Posted by
Michael Schmid on
URL: http://imagej.273.s1.nabble.com/Delaunay-Voronoi-intersected-with-boundary-tp5016272p5016283.html
Hi Angelika,
if you don't need it too accurate, you can try with the simple ImageJ
Voronoi approximation. Smething like this:
//convert to single points by 'Find Maxima',
//unless you are interested in the distance between the outlines
run("Find Maxima...", "noise=0 output=[Single Points] light");
run("Voronoi");
setThreshold(0, 0);
run("Create Selection");
run("Set...", "value=255");
run("Select None");
run("Grays"); //makes sure we have a non-inverting LUT
run("Find Maxima...", "noise=2 output=[Single Points] exclude light");
run("Create Selection");
run("Select None"); //gets selection into undo buffer
close();
run("Restore Selection"); //transfer selection to Voronoi image
run("Histogram");
The histogram will roughly be the distance distribution in units of
twice the pixel size.
Michael
________________________________________________________________
On 2016-04-29 17:13, schiriki wrote:
> Hello Kenneth,
>
> thank you for your help. I attached an image to better explain the problem.
> Since in my datasets all or almost all particles will be near the domain
> border, the problem arises a lot.
> The picture shows the particles, the domain boundary (close to a rectangle)
> and the Voronio as computed by imageJ. If I want to use Delaunay to
> determine distances, also e.g. the particles marked with red or those marked
> with blue will be considered neighbors, eventhough their Voronoi domains do
> not share an edge inside the domain.
>
> <
http://imagej.1557.x6.nabble.com/file/n5016282/example.jpg>
>
> For a single image I could maybe mirror the particles along the border to
> enforce real Voronoi separation, but I have a lot of data, so doing it by
> hand is not an option.
>
> Thank you,
> Angelika
>
>
>
> --
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http://imagej.1557.x6.nabble.com/Delaunay-Voronoi-intersected-with-boundary-tp5016272p5016282.html> Sent from the ImageJ mailing list archive at Nabble.com.
>
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