mirror of
https://github.com/wassname/scikit-image.git
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emmanuelle
55f5103dd8
Modified travis_script.sh to account for the new structure of the gallery Added README.txt files in directories of gallery examples Fixed references to gallery images in user guide pages Fixed broken links
62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
"""
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=======================
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BRIEF binary descriptor
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=======================
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This example demonstrates the BRIEF binary description algorithm.
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The descriptor consists of relatively few bits and can be computed using
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a set of intensity difference tests. The short binary descriptor results
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in low memory footprint and very efficient matching based on the Hamming
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distance metric.
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BRIEF does not provide rotation-invariance. Scale-invariance can be achieved by
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detecting and extracting features at different scales.
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"""
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from skimage import data
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from skimage import transform as tf
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from skimage.feature import (match_descriptors, corner_peaks, corner_harris,
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plot_matches, BRIEF)
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from skimage.color import rgb2gray
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import matplotlib.pyplot as plt
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img1 = rgb2gray(data.astronaut())
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tform = tf.AffineTransform(scale=(1.2, 1.2), translation=(0, -100))
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img2 = tf.warp(img1, tform)
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img3 = tf.rotate(img1, 25)
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keypoints1 = corner_peaks(corner_harris(img1), min_distance=5)
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keypoints2 = corner_peaks(corner_harris(img2), min_distance=5)
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keypoints3 = corner_peaks(corner_harris(img3), min_distance=5)
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extractor = BRIEF()
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extractor.extract(img1, keypoints1)
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keypoints1 = keypoints1[extractor.mask]
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descriptors1 = extractor.descriptors
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extractor.extract(img2, keypoints2)
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keypoints2 = keypoints2[extractor.mask]
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descriptors2 = extractor.descriptors
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extractor.extract(img3, keypoints3)
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keypoints3 = keypoints3[extractor.mask]
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descriptors3 = extractor.descriptors
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matches12 = match_descriptors(descriptors1, descriptors2, cross_check=True)
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matches13 = match_descriptors(descriptors1, descriptors3, cross_check=True)
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fig, ax = plt.subplots(nrows=2, ncols=1)
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plt.gray()
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plot_matches(ax[0], img1, img2, keypoints1, keypoints2, matches12)
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ax[0].axis('off')
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plot_matches(ax[1], img1, img3, keypoints1, keypoints3, matches13)
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ax[1].axis('off')
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plt.show()
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