I would like to generate a skeleton out of an image. The resulting output of the skeleton image has disconnected edges. 

import skimage

from skimage import data,io,filters

import numpy as np

import cv2

import matplotlib.pyplot as plt

from skimage.filters import threshold_adaptive,threshold_mean

from skimage.morphology import binary_dilation

from skimage import feature

from skimage.morphology import skeletonize_3d

imgfile = "Bagah.jpeg"

im = cv2.imread(imgfile)

image = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)

thresh = threshold_mean(image)

thresh = threshold_mean(thresh)

binary = image > thresh

#dilate = skimage.morphology.binary_dilation(binary)

gaussian = skimage.filters.gaussian(binary)

edges = filters.sobel(gaussian)

#dilate = feature.canny(edges)#binary,sigma=0)

skeleton = skeletonize_3d(gaussian)#binary)

fig, axes = plt.subplots(nrows=2,ncols=2, figsize=(8, 2))

ax = axes.ravel()

ax[0].imshow(gaussian, cmap=plt.cm.gray)

ax[0].set_title('gaussian')

ax[1].imshow(skeleton, cmap=plt.cm.gray)

ax[1].set_title('skeleton')

for a in ax:

    a.axis('off')

plt.show()

Please find the attachments of my input and output files.

I would like to translate this skeleton into a graph with nodes and edges.

Could someone suggest how to obtain a skeleton with connected edges?

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