8. Convex Hull

The convex hull of a binary image is the set of pixels included in the smallest convex polygon that surround all white pixels in the input.

A good overview of the algorithm is given on this blog.

import matplotlib.pyplot as plt

from skimage.morphology import convex_hull_image
from skimage import data, img_as_float
from skimage.util import invert

8.1. The original image is inverted as the object must be white

image = invert(data.horse())

8.2. Create a convex hull

chull = convex_hull_image(image)

8.3. Show the result

fig, axes = plt.subplots(1, 2, figsize=(8, 4))
ax = axes.ravel()

ax[0].set_title('Original picture')
ax[0].imshow(image, cmap=plt.cm.gray, interpolation='nearest')

ax[1].set_title('Transformed picture - convex hull')
ax[1].imshow(chull, cmap=plt.cm.gray, interpolation='nearest')


8.4. Showing the difference by fixing the pixel intensity on the convex hull

chull_diff = img_as_float(chull.copy())
chull_diff[image] = 2
fig, ax = plt.subplots()
ax.imshow(chull_diff, cmap=plt.cm.gray, interpolation='nearest')