complicated in actually implementing, computationally intensive, and demarcation condition is more harsh.
The content of the invention
To solve the above problems, the present invention proposes a kind of vehicle-mounted vidicon automatic Calibration side for the point that disappeared based on lane line
Method, it is not necessary to calibrated reference known to shape, size, can be demarcated, method is simple to operation in real time.
The concrete technical scheme of the present invention is as follows：A kind of vehicle-mounted vidicon automatic Calibration side for the point that disappeared based on lane line
Method, is specifically included：
Step 1, the image for obtaining video camera shooting when vehicle is located at track centre, described image is headstock frontal scene,
Image includes clearly left and right lane line；
Step 2, image is handled, set up image coordinate system, obtain the left and right lane line equation in image, calculate figure
The intersection point P of left and right lane line as in0And the intersection point P of left and right lane line respectively with image lower sideline1、P2In image coordinate system
Coordinate；
Step 3, set up world coordinate system, obtain image midpoint P0、P1、P2Corresponding real space point P0'、P1'、P2'
Coordinate in world coordinate system, its midpoint P0' be true left and right lane line disappearance point, point P1' and P2' it is respectively true left and right
Point on lane line；
Step 4, according to image midpoint P0、P1、P2Coordinate and corresponding real space point P in image coordinate system0'、
P1'、P2' coordinate in world coordinate system, ask for calibration matrix.
As a further improvement on the present invention, the step 2 is specifically included：
2.1st, first pixel for defining the image upper left corner is the origin of coordinates, and the transverse direction of image is X-axis, and longitudinal direction is Y-axis, is built
The vertical image coordinate system in units of pixel；
2.2nd, Canny rim detections first are carried out to image, obtains binary image, then Hough change is carried out to binary image
Straight-line detection is changed, the linear equation of left and right lane line in image is detected：The linear equation of left-lane line is y1=k1x1+b1, it is right
The linear equation of lane line is y2=k2x2+b2, wherein (x1,y1) it is pixel in image in left-lane line in image coordinate system
Coordinate, (x2,y2) it is coordinate of the pixel in image coordinate system in image in right-lane line, k1For the straight line of left-lane line
Slope, k2For the straight slope of right-lane line, b1For the Linear intercept of left-lane line, b2For the Linear intercept of right-lane line, k1、
k2、b1、b2Obtained in Hough transformation straight-line detection；
2.3rd, by the linear equation of the left and right lane line identified, the intersection point P of two lane lines in image is calculated0Sat in image
Coordinate in mark system：P0(x0,y0), whereinCalculate two lane lines and image in image
The intersection point P of lower edge1、P2Coordinate in image coordinate system：P1(x1',y1'), whereiny′1=H, P2(x′2,y
′2), whereiny′2=H, H are pixel count of the image in longitudinal direction.
Beneficial effects of the present invention：The inventive method is by the use of lane line as calibrated reference, and vehicle only need to be in track just
Middle traveling is parked in the middle of track, you can automatic that the image that video camera is shot is handled, and inquiry is currently located lane width
After try to achieve calibration matrix, stated accuracy is high, simple to operate, is not required to manual intervention, can be demarcated in real time；The inventive method
The point and the disappearance point of left and right lane line that selection left and right lane line intersects with headstock respectively set up image coordinate system as calibration point
And world coordinate system, the coordinate of above-mentioned point respectively under image coordinate system and world coordinate system is asked for, so that calibration matrix is asked for,
Amount of calculation is small, and the nominal time is fast, no demarcation condition limitation.
Brief description of the drawings
Fig. 1 is the flow chart of the inventive method.
Fig. 2 is the image coordinate system and key point position view that the present invention is set up.
Fig. 3 is the world coordinate system schematic diagram corresponding with image coordinate system that the present invention is set up.
Embodiment
As shown in figure 1, a kind of vehicle-mounted vidicon automatic calibration method for point that disappeared based on lane line that the present invention is provided, tool
Body comprises the following steps：
Step 1, the image for obtaining video camera shooting when vehicle is located at track centre, described image is headstock frontal scene,
Image includes clearly left and right lane line.
Step 2, image is handled, set up image coordinate system, obtain the left and right lane line equation in image, calculate figure
The intersection point P of left and right lane line as in0And the intersection point P of left and right lane line respectively with image lower edge1、P2In image coordinate system
Coordinate, specifically include：
2.1st, first point for defining the image upper left corner is the origin of coordinates, and the transverse direction of image is X-axis, and longitudinal direction is Y-axis, is set up
Image coordinate system as shown in Figure 2；
2.2nd, Lane detection technology in left and right is prior art, and the present invention first carries out Canny rim detections to image, obtained
Binary image, then Hough transformation straight-line detection is carried out to binary image, detect the straight line side of left and right lane line in image
Journey：The linear equation of left-lane line is y1=k1x1+b1, the linear equation of right-lane line is y2=k2x2+b2, wherein (x1,y1) be
Coordinate of the pixel in image coordinate system in image in left-lane line, (x2,y2) scheming for the pixel in right-lane line in image
As the coordinate in coordinate system, k1For the straight slope of left-lane line, k2For the straight slope of right-lane line, b1For left-lane line
Linear intercept, b2For the Linear intercept of right-lane line, k1、k2、b1、b2Obtained in Hough transformation straight-line detection；
2.3rd, by the left and right lane line linear equation identified, the intersection point P of two lane lines in image is calculated0In image coordinate
Coordinate in system：P0(x0,y0), whereinLane line disappearance point uses two tracks in the picture
The intersection point of line is represented；Calculate the intersection point P of two lane lines and image lower edge in image1、P2Coordinate in image coordinate system：
P1(x′1,y′1), whereiny′1=H, P2(x′2,y′2), whereiny′2=H, H are image in longitudinal direction
On pixel count.
Step 3, set up world coordinate system, obtain image midpoint P0、P1、P2Corresponding real space point P0'、P1'、P2'
Coordinate in world coordinate system, be specially：
With P in image1P2The corresponding real space point in midpoint of line segment be origin, headstock just to real space direction be Y
Axle positive direction, P1Corresponding real space point points to P2The direction of corresponding real space point is X-axis positive direction, and Z axis is perpendicular to sky
Between road surface, set up world coordinate system as shown in Figure 3；
Due to the point P in image1、P2Corresponding real space point P1'、P2' it is typically not greater than 2 meters apart from headstock, can be approximate
Two point P1'、P2' the coordinate in Y-axis in world coordinate system is 0.According to camera pinhole imaging system principle, two lane lines disappear
The certain point died a little at infinity on (parallel lines intersect at infinity), i.e. horizon, therefore point P0' be apart from the distance of vehicle
Infinity.But join for general focal length for 2-8mm (drive recorder and vehicle DAS (Driver Assistant System) common type) video camera
Number, can approximate point P0' the coordinate in Y-axis in world coordinate system is 10000, now available minute of the disappearance point of true lane line
Wei Yu be on the lane line of left and right 2 points are represented.Because the corresponding P of point on the image that calibration process is chosen0'、P1'、P2' three point
It is the point on road surface in real space, so the coordinate on above-mentioned 3 points of Z axis in world coordinate system is all 0.To sum up obtain
Obtain real space point P0'、P1'、P2' the coordinate in world coordinate system is respectively:P0' (- D/2,10000), (D/2,10000),
P'1(- D/2,0), P2' (D/2,0), wherein D is the normal width in track where by consulting the vehicle obtained.
Step 4, according to image midpoint P0、P1、P2Coordinate and corresponding real space point P in image coordinate system0'、
P1'、P2' coordinate in world coordinate system, ask for calibration matrix.
Relation between image and real space can be represented by the formula：
Wherein,For calibration matrix, (x, y) is the pixel in image in image coordinate system
Coordinate, (u, v) be coordinate of the corresponding real space point in world coordinate system, t is coefficient.
By P0、P1、P2、P0'、P1'、P2' coordinate substitute into above formula, wherein in order to avoid there is singularity, P in matrix0Also use
Two coordinate (x0-0.5,y0)、(x0+0.5,y0) represent, obtain：
Wherein matrix parameter a11To a32, and coefficient t1To t4It can be drawn by solving linear equation, so as to try to achieve mark
Set matrix M, completes the demarcation of vehicle-mounted vidicon.
Claims (2)
1. a kind of vehicle-mounted vidicon automatic calibration method for the point that disappeared based on lane line, it is characterised in that methods described includes：
Step 1, the image for obtaining video camera shooting when vehicle is located at track centre, described image is headstock frontal scene, image
Include clearly left and right lane line；
Step 2, image is handled, set up image coordinate system, obtain the left and right lane line equation in image, calculated in image
The intersection point P of left and right lane line0And the intersection point P of left and right lane line respectively with image lower sideline1、P2Seat in image coordinate system
Mark；
Step 3, set up world coordinate system, obtain image midpoint P0、P1、P2Corresponding real space point P0'、P1'、P2' in the world
Coordinate in coordinate system, its midpoint P0' be true left and right lane line disappearance point, P1' and P2' it is respectively true left and right lane line
On point；
Step 4, according to image midpoint P0、P1、P2Coordinate and corresponding real space point P in image coordinate system0'、P1'、
P2' coordinate in world coordinate system, ask for calibration matrix.
2. a kind of vehicle-mounted vidicon automatic calibration method of point that disappeared based on lane line according to claim 1, step 2 is had
Body includes：
2.1st, first pixel for defining the image upper left corner is the origin of coordinates, and the transverse direction of image is X-axis, and longitudinal direction is Y-axis, set up with
Pixel is the image coordinate system of unit；
2.2nd, Canny rim detections first are carried out to image, obtains binary image, then it is straight to binary image progress Hough transformation
Line is detected, detects the linear equation of left and right lane line in image：The linear equation of left-lane line is y1=k1x1+b1, right lane
The linear equation of line is y2=k2x2+b2, wherein (x1,y1) it is seat of the pixel in image coordinate system in image in left-lane line
Mark, (x2,y2) it is coordinate of the pixel in image coordinate system in image in right-lane line, k1For the straight slope of left-lane line,
k2For the straight slope of right-lane line, b1For the Linear intercept of left-lane line, b2For the Linear intercept of right-lane line, k1、k2、b1、
b2Obtained in Hough transformation straight-line detection；
2.3rd, by the linear equation of the left and right lane line identified, the intersection point P of two lane lines in image is calculated0In image coordinate system
In coordinate：P0(x0,y0), whereinCalculate two lane lines and image in image following
The intersection point P of edge1、P2Coordinate in image coordinate system：P1(x′1,y′1), whereiny′1=H, P2(x'2,y'2),
Whereiny'2=H, H are pixel count of the image in longitudinal direction.
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| CN109859278A (en) * | 2019-01-24 | 2019-06-07 | 惠州市德赛西威汽车电子股份有限公司 | The scaling method and calibration system joined outside in-vehicle camera system camera |
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| CN109584305A (en) * | 2017-09-29 | 2019-04-05 | 宝沃汽车（中国）有限公司 | Panorama system scaling method, device and vehicle |
| CN110555885A (en) * | 2018-05-31 | 2019-12-10 | 海信集团有限公司 | calibration method and device of vehicle-mounted camera and terminal |
| CN110555885B (en) * | 2018-05-31 | 2023-07-04 | 海信集团有限公司 | Calibration method and device of vehicle-mounted camera and terminal |
| CN110570475A (en) * | 2018-06-05 | 2019-12-13 | 上海商汤智能科技有限公司 | vehicle-mounted camera self-calibration method and device and vehicle driving method and device |
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| US11205284B2 (en) | 2018-08-24 | 2021-12-21 | Beijing Sensetime Technology Development Co., Ltd. | Vehicle-mounted camera pose estimation method, apparatus, and system, and electronic device |
| CN109572715A (en) * | 2018-11-01 | 2019-04-05 | 北京海纳川汽车部件股份有限公司 | Lane departure warning method, device and the automatic driving vehicle of automatic driving vehicle |
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| CN110163176A (en) * | 2019-05-28 | 2019-08-23 | 北京百度网讯科技有限公司 | The recognition methods of lane line change location, device, equipment and medium |
| CN110163176B (en) * | 2019-05-28 | 2021-06-18 | 北京百度网讯科技有限公司 | Lane line change position identification method, device, equipment and medium |
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| CN110718068A (en) * | 2019-09-27 | 2020-01-21 | 华中科技大学 | Road monitoring camera installation angle estimation method |
| CN112489136B (en) * | 2020-11-30 | 2024-04-16 | 商汤集团有限公司 | Calibration method, position determination device, electronic equipment and storage medium |
| CN112489136A (en) * | 2020-11-30 | 2021-03-12 | 商汤集团有限公司 | Calibration method, position determination method, device, electronic equipment and storage medium |
| WO2022134518A1 (en) * | 2020-12-22 | 2022-06-30 | 上海商汤临港智能科技有限公司 | Method and apparatus for calibrating camera device, and electronic device and storage medium |
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| CN112927309A (en) * | 2021-03-26 | 2021-06-08 | 苏州欧菲光科技有限公司 | Vehicle-mounted camera calibration method and device, vehicle-mounted camera and storage medium |
| CN113223300A (en) * | 2021-04-13 | 2021-08-06 | 河北科技大学 | Traffic accident speed measurement method based on vehicle-mounted video image |
| CN114120258A (en) * | 2022-01-26 | 2022-03-01 | 深圳佑驾创新科技有限公司 | Lane line identification method and device and storage medium |
| CN114659489A (en) * | 2022-03-11 | 2022-06-24 | 苏州清研微视电子科技有限公司 | Front vehicle distance detection method and device based on convex lens imaging principle |
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