Clustering of an image by taking into account the spatial context of each pixel (besides its intensity)
h.benoudjit at gmail.com
Fri Nov 20 19:28:05 EST 2015
Thanks for your reponse.
What I'm looking for is a *spatial criteria* that encourages the *clustering
algorithm* (K-means or others) to group together similar *neighbouring
pixels* inside the same cluster. This will help avoid having persistent
noise inside a cluster.
Le vendredi 20 novembre 2015 13:20:15 UTC, Hakim Benoudjit a écrit :
> Is there a clustering algorithm implemented in *scikit-image *that
> perform the image clustering by taking into account the *spatial context *of
> the clustered pixel (its neighbourhood), besides its *pixel brightness*?
> For the time being, I'm clustering images by reshaping them as vectors of
> pixels intensities distributions, and then performing the *K-means *or *Gaussian
> mixture models* implemented in *scikit-learn*. But, I'm looking for a
> image clustering technique implemented (or could be implemented) in *scikit-image
> *that would consider the neighbourhood of a pixel when classifying it.
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