Television – Camera – system and detail – Optics
Reexamination Certificate
2001-07-13
2004-09-14
Christensen, Andrew (Department: 2615)
Television
Camera, system and detail
Optics
C348S187000, C348S207990, C382S275000, C356S124000, C356S394000, C358S406000
Reexamination Certificate
active
06791616
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a correcting method of lens distortion of an image.
2. Description of Related Art
An image taken by a video camera or a digital camera causes distortion (distortion aberration) depending upon a camera lens. The distortion aberration is generally extreme with a wide angle, increases toward a periphery of the image, and increases to 3% or more particularly with a zoom lens. Moreover, since the image is deformed in a so-called barrel or bobbin shape, this distortion aberration disadvantageously adversely affects estimation in computer vision, measurement using the image, and the like.
Parameters such as a distortion coefficient for determining a camera lens distortion are called a camera internal parameter, and cameral calibration means that the camera internal parameter is obtained. When the camera internal parameter can be obtained through camera calibration, the image lens distortion can be corrected by an image processing using the internal parameter.
A conventional camera calibrating method is disclosed in many research papers.
In the aforementioned conventional method, a relation between a certain point in a three-dimensional space and a point signal to the certain point (correspondence point) in the image is derived, and the internal parameter is estimated. There are two methods of obtaining the correspondence point as follows:
(1) A person designates the correspondence point with a mouse or the like.
(2) A grid intersection point, a polygon or polyhedron apex, or another characteristic point is automatically detected.
Since either one of these methods includes a measurement error, a large number of correspondence points have to be given in order to inhibit an error influence. That is, the more the number of correspondence points is, the more precise the obtained internal parameter becomes. Therefore, correspondence of an enormous number of (several tens to several hundreds) points has to be designated.
Moreover, these methods have the following problems.
In the method (1) in which the person designates the correspondence point with the mouse or the like, the error is large, operation is monotonous, and much labor is necessary. Furthermore, fatigue increases the error during designation.
In the method (2) (characteristic point detecting method) of automatically detecting the characteristic point by the image processing, the number of points detectable by the processing is limited. For example, when the grid intersection point is detected, the number of intersection points is only 88 in total even with 8 longitudinal lines and 11 lateral lines. It is said that at least 200 points or more are necessary for obtaining the parameter with good precision, and it is necessary to prepare the corresponding grid, polyhedron, and the like.
SUMMARY OF THE INVENTION
The present invention has been developed to solve the aforementioned various problems. That is, an object of the present invention is to provide an image lens distortion correcting method in which (1) no correspondence point needs to be given, (2) any special tool or object is not used, and (3) all points on an image are used, so that an internal parameter can automatically be obtained with high precision, and an image lens distortion can be corrected with high precision.
According to the present invention, there is provided an image lens distortion correcting method comprising: an image printing step (A) for printing an arbitrary image I
1
in a computer; an image pickup step (B) for taking the printed image I
1
with a camera having a lens distortion and obtaining a photographed image I
2
in the computer; a parameter estimating step (C) for obtaining a parameter &thgr; such that the image I
1
is artificially distorted with the parameter &thgr; and an obtained distorted image I
1
ud
agrees with the photographed image I
2
; and an image correcting step (D) for using the obtained parameter &thgr; to correct the image taken by the camera.
According to the aforementioned method of the present invention, first the arbitrary image I
1
(Computer graphics, a picture extracted with a scanner, or an image taken by a digital camera) is prepared as a calibration pattern in the computer. Subsequently, the image I
1
is printed with a printer having no distortion. The printed image I
1
is taken by a camera to be corrected, and the distorted photographed image I
2
is obtained. When the certain internal parameter &thgr; is given, the image I
1
can artificially be distorted. When the artificially distorted image I
1
ud
is compared with the distorted image I
2
and the images accurately equal with each other, the given parameter &thgr; is desirable, and the obtained parameter &thgr; can be used to correct the camera lens distortion.
According to a preferred embodiment of the present invention, the parameter &thgr; includes a position correction parameter &thgr;
u
for correcting a position, and a distortion correction parameter &thgr;
d
for correcting the distortion.
The position correction parameter &thgr;
u
is a parameter for conversion to an image I
1
u
with the corrected position from the image I
1
. The conversion parameter is obtained in a least-squares method such that a difference r=I
1
(p)−I
1
u
(p+u) between a luminance value I
1
(p) of a point p in the image I
1
and a luminance value I
1
u
(p+u) of a point p+u in the image I
1
u
corresponding to the point p is minimized entirely on the image. The obtained parameter is used as the position correction parameter &thgr;
u
.
Moreover, the distortion correction parameter &thgr;
d
is a parameter for conversion to the image I
i
u
from the distorted image I
1
ud
. The conversion parameter is obtained in the least-squares method such that a difference r=I
2
(p)−I
1
u
(f(p)) between a luminance value I
2
(p) of the point p in the image I
2
and a luminance value I
1
u
(f(p)) of a point f(p) in the image I
1
u
corresponding to the point p is minimized entirely on the image. The obtained parameter is used as the distortion correction parameter &thgr;
d
.
Furthermore, in the image correcting step (D), the obtained distortion correction parameter &thgr;
d
is used to correct the image taken by the camera.
That is, as shown in
FIG. 1
, a position in the photographed image I
2
in which the original image I
1
is projected is not known. Therefore, two stages are performed in order to obtain the distorted image I
1
ud
. That is, first the position corrected image I
1
u
is obtained from the image I
1
, subsequently the image I
1
u
is distorted and the distorted image I
1
ud
is obtained.
First Stage
First, the parameter &thgr;
u
for conversion to the image I
1
u
from the image I
1
is obtained. This does not include any internal parameter. The point in I
1
u
corresponding to the point p in the image I
1
deviates by u and is represented by p+u. Here, u changes with p and &thgr;
u
. When the image I
1
exactly equals with the photographed image I
2
, the luminance value I
1
(p) in p has to be equal to the luminance value I
2
(p+u) in p+u. That is, the luminance difference r=I
1
(p)−I
2
(p+u) in each point has to be 0. An evaluation function &Sgr;r
2
is obtained by summing squared differences for all the points, and the parameter &thgr;
u
is automatically obtained by repeating calculations such that the evaluation function is minimized.
Second Stage
Subsequently, the parameter &thgr;
d
for conversion to the image I
1
u
from the distorted image I
1
ud
is obtained. This is the internal parameter such as a distortion coefficient. This stage is similar to the first stage, but instead of the conversion to the distorted image I
1
ud
from the image I
1
u
, a reverse conversion to the image I
1
u
from the distorted image I
1
ud
is considered.
The point in image I
1
u
corresponding to the point p in the photographed image I
2
is represented by f(p). Here, f( ) changes with p and &thgr;
d
.
When the photographed image I
Ohnishi Noboru
Tamaki Toru
Yamamura Tsuyoshi
Christensen Andrew
Griffin & Szipl, P.C.
Riken
Tran Nhan
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