Master Thesis - Fachbereich Informatik
Master Thesis - Fachbereich Informatik
Master Thesis - Fachbereich Informatik
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4.5. MEASURING POINT DETECTION 85<br />
(a)<br />
(b) (c)<br />
Figure 4.22: (a) Edge response of an angular oriented (transparent) tube edge. The characteristic<br />
peaks at the ends of transparent tube edges do not have to lie on one line perpendicular<br />
to the x-axis. The red line visualizes the slight angular orientation of the tube edge. (b) Example<br />
detection result with k = 1 orientations. (c) Corresponding result with k = 3 orientations.<br />
template. Figure 4.22(a) visualizes the edge response of a slightly angular tube edge of a<br />
transparent tube (left side). In such a situation no template will fit the edge perfectly. This<br />
can be critical if the edge contrast is poor. In this case, as mentioned before, the stronger<br />
weighting of the template ends helps to support a match at the real tube boundary instead<br />
of at a background edge. With an angular tube edge, a symmetric template can not be<br />
shifted over the image in a way it matches both edge ends. Thus, the cross-correlation<br />
score is significantly smaller and the probability increases that a background edge yields<br />
a larger score.<br />
A little rotation of the template can overcome this problem. Therefore, the bank of<br />
templates is extended by k − 1 rotated versions of each template. It turned out that it is<br />
sufficient to rotate each template by ±2 degrees to cover the range of expected deviations<br />
from the ideal symmetric model. Thus, k = 3 has been used throughout the experiments.<br />
It is assumed that larger angular deviations can not occur due to the guide bars.<br />
Model Knowledge Optimization The number of templates to be checked each time on<br />
the left and right side increases with the number of rotations. Instead of 2 × 10 templates