-After the Sensors Team relayed that they were now attaching something to the can in order to measure the change position, I decided to simply stick with the Canny Edge algorithm and implement something similar to what I had in my previous testing. The images in Figure \ref{canny_demo} shows the progression of the image through the algorithm. Figure \ref{canny_demo} A shows the original image, whereas \ref{canny_demo}B shows the blurred (with a BLUR value of 5) gray scale image. Whereas Figure \ref{canny_demo}C shows the image after going through the Canny Edge algorithm with a low threshold of 35. Figures \ref{canny_demo}D and \ref{canny_demo}E both have the same input image, however different input values. It can be seen how tweaking the values can remove outliers, as Figure \ref{canny_demo}E is skewed to the right due to the outliers. From Figure \ref{canny_demo}F it can be seen that despite there being no points in the edge in the top half of the image, the edge has still been accurately determined.
+After the Sensors Team relayed that they were now attaching something to the can in order to measure the change position, we decided to simply stick with the Canny Edge algorithm and implement something similar to what we had in my previous testing. The images in Figure \ref{canny_demo} shows the progression of the image through the algorithm. Figure \ref{canny_demo}A shows the original image, whereas \ref{canny_demo}B shows the blurred (with a BLUR value of 9) gray scale image. Whereas Figure \ref{canny_demo}C shows the image after going through the Canny Edge algorithm with a low threshold of 35 and the location of the determined edge superimposed on top.
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+Figures \ref{canny_demo}D, \ref{canny_demo}E and \ref{canny_demo}F all have the same input image (however different to \ref{canny_demo}A). Figure \ref{canny_demo}D had a blur of 5 and a low threshold value of 40, \ref{canny_demo}E had a blur of 9 and a low threshold value of 35, and \ref{canny_demo}F had a blur of 7 and a low threshold of 36. It can be seen how tweaking the values can remove outliers, as Figure \ref{canny_demo}D is skewed to the right due to theincreased number of outliers. From Figure \ref{canny_demo}E it can be seen that despite there being no points in the edge in the top half of the image, the edge has still been accurately determined.