How can i find cycles in a skeleton image with python libraries?

Question

I have many skeletonized images like this:

How can i detect a cycle, a loop in the skeleton? Are there "special" functions that do this or should I implement it as a graph?

In case there is only the graph option, can the python graph library NetworkX can help me?

Answer 1

You can exploit the topology of the skeleton. A cycle will have no holes, so we can use scipy.ndimage to find any holes and compare. This isn't the fastest method, but it's extremely easy to code.

import scipy.misc, scipy.ndimage

# Read the image
img = scipy.misc.imread("Skel.png")

# Retain only the skeleton
img[img!=255] = 0
img = img.astype(bool)

# Fill the holes
img2 = scipy.ndimage.binary_fill_holes(img)

# Compare the two, an image without cycles will have no holes
print "Cycles in image: ", ~(img == img2).all()

# As a test break the cycles
img3 = img.copy()
img3[0:200, 0:200] = 0
img4 = scipy.ndimage.binary_fill_holes(img3)

# Compare the two, an image without cycles will have no holes
print "Cycles in image: ", ~(img3 == img4).all()

I've used your "B" picture as an example. The first two images are the original and the filled version which detects a cycle. In the second version, I've broken the cycle and nothing gets filled, thus the two images are the same.