I'm working on a problem where a user enters a degraded, wiggly curve (it's actually created by tracing software from what might have been once a rectangle, for example, but has been physically printed, then scanned, and so on, so that there are plenty of stray pixels picked up by the tracing software).--- Synchronet 3.20a-Linux NewsLink 1.114
So basically what I want to do is sample the curve at a fairly low resolution, then re-fit it, to get rid of the noise. However I want to retain the genuine sharp corners. So in the rectangle case, the desired output wouldn't be a mathematical rectangle, but it would be four clean almost straight curves, connected by four corners of almost ninety degreees.
The curve tends to go back on itself. It's like a coastline. It's easy to pick out the real curve from the noise by eye, but harder to do it automatically.
On Monday, 12 December 2022 at 13:34:30 UTC+1, Malcolm McLean wrote:--- Synchronet 3.20a-Linux NewsLink 1.114
Whilst it works on the test set, the snag is that I had to fiddle withNext step is Machine Learning (learning the parameters)...
in an ad hoc way to achieve this.
Julio
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