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Oct 01, 2015, 11:08 PM
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Super chroma key testing

Testing continued to try to improve the algorithm & reduce the computation requirements. On some test videos, the algorithm successfully tracked over 99% of the frames. It was still a game of chance, with the threshold, search radius, maximum offset distance, & edge kernel size just happening to be the right values. More difficult lighting naturally degraded the results.

Camera noise contributed to variability even when the position didn't change. It would benefit from a high frame rate. Smaller frame size degraded results. The computational requirements are still way beyond what can be reasonably done on the vehicle.

Normalizing the YUV channels subjectively improved results. A false color image with the normalized channels has a priori information about the dynamic range which wasn't available when the camera took the image, but it inuitively should need the dynamic range of the color channels to be the same as reality.

It didn't work at all when either converted to RGB or using luminance only. It did best with all YUV channels.

It became possible to estimate the center of the path from the 2 sides. Tracking the center would be still more robust than tracking a side.
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