sorry about the worse problem description! I tried this example http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_rag_mean_color.html#sphx-glr-auto-examples-segmentation-plot-rag-mean-color-py with different parameters for SLIC and graph.cut_threshold but none of them gave me satisfying results.
I attached the original image, the ImageJ SRM (Q=25) output and the RAG output (segmentation.slic(img, compactness=20; n_segments=400), graph.cut_threshold(labels1, g, 10))
The results are quite different, obviously I am doing something wrong. My aim is to segment each leaf separately. At the moment I am using felzenszwalb, which gives me quite reasonable results. However I would like to try everything possible and therefore I would appreciate some tips.
Thank you for the explanation of the algorithm, that was helpful.
Best regards, Stefanie
2016-11-15 1:51 GMT+01:00 Juan Nunez-Iglesias email@example.com:
Sorry, these responses should all be CCd to the list, so that others can benefit from the discussion — my bad for dropping that thread. Could you please:
- provide an example segmentation where skimage is doing worse than Fiji
- provide the script and parameter settings for both
Then we can help troubleshoot. I don’t know what you mean by the results “were very strange”, for example, so it’s hard to diagnose the problem. =)
Starting to merge directly from pixels, as the Fiji plugin does, is expensive and can be error prone. SLIC is a fast, initial pixel merging step, from which we can merge regions according to various criteria. With the right parameters, SLIC + RAG mean color agglomeration should give quite similar results to Fiji’s approach…
On 15 November 2016 at 2:39:45 am, Stefanie Lück (firstname.lastname@example.org) wrote:
thank you for your reply! I have seen and tested the RAG examples but I did not understand the SLIC step and the results were very strange... Is there any advantage? I am using SLIC anyway at the moment but the statistical region merging of ImageJ gives me better results.
2016-11-14 13:44 GMT+01:00 Juan Nunez-Iglesias email@example.com:
Have a look at skimage.future.graph! There are some relevant examples in the gallery, too:
The future.graph API is still experimental (that’s why it’s in “future”), so we really appreciate any feedback you have about it!
On 14 November 2016 at 8:21:12 pm, Stefanie Lück (firstname.lastname@example.org) wrote:
I am looking for a statistical region merging segmentation. Is there anything like this in skimage?
Thanks in advance, Stefanie _______________________________________________ scikit-image mailing list email@example.com https://mail.python.org/mailman/listinfo/scikit-image