注意
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扩展分割标签,无重叠#
给定几个由标签图像表示的连通组件,可以使用 skimage.segmentation.expand_labels()
将这些连通组件扩展到背景区域。与 skimage.morphology.dilation()
相比,此方法不会让连通组件扩展到标签编号较低的相邻连通组件。
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()
脚本的总运行时间:(0 分 0.569 秒)