November 2018
Intermediate to advanced
492 pages
12h 19m
English
Content preview from Hands-On Image Processing with Python
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Matching with ORB feature detector and binary descriptor using scikit-image
Let's write a code that demonstrates the ORB feature detection and binary descriptor algorithm. An oriented FAST detection method and the rotated BRIEF descriptors are used by this algorithm. As compared to BRIEF, ORB is more scale and rotation invariant, but even this applies the Hamming distance metric for matching, which is more efficient. Hence, this method is preferred over BRIEF when considering real-time applications:
from skimage import transform as transformfrom skimage.feature import (match_descriptors, ORB, plot_matches)img1 = rgb2gray(imread('../images/me5.jpg'))img2 = transform.rotate(img1, 180)affine_trans = transform.AffineTransform(scale=(1.3, 1.1), ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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