Submitted version of the thesis - Airlab, the Artificial Intelligence ...

64 Chapter 5. Vision
in a form that can be converted into the rules. The result of the color selection
script, with the original picture is shown in Figure 5.7.
(a) Mask to be Applied (b) Orginal Picture
Figure 5.7: The mask applied to the orginal picture.
The boundaries found for the object are converted into rules, that will
add or subtract the color from the RGB Cube. The rules are checked by
color selection program, provided with the ST software coming with the
camera. The script can be found in Appendix B.1 in Color Histogram Calculator.
Using both thecolor selecting program and an offline Matlab script,
we have been able to define the color in a more precise way, and improved
the results for object detection. But the results diverged as the lighting
conditions change in the environment. For example the laboratory where
we have performed tests is exposed to direct sunlight in the morning, while
in the afternoon it is not. We introduced different configurations for the
same color, to avoid the need for sampling of the previously defined color.
By controlling the color before each run manually and recalculating when
necessary resulted a stable solution to the problem.
5.3 Tracking
The final working configuration of the object detection is made by solving
the problems described previously. We can explain these in three titles.
First one is finding the correct color information. We start by disabling the
automatic whitebalanceandautomatic exposurecompensation. Thisallows
us to have the color as it is seen directly from the camera, by not adjusting