.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/features_detection/plot_brief.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code or to run this example in your browser via Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_features_detection_plot_brief.py: ======================= 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. BRIEF does not provide rotation-invariance. Scale-invariance can be achieved by detecting and extracting features at different scales. .. GENERATED FROM PYTHON SOURCE LINES 14-65 .. image-sg:: /auto_examples/features_detection/images/sphx_glr_plot_brief_001.png :alt: Original Image vs. Transformed Image, Original Image vs. Transformed Image :srcset: /auto_examples/features_detection/images/sphx_glr_plot_brief_001.png :class: sphx-glr-single-img .. code-block:: default from skimage import data from skimage import transform from skimage.feature import (match_descriptors, corner_peaks, corner_harris, plot_matches, BRIEF) from skimage.color import rgb2gray import matplotlib.pyplot as plt img1 = rgb2gray(data.astronaut()) tform = transform.AffineTransform(scale=(1.2, 1.2), translation=(0, -100)) img2 = transform.warp(img1, tform) img3 = transform.rotate(img1, 25) keypoints1 = corner_peaks(corner_harris(img1), min_distance=5, threshold_rel=0.1) keypoints2 = corner_peaks(corner_harris(img2), min_distance=5, threshold_rel=0.1) keypoints3 = corner_peaks(corner_harris(img3), min_distance=5, threshold_rel=0.1) extractor = BRIEF() extractor.extract(img1, keypoints1) keypoints1 = keypoints1[extractor.mask] descriptors1 = extractor.descriptors extractor.extract(img2, keypoints2) keypoints2 = keypoints2[extractor.mask] descriptors2 = extractor.descriptors extractor.extract(img3, keypoints3) keypoints3 = keypoints3[extractor.mask] descriptors3 = extractor.descriptors matches12 = match_descriptors(descriptors1, descriptors2, cross_check=True) matches13 = match_descriptors(descriptors1, descriptors3, cross_check=True) fig, ax = plt.subplots(nrows=2, ncols=1) plt.gray() plot_matches(ax[0], img1, img2, keypoints1, keypoints2, matches12) ax[0].axis('off') ax[0].set_title("Original Image vs. Transformed Image") plot_matches(ax[1], img1, img3, keypoints1, keypoints3, matches13) ax[1].axis('off') ax[1].set_title("Original Image vs. Transformed Image") plt.show() .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.661 seconds) .. _sphx_glr_download_auto_examples_features_detection_plot_brief.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/scikit-image/scikit-image/v0.22.x?filepath=notebooks/auto_examples/features_detection/plot_brief.ipynb :alt: Launch binder :width: 150 px .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_brief.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_brief.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_