OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition

Recipes to help you build computer vision applications that make the most of the popular C++ library OpenCV 3

About This Book

• Written to the latest, gold-standard specification of OpenCV 3
• Master OpenCV, the open source library of the computer vision community
• Master fundamental concepts in computer vision and image processing
• Learn about the important classes and functions of OpenCV with complete working examples applied to real images

Who This Book Is For

OpenCV 3 Computer Vision Application Programming Cookbook Third Edition is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers who wish to be introduced to the concepts of computer vision programming. It can also be used as a companion book for university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision.

What You Will Learn

• Install and create a program using the OpenCV library
• Process an image by manipulating its pixels
• Analyze an image using histograms
• Segment images into homogenous regions and extract meaningful objects
• Apply image filters to enhance image content
• Exploit the image geometry in order to relay different views of a pictured scene
• Calibrate the camera from different image observations
• Detect people and objects in images using machine learning techniques
• Reconstruct a 3D scene from images

In Detail

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.

Style and approach

This book will arm you with the basics you need to start writing world-aware applications right from a pixel level all the way through to processing video sequences.

Robert Laganiere is a professor at the School of Electrical Engineering and Computer Science of the University of Ottawa, Canada. He is also a faculty member of the VIVA research lab and is the co-author of several scientific publications and patents in content-based video analysis, visual surveillance, driver-assistance, object detection, and tracking. Robert authored the OpenCV2 Computer Vision Application Programming Cookbook in 2011 and co-authored Object Oriented Software Development published by McGraw Hill in 2001. He is also a consultant in computer vision and has assumed the role of Chief Scientist in a number of startups companies such as Cognivue Corp, iWatchlife, and Tempo Analytics. Robert has a Bachelor of Electrical Engineering degree from Ecole Polytechnique in Montreal (1987) and MSc and PhD degrees from INRS-Telecommunications, Montreal (1996).