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Learning OpenCV 4 Computer Vision with Python 3

You're reading from   Learning OpenCV 4 Computer Vision with Python 3 Get to grips with tools, techniques, and algorithms for computer vision and machine learning

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781789531619
Length 372 pages
Edition 3rd Edition
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Authors (2):
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Joe Minichino Joe Minichino
Author Profile Icon Joe Minichino
Joe Minichino
Joseph Howse Joseph Howse
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Joseph Howse
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Table of Contents (13) Chapters Close

Preface 1. Setting Up OpenCV 2. Handling Files, Cameras, and GUIs FREE CHAPTER 3. Processing Images with OpenCV 4. Depth Estimation and Segmentation 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Building Custom Object Detectors 8. Tracking Objects 9. Camera Models and Augmented Reality 10. Introduction to Neural Networks with OpenCV 11. Other Book You May Enjoy Appendix A: Bending Color Space with the Curves Filter

Performing homography with FLANN-based matches

First of all, what is homography? Let's read a definition from the internet:

"A relation between two figures, such that to any point of the one corresponds one and but one point in the other, and vice versa. Thus, a tangent line rolling on a circle cuts two fixed tangents of the circle in two sets of points that are homographic."

If you – like the authors of this book – are none the wiser from the preceding definition, you will probably find the following explanation a bit clearer: homography is a condition in which two figures find each other when one is a perspective distortion of the other.

First, let's take a look at what we want to achieve so that we can fully understand what homography is. Then, we will go through the code.

Imagine that we want to search for the following tattoo:

We, as human...

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