10.grey_scal_dilation_using_to_remove_noise.py

import numpy as np
from scipy import ndimage
import matplotlib.pyplot as plt

im = np.zeros((64, 64))
np.random.seed(2)

x, y = (63*np.random.random((2, 8))).astype(np.int)
im[x, y] = np.arange(8)
# print(im[x,y])
bigger_points = ndimage.grey_dilation(im, size=(5, 5), structure=np.ones((5, 5)))

square = np.zeros((16, 16))
square[4:-4, 4:-4] = 1
dist = ndimage.distance_transform_bf(square)
dilate_dist = ndimage.grey_dilation(dist, size=(3, 3), \
        structure=np.ones((3, 3)))

plt.figure(figsize=(12.5, 3))
plt.subplot(141)
plt.imshow(im, interpolation='nearest', cmap=plt.cm.nipy_spectral)
plt.axis('off')
plt.subplot(142)
plt.imshow(bigger_points, interpolation='nearest', cmap=plt.cm.nipy_spectral)
plt.axis('off')
plt.subplot(143)
plt.imshow(dist, interpolation='nearest', cmap=plt.cm.nipy_spectral)
plt.axis('off')
plt.subplot(144)
plt.imshow(dilate_dist, interpolation='nearest', cmap=plt.cm.nipy_spectral)
plt.axis('off')

plt.subplots_adjust(wspace=0, hspace=0.02, top=0.99, bottom=0.01, left=0.01, right=0.99)
plt.show()


# el = ndimage.generate_binary_structure(2, 1)
# print(el)
# intmatrix = el.astype(np.int)
# # print(intmatrix)


# a = np.zeros((7,7), dtype=np.int)
# a[3:4, 3:4] = 1
# print(a)
# binmat = ndimage.binary_erosion(a).astype(a.dtype)
# print(binmat)
# #Erosion removes objects smaller than the structure
# print(ndimage.binary_erosion(a, structure=np.ones((5,5))).astype(a.dtype))
# # print('\n',newmat)
# # ndimage.binary_

# # binary dilation
# print('\n',ndimage.binary_dilation(a).astype(a.dtype))