Expand segmentation labels without overlap

Given several connected components represented by a label image, these connected components can be expanded into background regions using skimage.segmentation.expand_labels(). In contrast to skimage.morphology.dilation() this method will not let connected components expand into neighboring connected components with lower label number.

import matplotlib.pyplot as plt
import numpy as np
from skimage import data
from skimage.color import label2rgb
from skimage.filters import sobel
from skimage.measure import label
from skimage.segmentation import expand_labels, watershed

coins = data.coins()

# Make segmentation using edge-detection and watershed.
edges = sobel(coins)

# Identify some background and foreground pixels from the intensity values.
# These pixels are used as seeds for watershed.
markers = np.zeros_like(coins)
foreground, background = 1, 2
markers[coins < 30.0] = background
markers[coins > 150.0] = foreground

ws = watershed(edges, markers)
seg1 = label(ws == foreground)

expanded = expand_labels(seg1, distance=10)

# Show the segmentations.
fig, axes = plt.subplots(
    nrows=1,
    ncols=3,
    figsize=(9, 5),
    sharex=True,
    sharey=True,
)

axes[0].imshow(coins, cmap="Greys_r")
axes[0].set_title("Original")

color1 = label2rgb(seg1, image=coins, bg_label=0)
axes[1].imshow(color1)
axes[1].set_title("Sobel+Watershed")

color2 = label2rgb(expanded, image=coins, bg_label=0)
axes[2].imshow(color2)
axes[2].set_title("Expanded labels")

for a in axes:
    a.axis("off")
fig.tight_layout()
plt.show()