mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-28 02:47:01 +08:00
Alexandre Fioravante de Siqueira
ce4a68f695
Solving space convex_hull + fixing local_otsu Solving space on censure
55 lines
1.5 KiB
Python
55 lines
1.5 KiB
Python
"""
|
|
===========
|
|
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.
|
|
|
|
In this example, we show how the input pixels (white) get filled in by the
|
|
convex hull (white and grey).
|
|
|
|
A good overview of the algorithm is given on `Steve Eddin's blog
|
|
<http://blogs.mathworks.com/steve/2011/10/04/binary-image-convex-hull-algorithm-notes/>`__.
|
|
|
|
"""
|
|
|
|
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
|
|
from skimage.morphology import convex_hull_image
|
|
|
|
image = np.array(
|
|
[[0, 0, 0, 0, 0, 0, 0, 0, 0],
|
|
[0, 0, 0, 0, 1, 0, 0, 0, 0],
|
|
[0, 0, 0, 1, 0, 1, 0, 0, 0],
|
|
[0, 0, 1, 0, 0, 0, 1, 0, 0],
|
|
[0, 1, 0, 0, 0, 0, 0, 1, 0],
|
|
[0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=float)
|
|
|
|
original_image = np.copy(image)
|
|
|
|
chull = convex_hull_image(image)
|
|
image[chull] += 1
|
|
|
|
# image is now:
|
|
# [[ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
|
|
# [ 0. 0. 0. 0. 2. 0. 0. 0. 0.]
|
|
# [ 0. 0. 0. 2. 1. 2. 0. 0. 0.]
|
|
# [ 0. 0. 2. 1. 1. 1. 2. 0. 0.]
|
|
# [ 0. 2. 1. 1. 1. 1. 1. 2. 0.]
|
|
# [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
|
|
|
|
fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(12, 4))
|
|
plt.tight_layout()
|
|
|
|
ax0.set_title('Original picture')
|
|
ax0.imshow(original_image, cmap=plt.cm.gray, interpolation='nearest')
|
|
ax0.set_xticks([]), ax0.set_yticks([])
|
|
|
|
ax1.set_title('Transformed picture')
|
|
ax1.imshow(image, cmap=plt.cm.gray, interpolation='nearest')
|
|
ax1.set_xticks([]), ax1.set_yticks([])
|
|
|
|
plt.show()
|