diff --git a/doc/examples/plot_brief.py b/doc/examples/plot_brief.py new file mode 100644 index 00000000..390da1e5 --- /dev/null +++ b/doc/examples/plot_brief.py @@ -0,0 +1,62 @@ +""" +======================= +BRIEF binary descriptor +======================= + +This example demonstrates the BRIEF binary description algorithm. + +The descriptor consists of relatively few bits and can be computed using +a set of intensity difference tests. The short binary descriptor results +in low memory footprint and very efficient matching based on the Hamming +distance metric. + +However, BRIEF does not provide rotation-invariance and scale scale-invariance +can be achieved by detecting and extracting features at different scales. + +The ORB feature detection and binary description algorithm is an extension to +the BRIEF method and provides rotation and scale-invariance, see +`skimage.feature.ORB`. + +""" +import numpy as np +from skimage import data +from skimage import transform as tf +from skimage.feature import (match_descriptors, corner_peaks, corner_harris, + plot_matches, BRIEF) +from skimage.color import rgb2gray +from skimage import img_as_float +import matplotlib.pyplot as plt + + +img1 = rgb2gray(data.lena()) +tform = tf.AffineTransform(scale=(1.2, 1.2), translation=(0, -100)) +img2 = tf.warp(img1, tform) +img3 = tf.rotate(img1, 25) + +keypoints1 = corner_peaks(corner_harris(img1), min_distance=5) +keypoints2 = corner_peaks(corner_harris(img2), min_distance=5) +keypoints3 = corner_peaks(corner_harris(img3), min_distance=5) + +extractor = BRIEF() + +descriptors1, mask1 = extractor.extract(img1, keypoints1) +descriptors2, mask2 = extractor.extract(img2, keypoints2) +descriptors3, mask3 = extractor.extract(img3, keypoints3) + +keypoints1 = keypoints1[mask1] +keypoints2 = keypoints2[mask2] +keypoints3 = keypoints3[mask3] + +fig, ax = plt.subplots(nrows=2, ncols=1) + +plt.gray() + +idxs1, idxs2 = match_descriptors(descriptors1, descriptors2, cross_check=True) +plot_matches(ax[0], img1, img2, keypoints1, keypoints2, idxs1, idxs2) +ax[0].axis('off') + +idxs1, idxs3 = match_descriptors(descriptors1, descriptors3, cross_check=True) +plot_matches(ax[1], img1, img3, keypoints1, keypoints3, idxs1, idxs3) +ax[1].axis('off') + +plt.show()