.. _example_cluster_plot_lena_segmentation.py: ========================================= Segmenting the picture of Lena in regions ========================================= This example uses :ref:`spectral_clustering` on a graph created from voxel-to-voxel difference on an image to break this image into multiple partly-homogeneous regions. This procedure (spectral clustering on an image) is an efficient approximate solution for finding normalized graph cuts. There are two options to assign labels: * with 'kmeans' spectral clustering will cluster samples in the embedding space using a kmeans algorithm * whereas 'discrete' will iteratively search for the closest partition space to the embedding space. .. rst-class:: horizontal * .. image:: images/plot_lena_segmentation_001.png :scale: 47 * .. image:: images/plot_lena_segmentation_002.png :scale: 47 **Python source code:** :download:`plot_lena_segmentation.py ` .. literalinclude:: plot_lena_segmentation.py :lines: 20- **Total running time of the example:** 60.48 seconds ( 1 minutes 0.48 seconds)