- 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
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.
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 faces and people in images using machine learning techniques
About the Author
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, object recognition, and 3D reconstruction. Robert authored OpenCV2 Computer Vision Application Programming Cookbook in 2011 and co-authored Object Oriented Software Development published by McGraw Hill in 2001.
He co-founded Visual Cortek in 2006, an Ottawa-based video analytics start-up that was later acquired by iWatchLife.com in 2009 where he also assumes the role of Chief Scientist. Since 2011, Robert has also been Chief Scientist at Cognivue Corp, a leader in embedded vision solutions. Robert has a Bachelor of Electrical Engineering degree from Ecole Polytechnique in Montreal (1987) and M.Sc. and Ph.D. degrees from INRS-Telecommunications, Montreal (1996).
Table of Contents
Chapter 1. Playing with Images
Chapter 2. Manipulating Pixels
Chapter 3. Processing the Colors of an Image
Chapter 4. Counting the Pixels with Histograms
Chapter 5. Transforming Images with Morphological Operations
Chapter 6. Filtering the Images
Chapter 7. Extracting Lines, Contours, and Components
Chapter 8. Detecting Interest Points
Chapter 9. Describing and Matching Interest Points
Chapter 10. Estimating Projective Relations in Images
Chapter 11. Reconstructing 3D Scenes
Chapter 12. Processing Video Sequences
Chapter 13. Tracking Visual Motion
Chapter 14. Learning from Examples