# Processing line scanner data

I have a line scanner output that is scanning the geometry of a surface. Typically the output looks something like this:

Where the x and y axis refers to the coordinate system in mm. (ignore the red dots). This data is essentially a 2d point cloud.

So what i am trying to achieve is to detect the corner points of this scan. I try to start using image processing techniques, for example using a harris corner detector.

However, the issue with this is that this data has a resolution of up to 0.01um vs a possible area size of 140mm X 100mm of all possible data points. If i were to convert this to 2d image, it would be a very large file, with most of the pixels being empty.

My question is that is there a better way to go about processing this type of data; or is there an alternative way to apply techniques such as the harris corner without resorting to conversion into an image.

• Just to be clear - the data is the form of [x,y] coordinates, but neither the x or y coordinates are evenly spaced? – geometrikal Sep 2 '15 at 4:45
• @geometrikal The coordinates are evenly spaced; only the drawing of the axis for display is not. – John Tan Sep 2 '15 at 5:12
• Can you just treat it as a 1-D signal then, and look for jumps in $y$? – geometrikal Sep 2 '15 at 5:32
• Where are those "corner points" that you want to find ? Please be explicit. – Yves Daoust Sep 3 '15 at 12:35
• @geometrikal Yes I have tried that (looking for the 2nd derivatives), but the jumps are very noisy, and give a lot of false readings. In fact, the red dots on the image indicate mark out the boundaries where the 2nd derivatives are above a certain threshold. – John Tan Sep 4 '15 at 1:51