Book Image

Learn OpenCV 4 By Building Projects - Second Edition

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

Learn OpenCV 4 By Building Projects - Second Edition

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

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. Whether you’re completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects – Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. You’ll begin with the installation of OpenCV and the basics of image processing. Then, you’ll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module. By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch.
Table of Contents (14 chapters)

Introducing optical character recognition

Identifying text in an image is a very popular application for computer vision. This process is commonly called optical character recognition, and is divided as follows:

  • Text preprocessing and segmentation: During this step, the computer must deal with image noise, and rotation (skewing), and identify what areas are candidate text.
  • Text identification: This is the process of identifying each letter in text. Although this is also a computer vision topic, we will not show how you to do this in this book purely using OpenCV. Instead, we will show you how to use the Tesseract library to do this step, since it was integrated in OpenCV 3.0. If you are interested in learning how to do what Tesseract does by yourself, take a look at Packt's Mastering OpenCV book, which presents a chapter on car plate recognition.

The preprocessing and segmentation...