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.
A first suggestion (without being sure to understand the question).

After sorting on X, try a line fit in a short sliding window (say 4 units long) and observe the correlation coefficient.

In smooth areas, the fit will be excellent. It will degrade at corners. Looking at the plot of the correlation, you should be able to set a suitable detection threshold.