3.3.9.8. Labelling connected components of an imageΒΆ

This example shows how to label connected components of a binary image, using the dedicated skimage.measure.label function.

../../../_images/sphx_glr_plot_labels_001.png
from skimage import measure
from skimage import filters
import matplotlib.pyplot as plt
import numpy as np
n = 12
l = 256
np.random.seed(1)
im = np.zeros((l, l))
points = l * np.random.random((2, n ** 2))
im[(points[0]).astype(np.int), (points[1]).astype(np.int)] = 1
im = filters.gaussian_filter(im, sigma= l / (4. * n))
blobs = im > 0.7 * im.mean()
all_labels = measure.label(blobs)
blobs_labels = measure.label(blobs, background=0)
plt.figure(figsize=(9, 3.5))
plt.subplot(131)
plt.imshow(blobs, cmap='gray')
plt.axis('off')
plt.subplot(132)
plt.imshow(all_labels, cmap='spectral')
plt.axis('off')
plt.subplot(133)
plt.imshow(blobs_labels, cmap='spectral')
plt.axis('off')
plt.tight_layout()
plt.show()

Total running time of the script: ( 0 minutes 0.173 seconds)

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