Book Image

OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition

By : Robert Laganiere
Book Image

OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition

By: Robert Laganiere

Overview of this book

Making your applications see has never been easier with OpenCV. With it, you can teach your robot how to follow your cat, write a program to correctly identify the members of One Direction, or even help you find the right colors for your redecoration. OpenCV 3 Computer Vision Application Programming Cookbook Third Edition provides a complete introduction to the OpenCV library and explains how to build your first computer vision program. You will be presented with a variety of computer vision algorithms and exposed to important concepts in image and video analysis that will enable you to build your own computer vision applications. This book helps you to get started with the library, and shows you how to install and deploy the OpenCV library to write effective computer vision applications following good programming practices. You will learn how to read and write images and manipulate their pixels. Different techniques for image enhancement and shape analysis will be presented. You will learn how to detect specific image features such as lines, circles or corners. You will be introduced to the concepts of mathematical morphology and image filtering. The most recent methods for image matching and object recognition are described, and you’ll discover how to process video from files or cameras, as well as how to detect and track moving objects. Techniques to achieve camera calibration and perform multiple-view analysis will also be explained. Finally, you’ll also get acquainted with recent approaches in machine learning and object classification.
Table of Contents (21 chapters)
OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition
Credits
About the Author
About the Reviewer
www.PacktPub.com
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Preface

Introduction


Images are generally produced using a digital camera, which captures a scene by projecting light going through its lens onto an image sensor. The fact that an image is formed by the projection of a 3D scene onto a 2D plane implies the existence of important relationships both between a scene and its image and between different images of the same scene. Projective geometry is the tool that is used to describe and characterize, in mathematical terms, the process of image formation. In this chapter, we will introduce you to some of the fundamental projective relations that exist in multi-view imagery and explain how these can be used in computer vision programming. But, before we start the recipes, let's explore the basic concepts related to scene projection and image formation.

Image formation

Fundamentally, the process used to produce images has not changed since the beginning of photography. The light coming from an observed scene is captured by a camera through a frontal aperture...