Better results with Canny/Hough for circular particles

Dan Farmer dfarmernv at gmail.com
Fri Dec 13 15:03:30 EST 2013


Hi Adam,

This can be the worst part of image processing, but I'm curious how
much you played with the parameters to Canny? You probably know this,
but canny already tries to close gaps (hysteresis thresholding). What
you want to do is try to lower the low_threshold parameter (values
above the high threshold value get initially labeled as edges, then it
looks for pixels that are connected to edge pixels and whose value is
> low_threshold to link the edges).

An easy/basic way to get rid of small fragments would be to start with
morphological erosion.

-Dan

On Fri, Dec 13, 2013 at 11:47 AM, Adam Hughes <hughesadam87 at gmail.com> wrote:
> Hi,
>
> I have several images of circular particles (see attached for an example)
> and I've been experimenting with automatic routines to find edges.
>
> I've found that with Canny, I can get really nice edges, but the edges are
> not always connected.  Thus, when I do fill-binary, many of my particles are
> not painted in due to slight breaks in the border returned by canny.  Is
> there an ideal way to fix this, either by connecting "almost" connected
> canny edges?  Additionally, what is the best way to filter out small
> fragments and/or non-circular edges?
>
> I've attached an image of the canny outlines; you can see that I obviously
> want to get rid some of the regions that aren't associated with any
> particles.  PS, the coloring of the outlines are based on the brightness of
> the image at that point underneath it, which has been hidden.  (Would be
> happy to share the function if anyone wants it).
>
> Lastly, I tried adapting the circular hough transform example:
>
> http://scikit-image.org/docs/dev/auto_examples/plot_circular_elliptical_hough_transform.html
>
> But struggled with setting it up, due to a naive understanding of the
> algorithm.  Given that my image has thousands of particles, but I know
> roughly the size distribution, would the circular hough transform be useful
> to me?
>
> Thanks
>
>
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