Master Thesis - Fachbereich Informatik

A. Profile Analysis Implementation Details
Details regarding the implementation of the profile analysis with a focus on performance
aspects are introduced in the following.
A.1. Global ROI
A simple, but very effective way to decrease the computational load is to restrict the image
processing to a certain region of interest (ROI). Following the assumption that parts of
the guide bars are visible in the images at the top and the bottom without containing
any information, the guide bars can be excluded from further processing and, thus, the
ROI lies in between these guide bars. The height of the ROI is given by the guide bar
distance which should be almost constant over the whole image since they are adjusted to
be parallel to the x-axis in the image. The ROI extends in horizontal direction over the
whole image width minus a certain offset at both sides. This offset is due to the fact that
the image distortion is maximal at the boundaries. The actual value of the offset depends
on the ability to overcome the distortion at measuring. If the measurements are accurate
even at the image boundaries, the offset tends against zero. In the following, the ROI
betweentheguidebarsisalsoreferredtoasglobal ROI.
Section 3.2 states it is possible to adapt the camera resolution to a user-defined size.
The reason why the image size is not adjusted to cover the global ROI exactly (by what it
becomes redundant) is a very practical one. First of all, the guide bars provide a valuable
clue in adjusting the field of view of the camera. In addition, smaller images mean less data
has to be transferred and consequentially a larger number of images can be transferred in
the same time. If the image size is too small, the actual frame rate exceeds the number of
frames that can be processed without skipping frames which should be avoided.
The extraction of the global ROI can be automated using a similar profile analysis
approach as used for tube localization but in vertical direction. Again several vertical
scan lines are used to build the profile. If there is no tube in the image (empty scene),
the guide bars can be detected clearly since the contrast between the bright conveyor belt
and the black guide bars is very strong. A smoothing step as used in horizontal direction
to overcome the background clutter is not necessary. This has the benefit that the two
strongest peaks in the profile describe the guide bar location quite accurate. The detection
of the global ROI has to be performed only once at an initialization step if assuming a static
setup of camera and conveyor that does not change over time. In future, it is thinkable
that everytime the state ’empty’ is detected, the ROI is reinitialized and compared with
the previous location. A difference indicates something changed with the setup and may
induce an alert or some specific reaction.
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