Rename km_segmentation to slic. They have a PAMI paper now so I guess we should use their name.

doc/examples/plot_slic.py

@@ -6,12 +6,12 @@ import matplotlib.pyplot as plt
 import numpy as np
 
 from skimage.data import lena
-from skimage.segmentation import km_segmentation, visualize_boundaries
+from skimage.segmentation import slic, visualize_boundaries
 from skimage.util import img_as_float
 from skimage.color import rgb2lab
 
 img = img_as_float(lena()).copy("C")
-segments = km_segmentation(rgb2lab(img), ratio=10.0, n_segments=1000)
+segments = slic(rgb2lab(img), ratio=10.0, n_segments=1000)
 
 print("number of segments: %d" % len(np.unique(segments)))
 

skimage/segmentation/__init__.py

@@ -1,8 +1,8 @@
 from .random_walker_segmentation import random_walker
 from .felzenszwalb import felzenszwalb_segmentation
-from .km_segmentation import km_segmentation
+from .slic import slic
 from .quickshift import quickshift
 from .boundaries import find_boundaries, visualize_boundaries
 
 __all__ = [random_walker, quickshift, felzenszwalb_segmentation,
-    km_segmentation, find_boundaries, visualize_boundaries]
+    slic, find_boundaries, visualize_boundaries]

skimage/segmentation/setup.py

@@ -17,8 +17,8 @@ def configuration(parent_package='', top_path=None):
     cython(['quickshift.pyx'], working_path=base_path)
     config.add_extension('quickshift', sources=['quickshift.c'],
                          include_dirs=[get_numpy_include_dirs()])
-    cython(['km_segmentation.pyx'], working_path=base_path)
-    config.add_extension('km_segmentation', sources=['km_segmentation.c'],
+    cython(['slic.pyx'], working_path=base_path)
+    config.add_extension('slic', sources=['slic.c'],
                          include_dirs=[get_numpy_include_dirs()])
 
     return config

skimage/segmentation/slic.pyx

@@ -5,7 +5,7 @@ from scipy import ndimage
 from ..util import img_as_float
 
 
-def km_segmentation(image, n_segments=100, ratio=10., max_iter=10, sigma=1):
+def slic(image, n_segments=100, ratio=10., max_iter=10, sigma=1):
     """Segments image using k-means clustering in Color-(x,y) space.
 
     Parameters
@@ -32,9 +32,9 @@ def km_segmentation(image, n_segments=100, ratio=10., max_iter=10, sigma=1):
 
     References
     ----------
-    .. [1] Slic superpixels, Achanta, R. and Shaji, A. and Smith, K. and Lucchi,
-           A. and Fua, P. and Suesstrunk, S.
-           Technical Report 2010
+    .. [1] Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi,
+        Pascal Fua, and Sabine Süsstrunk, SLIC Superpixels Compared to
+        State-of-the-art Superpixel Methods, TPAMI, May 2012.
 
     """
     image = np.atleast_3d(image)