Add funct to remove small connected compononents

skimage/morphology/__init__.py

@@ -7,3 +7,4 @@ from .watershed import watershed, is_local_maximum
 from ._skeletonize import skeletonize, medial_axis
 from .convex_hull import convex_hull_image
 from .greyreconstruct import reconstruction
+from .misc import remove_small_connected_components

skimage/morphology/misc.py

@@ -0,0 +1,40 @@
+import numpy as np
+import scipy.ndimage as nd
+
+def remove_small_connected_components(ar, min_size=64, 
+                                            connectivity=1, in_place=False):
+    """Remove connected components smaller than the specified size.
+
+    Parameters
+    ----------
+    ar : ndarray (arbitrary shape, int or bool type)
+        The array containing the connected components of interest.
+    min_size : int, optional (default: 64)
+        The smallest allowable connected component size.
+    connectivity : int, {1, 2, ..., ar.ndim}, optional (default: 1)
+        The connectivity defining the neighborhood of a pixel.
+    in_place : bool, optional (default: False)
+        If `True`, remove the connected components in the input array itself.
+        Otherwise, make a copy.
+
+    Returns
+    -------
+    out : ndarray, same shape and type as input `ar`
+        The input array with small connected components removed.
+    """
+    structuring_element = nd.generate_binary_structure(ar.ndim, connectivity)
+    if in_place:
+        out = ar
+    else:
+        out = ar.copy()
+    if min_size == 0: # shortcut for efficiency
+        return out
+    if out.dtype == bool:
+        ccs = nd.label(ar, structuring_element)[0]
+    else:
+        ccs = out
+    component_sizes = np.bincount(ccs.ravel())
+    too_small = component_sizes < min_size
+    too_small_mask = too_small[ccs]
+    out[too_small_mask] = 0
+    return out