Hi,
I read the excellent article on centralskeleton at https://github.com/orbisgis/h2gis/wiki/3.1Extractcentralskeleton I've almost finished to write an implementation as a plugin for OpenJUMP. First, I want to thank you and to make sure that such an implementation does not infringe your license (anyway, I don't use h2GIS source code, but I relied on your excellent article). Here after are a few remarks about the article Step 1 : you noted "Epsilon is the merge distance of two close points", but it seems you use SimplifyPreservingTopology function which uses a DouglasPeucker which is not based on a minimum distance between consecutive points but on a maximum Hausdorff distance between the original and the simplified lines. Step 3 : you noted "Union and simplify skeleton". I can see a merge, but no simplification in the code. Also I wonder why you merge then explode. I think that edges get from the voronoi diagram are simple segments ending at intersections, so that merge/explode should do almost nothing (I did not test though, maybe I missed something) Step 4 : to perform the graph filtering, I used jgraphtsna. Any reason why you have implemented your own javanetworkanalyzer. Has javanetworkanalyzer other dependances than jgrapht ? Thanks and keep the good work ! 
After some more tests :
Step 3 : ok, I understood why merge is useful (after the elimination of voronoi edges intersecting the polygon boundary). After some tests on big polygons and big datasets, I realized that BetweennessCentrality is very cpu intensive and that it will probably not be able to process big datasets if I need to densify them up to 1 or 2 m. I would like to compare the method with simpler one like iterative elimination of ending edges, which should be faster. 
Administrator

In reply to this post by mukoki
Hi,
No problems, We are pleased to have been of any help for your work. Yes you are true, we will update the tutorial. I will let my colleague answer this question since I was not involved in the development of javanetworkanalyzer. Yes centrality computation is a cpu intensive operation. Best regards 
Administrator

Hi mukoki ;)
It's a pleasure to see you here. Thanks for the comments and feel free to use H2 network in OpenJump. We will fix the documentation asap. Please find more details about H2Network functions and the JNA library here : https://halshs.archivesouvertes.fr/halshs01133333 Cheers Erwan 
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