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OpenCV 4 Computer Vision Application Programming Cookbook

You're reading from   OpenCV 4 Computer Vision Application Programming Cookbook Build complex computer vision applications with OpenCV and C++

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789340723
Length 494 pages
Edition 4th Edition
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Authors (2):
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Robert Laganiere Robert Laganiere
Author Profile Icon Robert Laganiere
Robert Laganiere
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
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Table of Contents (17) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating the Pixels 3. Processing Color Images with Classes 4. Counting the Pixels with Histograms 5. Transforming Images with Morphological Operations 6. Filtering the Images 7. Extracting Lines, Contours, and Components 8. Detecting Interest Points 9. Describing and Matching Interest Points 10. Estimating Projective Relations in Images 11. Reconstructing 3D Scenes 12. Processing Video Sequences 13. Tracking Visual Motion 14. Learning from Examples 15. OpenCV Advanced Features 16. Other Books You May Enjoy

Describing keypoints with binary features

In the previous recipe, we learned how to describe a keypoint using rich descriptors extracted from the image intensity gradient. These descriptors are floating-point vectors that have a dimension of 64, 128, or sometimes even longer. This makes them costly to manipulate. In order to reduce the memory and computational load associated with these descriptors, the idea of using binary descriptors has been recently introduced. The challenge here is to make them easy to compute and yet keep them robust to scene and viewpoint changes. This recipe describes some of these binary descriptors. In particular, we will look at the ORB (short for Oriented FAST and Rotated BRIEF) and BRISK (short for Binary Robust Invariant Scalable Keypoints) descriptors for which we presented their associated feature point detectors in Chapter 8, Detecting Interest...

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