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 plentyof stray pixels picked up by the tracing software).
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 mathematicalrectangle, 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 Tuesday, December 6, 2022 at 10:52:35 AM UTC, Malcolm McLean wrote:plenty of stray pixels picked up by the tracing software).
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
rectangle, but it would be four clean almost straight curves, connected by four corners of almost ninety degreees.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
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.Would it help to assume that if the "curve" is close enough to a straight line, then it is meant to be one, and choose the best straight line that fits?
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).
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.
Malcolm McLean <malcolm.ar...@gmail.com> writes:
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).
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 easyHow is this going? I can't help, but I was hoping so see some
to pick out the real curve from the noise by eye, but harder to do it automatically.
interesting discussion as it seems both challenging and likely to have
been solved before (though possibly with constraints that don't match
your circumstances).
Whilst it works on the test set, the snag is that I had to fiddle with
in an ad hoc way to achieve this.
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 plentyof stray pixels picked up by the tracing software).
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 mathematicalrectangle, 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:
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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