trim_saddle_points#

trim_saddle_points function is a filter which removes peaks that were mistakenly identified because they lie on a saddle or a ridge in the distance transform.

import numpy as np
import porespy as ps
import scipy.ndimage as spim
import matplotlib.pyplot as plt
import skimage
from edt import edt
ps.visualization.set_mpl_style()

dt#

The distance transform of a test image is detetmined using the edt method.

im = ps.generators.blobs(shape=[200, 200], blobiness=[2, .5], porosity=0.65)
dt = edt(im)

plt.figure(figsize=[6, 6]);
plt.axis(False);
plt.imshow(dt/im);
../../../_images/0c350a06329c8eaa3b72520a22d6c62696fb65e50369acc1816aab51f58ba90e.svg

peaks#

peaks is found using the find_peaks filter on the distance transform. Peaks that lie on a saddle or a ridge are removed.

peaks = ps.filters.find_peaks(dt, r_max=4)

x = ps.filters.trim_saddle_points(peaks=peaks, dt=dt)

fix, ax = plt.subplots(1, 2, figsize=[12, 12])
ax[0].axis(False)
ax[0].imshow(peaks/im)
ax[0].set_title('Before', fontdict={'fontsize': 18});
ax[1].axis(False)
ax[1].imshow(x/im);
ax[1].set_title('After', fontdict={'fontsize': 18});
../../../_images/1df344db8fbe68743a6f3a31265537cf4ac461c4322fa0da60b28f36e2bf1109.svg