Key FeaturesWritten to the latest, gold-standard specification of OpenCV 3Master OpenCV, the open source library of the computer vision communityMaster fundamental concepts in computer vision and image processingLearn about the important classes and functions of OpenCV with complete working examples applied to real imagesBook DescriptionMaking 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 youll 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, youll also get acquainted with recent approaches in machine learning and object classification.What you will learnInstall and create a program using the OpenCV libraryProcess an image by manipulating its pixelsAnalyze an image using histogramsSegment images into homogenous regions and extract meaningful objectsApply image filters to enhance image contentExploit the image geometry in order to relay different views of a pictured sceneCalibrate the camera from different image observationsDetect people and objects in images using machine learning techniquesReconstruct a 3D scene from imagesAbout the AuthorRobert 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 co-founded Visual Cortek in 2006, an Ottawa-based video analytics startup that was later acquired by http://iwatchlife.com/ in 2009. 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). Visit the authors website at http://www.laganiere.name/.Table of ContentsPlaying with ImagesManipulating PixelsProcessing the Colors of an ImageCounting the Pixels with HistogramsTransforming Images with Morphological OperationsFiltering the ImagesExtracting Lines, Contours, and ComponentsDetecting Interest PointsDescribing and Matching Interest PointsEstimating Projective Relations in ImagesReconstructing 3D ScenesProcessing Video SequencesTracking Visual MotionLearning from Examples