Note
Go to the end to download the full example code.
2.6.8.19. Finding edges with Sobel filtersΒΆ
The Sobel filter is one of the simplest way of finding edges.
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
rng = np.random.default_rng(27446968)
im = np.zeros((256, 256))
im[64:-64, 64:-64] = 1
im = sp.ndimage.rotate(im, 15, mode="constant")
im = sp.ndimage.gaussian_filter(im, 8)
sx = sp.ndimage.sobel(im, axis=0, mode="constant")
sy = sp.ndimage.sobel(im, axis=1, mode="constant")
sob = np.hypot(sx, sy)
plt.figure(figsize=(16, 5))
plt.subplot(141)
plt.imshow(im, cmap="gray")
plt.axis("off")
plt.title("square", fontsize=20)
plt.subplot(142)
plt.imshow(sx)
plt.axis("off")
plt.title("Sobel (x direction)", fontsize=20)
plt.subplot(143)
plt.imshow(sob)
plt.axis("off")
plt.title("Sobel filter", fontsize=20)
im += 0.07 * rng.random(im.shape)
sx = sp.ndimage.sobel(im, axis=0, mode="constant")
sy = sp.ndimage.sobel(im, axis=1, mode="constant")
sob = np.hypot(sx, sy)
plt.subplot(144)
plt.imshow(sob)
plt.axis("off")
plt.title("Sobel for noisy image", fontsize=20)
plt.subplots_adjust(wspace=0.02, hspace=0.02, top=1, bottom=0, left=0, right=0.9)
plt.show()
Total running time of the script: (0 minutes 0.201 seconds)