Acquisition algorithm development is complete!

All development related to target centroid finding is complete, with a few setbacks, the foremost of which being that Fine acq. translated nicely from a great heap of nested code into a nice warm dumpster fire.  

I had to hedge my bets on a backup algorithm called black acq. which serves the same purpose, but requires a black dot in the center of the target where fine acq. could work with or without the dot (if it worked at all, which it doesn't).

This marks the much-anticipated end of the computer vision/image processing phase of the project, which is nice.  The next step is vector transformation, which should be easy-peasy compared to the image processing portion.  I actually had most of that math worked out on paper with the intention of passing the coarse acq. results to it, but I could not narrow down the possible attitude past two distinct solution-spaces without more precise target centroid data.

The green dots on each target are the results of coarse acq., the blue dots are the results of black acq.  Black acq. shares a more limited version of fine acq.'s designed ability to narrow in even further on the centroid based on its input arguments, at the cost of valuable processing time.  In other words, if it is deemed necessary the target centroids can be placed with more precision than they are in this picture.