备注
单击 here 下载完整的示例代码或通过活页夹在浏览器中运行此示例
标记图像区域¶
此示例说明如何使用图像标签对图像进行分割。应用以下步骤:
用自动OTSU方法进行阈值分割
用二进制闭合闭合小孔
移除接触图像边框的瑕疵
测量图像区域以过滤小对象

import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from skimage import data
from skimage.filters import threshold_otsu
from skimage.segmentation import clear_border
from skimage.measure import label, regionprops
from skimage.morphology import closing, square
from skimage.color import label2rgb
image = data.coins()[50:-50, 50:-50]
# apply threshold
thresh = threshold_otsu(image)
bw = closing(image > thresh, square(3))
# remove artifacts connected to image border
cleared = clear_border(bw)
# label image regions
label_image = label(cleared)
# to make the background transparent, pass the value of `bg_label`,
# and leave `bg_color` as `None` and `kind` as `overlay`
image_label_overlay = label2rgb(label_image, image=image, bg_label=0)
fig, ax = plt.subplots(figsize=(10, 6))
ax.imshow(image_label_overlay)
for region in regionprops(label_image):
# take regions with large enough areas
if region.area >= 100:
# draw rectangle around segmented coins
minr, minc, maxr, maxc = region.bbox
rect = mpatches.Rectangle((minc, minr), maxc - minc, maxr - minr,
fill=False, edgecolor='red', linewidth=2)
ax.add_patch(rect)
ax.set_axis_off()
plt.tight_layout()
plt.show()
脚本的总运行时间: (0分0.190秒)