ImagePro>Re: skeletonisation and object definition

["Glenn Weigel" <GWeigel[at]paprican.ca>]

Thanks very much for the help, Kevin.

With respect to your suggestions on skeletonisation, is there also some way
of ensuring that the thinning process yields a contiguous skeleton (given
we're starting with a closed-loop object)? I seem to mostly end up with a
series of non-contiguous line segments - which don't survive pruning as you
pointed out.


Thanks again,

Glenn


Pulp and Paper Research Institute of Canada
3800 Wesbrook Mall
Vancouver, British Columbia
V6S 2L9

(604) 222-3200




                                                                                                                              
                    "Kevin Ryan"                                                                                              
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Some excellent questions here; I hope I can help out a bit.

The various branches on your washer represent small deviations along the
edges of your washer. The thinning filter will represent a single pixel
'bump' along the edge of an object with a branch running to that bump as a
skeleton support.

To minimize this you can perform an opening or a closing on the binary
object image prior to thinning. This will greatly smooth the outline and
remove a lot of the branches.

Once you have thinned your object (assuming that it is a closed loop of
some
sort) you can prune the skeleton to remove the little branches. Note that
this does not work for linear objects! If your thinned object is a line,
rather than a loop, pruning may remove it entirely. Optionally, you can use
the 'reduce' filter, which is a pruning filter that leaves single point
objects.


To segment on edges rather than on intensities:

- Create a secondary image that is an edge filtered version of your
original. For example, duplicate your image and perform a Sobel filter on
it.
- Segment on the edges.
- Save the outline to a temporary file.
- Load the outline on your original image to apply edge filtered
thresholding to the original.

I do this kind of segmentation all the time based on derived images: edges
(Sobel, Laplacian), textures (variance, median), etc. It's a very useful
generalized technique.

-- Kevin Ryan
kevin@mediacy.com
Sr. Project Manager



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