Finding edges with Sobel filters

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

../../../_images/plot_find_edges_1.png

Python ソースコード: plot_find_edges.py

import numpy as np

from scipy import ndimage

import matplotlib.pyplot as plt



im = np.zeros((256, 256))

im[64:-64, 64:-64] = 1



im = ndimage.rotate(im, 15, mode='constant')

im = ndimage.gaussian_filter(im, 8)



sx = ndimage.sobel(im, axis=0, mode='constant')

sy = ndimage.sobel(im, axis=1, mode='constant')

sob = np.hypot(sx, sy)



plt.figure(figsize=(16, 5))

plt.subplot(141)

plt.imshow(im, cmap=plt.cm.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*np.random.random(im.shape)



sx = ndimage.sobel(im, axis=0, mode='constant')

sy = 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 example: 0.28 seconds ( 0 minutes 0.28 seconds)