skeletonize MS ticket 5854

gistfile1.txt

2021-02-23

Some experiments with skeletonize function

I have extracted three test data sets from three different sources

A 1:250K data set with 6 lakes from the Swedish topographic map (Swedish National Landsurvey)
A 1:1M data set with the same lakes from the European EGM-2019 data (EuroGraphics
The chosen lakes are close to my hometown where I grew up.
Text labels that are associated with polygons 1:250K topo map from Norway. (Kartverket)

All three data sets have open licence.

Some observations:

The skeleton function works very well with the simple case to place the text in the Norwegian text boxes.  
This is one use case for me right now, where this function would be very useful.

The Swedish lakes might be an extreme use case.  It works ok I think for four of the lakes.
The lake in the lower right corner might be unusual since it has this big island inside the lake.
When I compare the same lakes between the 250K and 1M data sets, I can see that all small islands in the 250K 
introduce complexity for the algorithm.  Maybe I should try and do some filtering and 
remove small islands when requesting the data. 
(I have to find a way to do that on the fly).

Well this was just some initial testing and setting up a test environment for myself required some thoughts.  
Hopefully I can start to understand the actual algorithm now. 

Norway_label.png

test_250K_s3.png

ticket-5854-skeletonize-lars.zip