Clustering of an image by taking into account the spatial context of each pixel (besides its intensity)
emmanuelle.gouillart at nsup.org
Wed Nov 25 07:02:32 EST 2015
I think this example from the gallery does what you want: merging slic
On Wed, Nov 25, 2015 at 03:50:08AM -0800, Hakim Benoudjit wrote:
> Hi StÃ©fan,
> Thanks for the suggestion.
> I didn't try SLIC algorithm yet, but it seems to me (from the resulting images)
> that it segment images into small regions (superpixels) that could belong
> (visually) to the same object.
> In my case (ideally), these superpixels need to be merged afterwards.
> Do you have an idea on how to achieve the subsequent merging?
> Le mercredi 25 novembre 2015 02:21:00 UTC, stefanv a Ã©critÂ :
> On 2015-11-24 01:47:00, Hakim Benoudjit <h.ben... at gmail.com> wrote:
> > Thanks Juan, I think you're right.
> > I might have to read the paper on SLIC algorithm to understand how to
> > the "compactness" parameter.
> You can also use SLIC to label the image, and then compute features of
> each SLIC region. Â Or perhaps that is what is being suggested already, I
> wasn't sure.
More information about the scikit-image