2.6.8.19. Finding edges with Sobel filters

The Sobel filter is one of the simplest way of finding edges.

square, Sobel (x direction), Sobel filter, Sobel for noisy image
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 0.198 seconds)

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