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// Computer Vision
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System to detect objects based on object features. 


To match objects three criteria had to be met:
	1. Matching # of holes
	2. Aspect Ratio within +/-10%
	3. Roundness Ratio within +/-10%


I chose 800 rho bins and 180 such that I would end up with a range of -800:+800 rho values and -180:+180 degrees. 


Standard threshold for Hough: simply filtered anything that not within the 90th, 30th & 40th percentile for hough1/2/3 respectively. 

Line Segments:
The key to my algorithm was to compute the line and then check whether all the points on the line had been detected by the edge detector. If a point was present in the edge detected image that meant that i'd include it as a point in my line. In a second step, once points were added to line segment matrices to be plotted; I would keep track of the distances between the points. If the distance between points passed a certain threshold, I'd start a new line segment.