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7.2.
Difference of Gaussians
This filter does edge detection using the
so-called “Difference of Gaussians”
algorithm, which works by performing two different Gaussian blurs on the
image, with a different blurring radius for each, and subtracting them
to yield the result. This algorithm is very widely used in artificial
vision (maybe in biological vision as well!), and is pretty fast because
there are very efficient methods for doing Gaussian blurs. The most
important parameters are the blurring radii for the two Gaussian blurs.
It is probably easiest to set them using the preview, but it may help to
know that increasing the smaller radius tends to give thicker-appearing
edges, and decreasing the larger radius tends to increase the
“threshold”
for recognizing something as an edge. In most cases you will get nicer
results if Radius 2 is smaller than Radius 1, but nothing prevents you
from reversing them, and in situations where you have a light figure on
the dark background, reversing them may actually improve the result.
7.2.2.
Activate the filter
You can find this filter through
→ →
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Smoothing parameters
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Radius 1 and Radius 2 are the blurring radii for the two Gaussian
blurs. The only constraints on them is that they cannot be equal,
or else the result will be a blank image. If you want to produce
something that looks like a sketch, in most cases setting Radius 2
smaller than Radius 1 will give better results.
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Normalize
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Checking this box causes the brightness range in the result to be
stretched as much as possible, increasing contrast. Note that in
the preview, only the part of the image that is shown is taken
into account, so with Normalize
checked the preview is not completely accurate. (It is accurate
except in terms of global contrast, though.)
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Invert
-
Checking this box inverts the result, so that you see dark edges
on a white background, giving something that looks more like a
drawing.
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