If two endpoints are closer than this value, they are made to be
Corner Always Threshold:
If the angle defined by a point and its predecessors
and successors is smaller than this, it is a corner,
even if it is within Corner Surround
pixels of a point with a smaller angle.
Number of points to consider when determining if a
point is a corner or not.
If a point, its predecessors, and its successors
define an angle smaller than this, it is a corner.
Amount of error at which a fitted spline
is unacceptable. If any pixel is further away than this from the
fitted curve, the algorithm tries again.
Filter Alternative Surround:
A second number of adjacent points to consider
If the angles between the vectors produced by
Filter Surround and
Filter Alternative Surround
points differ by more than this, use the one from
Filter Alternative Surround.
Filter Iteration Count:
The number of times to smooth the original data points.
Increasing this number dramatically, to 50 or
so, can produce vastly better results. But if
any points that “should” be corners aren't found,
the curve goes wild around that point.
Filter Percent: To produce the new point,
use the old point plus this times the neighbors.
Filter Secondary Surround:
Number of adjacent points to consider if
Filter Surround points defines a
Number of adjacent points to consider when filtering.
This check box says whether or not to remove “knee”
points after finding the outline.
Line Reversion Threshold:
If a spline is closer to a straight line than this value,
it remains a straight line, even if it would otherwise
be changed back to a curve. This is weighted by the
square of the curve length, to make shorter curves
more likely to be reverted.
How many pixels (on the average) a spline can
diverge from the line determined by its endpoints
before it is changed to a straight line.
If reparameterization doesn't improve the fit by this
much percent, the algorithm stops doing it.
Amount of error at which it is pointless to reparameterize.
This happens, for example, when the algorithm is trying to fit the
outline of the outside of an “O” with a single spline.
The initial fit is not good enough for the Newton-Raphson
iteration to improve it. It may be that it would be better
to detect the cases where the algorithm didn't find any corners.
Percentage of the curve away from the worst point
to look for a better place to subdivide.
Number of points to consider when deciding whether
a given point is a better place to subdivide.
How many pixels a point can diverge from a straight
line and still be considered a better place to
Number of points to look at on either side of a
point when computing the approximation to the
tangent at that point.