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)

What are integral images?

In order to extract these Haar features, we will have to calculate the sum of the pixel values enclosed in many rectangular regions of the image. To make it scale-invariant, we are required to compute these areas at multiple scales (for various rectangle sizes). Implemented naively, this would be a very computationally-intensive process; we would have to iterate over all the pixels of each rectangle, including reading the same pixels multiple times if they are contained in different overlapping rectangles. If you want to build a system that can run in real-time, you cannot spend so much time in computation. We need to find a way to avoid this huge redundancy during the area computation because we iterate over the same pixels multiple times. To avoid it, we can use something called integral images. These images can be initialized at a linear time (by iterating...