Refactor corner detection example

This commit is contained in:
Johannes Schönberger
2012-09-16 15:39:25 +02:00
parent c1f9336c2a
commit f95e936696
2 changed files with 38 additions and 42 deletions
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"""
================
Corner detection
================
Detect corner points using the Harris corner detector and determine subpixel
position of corners.
.. [1] http://en.wikipedia.org/wiki/Corner_detection
.. [2] http://en.wikipedia.org/wiki/Interest_point_detection
"""
import numpy as np
from matplotlib import pyplot as plt
from skimage import data
from skimage.feature import corner_harris, corner_subpix, peak_local_max
from skimage.transform import warp, AffineTransform
from skimage.draw import ellipse
tform = AffineTransform(scale=(1.3, 1.1), rotation=1, shear=0.7,
translation=(210, 50))
image = warp(data.checkerboard(), tform.inverse, output_shape=(350, 350))
rr, cc = ellipse(310, 175, 10, 100)
image[rr, cc] = 1
image[180:230, 10:60] = 1
image[230:280, 60:110] = 1
coords = peak_local_max(corner_harris(image), min_distance=5)
coords_subpix = corner_subpix(image, coords, window_size=13)
plt.gray()
plt.imshow(image, interpolation='nearest')
plt.plot(coords[:, 1], coords[:, 0], '.b', markersize=3)
plt.plot(coords_subpix[:, 1], coords_subpix[:, 0], '+r', markersize=15)
plt.axis((0, 350, 350, 0))
plt.show()
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"""
===============================================================================
Harris Corner detector
===============================================================================
The Harris corner filter [1]_ detects "interest points" [2]_ using edge
detection in multiple directions.
.. [1] http://en.wikipedia.org/wiki/Corner_detection
.. [2] http://en.wikipedia.org/wiki/Interest_point_detection
"""
import numpy as np
from matplotlib import pyplot as plt
from skimage import data, img_as_float
from skimage.feature import harris, peak_local_max
def plot_harris_points(image, filtered_coords):
""" plots corners found in image"""
plt.imshow(image)
y, x = np.transpose(filtered_coords)
plt.plot(x, y, 'b.')
plt.axis('off')
# display results
plt.figure(figsize=(8, 3))
im_lena = img_as_float(data.lena())
im_text = img_as_float(data.text())
filtered_coords = peak_local_max(harris(im_lena), min_distance=4)
plt.axes([0, 0, 0.3, 0.95])
plot_harris_points(im_lena, filtered_coords)
filtered_coords = peak_local_max(harris(im_text), min_distance=4)
plt.axes([0.2, 0, 0.77, 1])
plot_harris_points(im_text, filtered_coords)
plt.show()