Book Image

Learning OpenCV 5 Computer Vision with Python, Fourth Edition - Fourth Edition

By : Joseph Howse, Joe Minichino
5 (2)
Book Image

Learning OpenCV 5 Computer Vision with Python, Fourth Edition - Fourth Edition

5 (2)
By: Joseph Howse, Joe Minichino

Overview of this book

Computer vision is a rapidly evolving science in the field of artificial intelligence, encompassing diverse use cases and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You'll be able to put theory into practice by building apps with OpenCV 5 and Python 3. You'll start by setting up OpenCV 5 with Python 3 on various platforms. Next, you'll learn how to perform basic operations such as reading, writing, manipulating, and displaying images, videos, and camera feeds. From taking you through image processing, video analysis, depth estimation, and segmentation, to helping you gain practice by building a GUI app, this book ensures you'll have opportunities for hands-on activities. You'll tackle two popular challenges: face detection and face recognition. You'll also learn about object classification and machine learning, which will enable you to create and use object detectors and even track moving objects in real time. Later, you'll develop your skills in augmented reality and real-world 3D navigation. Finally, you'll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age, and you'll deploy your solutions to the Cloud. By the end of this book, you'll have the skills you need to execute real-world computer vision projects.
Table of Contents (12 chapters)
Free Chapter
1
Learning OpenCV 5 Computer Vision with Python, Fourth Edition: Tackle tools, techniques, and algorithms for computer vision and machine learning
Appendix A: Bending Color Space with the Curves Filter

Finding 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:

Figure 6.16: An anchor tattoo, to be used for keypoint matching and finding homography

We, as human beings, can easily locate...