Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By : David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot
Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By: David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot

Overview of this book

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: •Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá •Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi
Table of Contents (28 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Chapter 1. Getting Started with OpenCV

Computer vision applications are interesting and useful, but the underlying algorithms are computationally intensive. With the advent of cloud computing, we are getting more processing power to work with.

The OpenCV library enables us to run computer vision algorithms efficiently in real time. It has been around for many years and has become the standard library in this field. One of the main advantages of OpenCV is that it is highly optimized and available on almost all platforms.

This book will cover the various algorithms we will be using, why we are using them, and how to implement them in OpenCV.

In this chapter, we are going to learn how to install OpenCV on various operating systems. We will discuss what OpenCV offers out of the box, and the various things that we can do using the inbuilt functions.

By the end of this chapter, you will be able to answer the following questions:

  • How do humans process visual data, and how do they understand image content?
  • What can we do with OpenCV, and what are the various modules available in OpenCV that can be used to achieve those things?
  • How do we install OpenCV on Windows, Linux, and Mac OS X?