Book Image

OpenCV By Example

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

OpenCV By Example

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

Overview of this book

Open CV is a cross-platform, free-for-use library that is primarily used for real-time Computer Vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. Whether you are completely new to the concept of Computer Vision or have a basic understanding of it, this book will be your guide to understanding the basic OpenCV concepts and algorithms through amazing real-world examples and projects. Starting from the installation of OpenCV on your system and understanding the basics of image processing, we swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly used Computer Vision techniques to build your own Open CV projects from scratch. By the end of this book, you will be familiar with the basics of Open CV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition.
Table of Contents (18 chapters)
OpenCV By Example
About the Authors
About the Reviewers

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 you to run Computer Vision algorithms efficiently in real time. It has been around for many years and it 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. The discussions in this book will cover everything, including the algorithm we are using, why we are using it, and how to implement it 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 in-built 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 to install OpenCV on Windows, Linux, and Mac OS X?