Master Thesis - Fachbereich Informatik
Master Thesis - Fachbereich Informatik
Master Thesis - Fachbereich Informatik
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4.3. CAMERA CALIBRATION 59<br />
4.2.7. Background Pattern<br />
As introduced in Section 3.3, the measuring area is illuminated by a back light setup below<br />
the conveyor belt. This setup emphasizes the structure of the belt which can be seen as a<br />
characteristic pattern in the image. This pattern may differ between different belt types.<br />
Depending on the light intensity it is possible to eliminate the background completely. If<br />
the light source is bright enough, the background appears uniform white even with a short<br />
shutter. For black tubes such an overexposed image would lead to an almost binary image.<br />
Transparent tubes, however, do also disappear under too bright illumination. Hence, there<br />
will be always a certain amount of background structure visible in the image in practice.<br />
The strength of the background pattern increases with lower light intensity.<br />
In the following, it is generally assumed that the illumination is adjusted to allow for<br />
distinguishing between a tube edge and edges in the background. Larger amounts of dirt<br />
or other particles than heat shrink tubes on the conveyor must be prevented.<br />
4.3. Camera Calibration<br />
In the previous section several assumptions regarding the camera position and the image<br />
content have been presented. With respect to accurate measurements it is important that<br />
an object is imaged as reliably as possible, this means, straight lines should appear straight<br />
and not curved in the image, parallelism should be preserved, and objects of the same size<br />
should be mapped to the same size in the image. Unfortunately, the later properties do<br />
not hold in the perspective camera model as introduced before. However, under certain<br />
constraintsitispossibletominimizetheperspectiveeffects.<br />
If the internal camera parameters are known including the radial and tangential distortion<br />
coefficients, it is possible to compute an undistorted version of an image. After<br />
undistorting, straight lines in the world will appear as straight lines in the image. Furthermore,<br />
if one can arrange the camera in way that objects of equal size are projected<br />
onto the same size in the image within the camera’s field of view at a constant depth, one<br />
can assume that the image plane is approximately parallel to the conveyor.<br />
In the following the calibration method used to receive the intrinsic camera parameters<br />
as well as a method to arrange the camera in a way that perspective effects are minimized<br />
is presented.<br />
4.3.1. Compensating Radial Distortion<br />
To compensate for the radial distortion of an optical system, one needs to compute the<br />
intrinsic camera parameters. Since the intrinsic parameters can be assumed to be constant<br />
if the focal length is not changed, the calibration procedure does not have to be repeated<br />
every time the system is started and therefore can be precomputed offline.<br />
The common Camera Calibration Toolbox for Matlab of Jean-Yves Bouguet [9] is used<br />
for this purpose. It is closely related to the calibration method proposed in [74] and [31].<br />
The calibration pattern required in this method is a planar chessboard of known grid size.<br />
The calibration procedure has to be performed for each lens separately. The camera is<br />
placed at a working distance of approximately 250mm over the measuring area with a<br />
16mm fix-focal lens. It is adjusted to bring tubes with a diameter of 8mm at this distance<br />
intofocus(inthemeasuringplaneΠM).