Python 相当于灰度的 Matlab 函数 'imfill'？

Question

是否有使用OpenCV或scikit-image的实现相当于Matlab的灰度图像imfill函数(即灰度孔填充)？

请参阅以下示例链接中的灰度填充部分 (I2= imfill(I)) matlab_imfill .或者看图片:matlab_tire_ex

这是示例中轮胎图片的链接

我一直在尝试使用 scipy.ndimage.grey_closing 函数并改变大小参数来复制 Matlab 输出，但没有成功。

我正在使用 Python 3.5。

Answer 1

Matlab infill() 依次使用函数 IM = imreconstruct(marker,mask)

Scikit-image 有类似的功能... skimage.morphology.reconstruction(seed, mask, method='dilation', selem=None, offset=None)

算法详见Soille, P.，形态图像分析:原理和应用，Springer-Verlag，1999，第 208-209 页。第 6.3.7 节“填充孔”

import numpy as np
from skimage.morphology import reconstruction
import matplotlib.pyplot as plt
from skimage.io import imread, imsave


# Use the matlab reference Soille, P., Morphological Image Analysis: Principles and Applications, Springer-Verlag, 1999, pp. 208-209.
#  6.3.7  Fillhole
# The holes of a binary image correspond to the set of its regional minima which
# are  not  connected  to  the image  border.  This  definition  holds  for  grey scale
# images.  Hence,  filling  the holes of a  grey scale image comes down  to remove
# all  minima  which  are  not  connected  to  the  image  border, or,  equivalently,
# impose  the  set  of minima  which  are  connected  to  the  image  border.  The
# marker image 1m  used  in  the morphological reconstruction by erosion is set
# to the maximum image value except along its border where the values of the
# original image are kept:

img = imread("tyre.jpg")

seed = np.ones_like(img)*255
img[ : ,0] = 0
img[ : ,-1] = 0
img[ 0 ,:] = 0
img[ -1 ,:] = 0
seed[ : ,0] = 0
seed[ : ,-1] = 0
seed[ 0 ,:] = 0
seed[ -1 ,:] = 0


fill = reconstruction(seed, img, method='erosion')

f, (ax0, ax1) = plt.subplots(1, 2,
    subplot_kw={'xticks': [], 'yticks': []},
    figsize=(12, 8))
ax0.imshow(img)
ax1.imshow(fill)
plt.show()

Link to tyre image and filled image