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OpenCV 4 Computer Vision Application Programming Cookbook

OpenCV 4 Computer Vision Application Programming Cookbook

By : Millán Escrivá, Robert Laganiere
5 (1)
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OpenCV 4 Computer Vision Application Programming Cookbook

OpenCV 4 Computer Vision Application Programming Cookbook

5 (1)
By: Millán Escrivá, Robert Laganiere

Overview of this book

OpenCV is an image and video processing library used for all types of image and video analysis. Throughout the book, you'll work with recipes to implement a variety of tasks. With 70 self-contained tutorials, this book examines common pain points and best practices for computer vision (CV) developers. Each recipe addresses a specific problem and offers a proven, best-practice solution with insights into how it works, so that you can copy the code and configuration files and modify them to suit your needs. This book begins by guiding you through setting up OpenCV, and explaining how to manipulate pixels. You'll understand how you can process images with classes and count pixels with histograms. You'll also learn detecting, describing, and matching interest points. As you advance through the chapters, you'll get to grips with estimating projective relations in images, reconstructing 3D scenes, processing video sequences, and tracking visual motion. In the final chapters, you'll cover deep learning concepts such as face and object detection. By the end of this book, you'll have the skills you need to confidently implement a range of computer vision algorithms to meet the technical requirements of your complex CV projects.
Table of Contents (17 chapters)
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Processing Video Sequences

Video signals constitute a rich source of visual information. They are made of a sequence of images, called frames, that are taken at regular time intervals (specified as the frame rate, generally expressed in frames per second) and show a scene in motion. With the advent of powerful computers, it is now possible to perform advanced visual analysis on video sequences—sometimes at rates close to, or even faster than, the actual video frame rate. This chapter will show you how to read, process, and store video sequences.

We will see that, once the individual frames of a video sequence have been extracted, the different image processing functions presented in this book can be applied to each of them. In addition, we will also look at a few algorithms that perform a temporal analysis of the video sequence, compare adjacent frames to track objects...

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