April 2020
Intermediate to advanced
438 pages
12h 2m
English
Content preview from Python Image Processing Cookbook
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How to do it...
Run the following code segments to see how the RANSAC algorithm makes model fitting robust:
- Set a random seed using numpy (for the sake of reproducible results):
np.random.seed(2)
- Read the input images to be matched:
img1 = rgb2gray(imread('images/victoria3.png'))img2 = rgb2gray(imread('images/victoria4.png'))
- Extract the Harris Corner keypoints (features) from the input images using the following couple of lines of code:
keypoints1 = corner_peaks(corner_harris(img1), min_distance=1)keypoints2 = corner_peaks(corner_harris(img2), min_distance=1)
- Extract the binary BRIEF descriptors for the keypoints found for both of the input images:
extractor = BRIEF(patch_size=10)extractor.extract(img1, keypoints1)descriptors1 = ...
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