Learning OpenCV 3 computer vision in C++ with the OpenCV library

Get started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, roboticists, and hobbyists. You'll learn what it...

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Bibliographic Details
Main Author: Kaehler, Adrian
Other Authors: Bradski, Gary R.
Format: eBook
Language:English
Published: Sebastopol, CA O'Reilly Media 2016
Edition:First edition
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
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245 0 0 |a Learning OpenCV 3  |b computer vision in C++ with the OpenCV library  |c Adrian Kaehler and Gary Bradski 
246 3 1 |a Computer vision in C++ with the OpenCV library 
250 |a First edition 
260 |a Sebastopol, CA  |b O'Reilly Media  |c 2016 
300 |a 1 online resource 
505 0 |a Includes bibliographical references and index 
505 0 |a Copyright; Table of Contents; Preface; Purpose of This Book; Who This Book Is For; What This Book Is Not; About the Programs in This Book; Prerequisites; How This Book Is Best Used; Conventions Used in This Book; Using Code Examples; O'Reilly Safari; We'd Like to Hear from You; Acknowledgments; Thanks for Help on OpenCV; Thanks for Help on This Book; Adrian Adds ... ; Gary Adds ... ; Chapter 1. Overview; What Is OpenCV?; Who Uses OpenCV?; What Is Computer Vision?; The Origin of OpenCV; OpenCV Block Diagram; Speeding Up OpenCV with IPP; Who Owns OpenCV?; Downloading and Installing OpenCV. 
505 0 |a InstallationGetting the Latest OpenCV via Git; More OpenCV Documentation; Supplied Documentation; Online Documentation and the Wiki; OpenCV Contribution Repository; Downloading and Building Contributed Modules; Portability; Summary; Exercises; Chapter 2. Introduction to OpenCV; Include Files; Resources; First Program-Display a Picture; Second Program-Video; Moving Around; A Simple Transformation; A Not-So-Simple Transformation; Input from a Camera; Writing to an AVI File; Summary; Exercises; Chapter 3. Getting to Know OpenCV Data Types; The Basics; OpenCV Data Types 
505 0 |a Cv::getConvertElem() and cv::getConvertScaleElem()cv::idct(); cv::idft(); cv::inRange(); cv::insertImageCOI(); cv::invert(); cv::log(); cv::LUT(); cv::magnitude(); cv::Mahalanobis(); cv::max(); cv::mean(); cv::meanStdDev(); cv::merge(); cv::min(); cv::minMaxIdx(); cv::minMaxLoc(); cv::mixChannels(); cv::mulSpectrums(); cv::multiply(); cv::mulTransposed(); cv::norm(); cv::normalize(); cv::perspectiveTransform(); cv::phase(); cv::polarToCart(); cv::pow(); cv::randu(); cv::randn(); cv::randShuffle(); cv::reduce(); cv::repeat(); cv::scaleAdd(); cv::setIdentity(); cv::solve(); cv::solveCubic() 
505 0 |a Overview of the Basic TypesBasic Types: Getting Down to Details; Helper Objects; Utility Functions; The Template Structures; Summary; Exercises; Chapter 4. Images and Large Array Types; Dynamic and Variable Storage; The cv::Mat Class: N-Dimensional Dense Arrays; Creating an Array; Accessing Array Elements Individually; The N-ary Array Iterator: NAryMatIterator; Accessing Array Elements by Block; Matrix Expressions: Algebra and cv::Mat; Saturation Casting; More Things an Array Can Do; The cv::SparseMat Class: Sparse Arrays; Accessing Sparse Array Elements; Functions Unique to Sparse Arrays 
505 0 |a Template Structures for Large Array TypesSummary; Exercises; Chapter 5. Array Operations; More Things You Can Do with Arrays; cv::abs(); cv::absdiff(); cv::add(); cv::addWeighted(); cv::bitwise_and(); cv::bitwise_not(); cv::bitwise_or(); cv::bitwise_xor(); cv::calcCovarMatrix(); cv::cartToPolar(); cv::checkRange(); cv::compare(); cv::completeSymm(); cv::convertScaleAbs(); cv::countNonZero(); cv::cvarrToMat(); cv::dct(); cv::dft(); cv::cvtColor(); cv::determinant(); cv::divide(); cv::eigen(); cv::exp(); cv::extractImageCOI(); cv::flip(); cv::gemm() 
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520 |a Get started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, roboticists, and hobbyists. You'll learn what it takes to build applications that enable computers to "see" and make decisions based on that data. With over 500 functions that span many areas in vision, OpenCV is used for commercial applications such as security, medical imaging, pattern and face recognition, robotics, and factory product inspection. This book gives you a firm grounding in computer vision and OpenCV for building simple or sophisticated vision applications. Hands-on exercises in each chapter help you apply what you've learned. This volume covers the entire library, in its modern C++ implementation, including machine learning tools for computer vision. Learn OpenCV data types, array types, and array operations Capture and store still and video images with HighGUI Transform images to stretch, shrink, warp, remap, and repair Explore pattern recognition, including face detection Track objects and motion through the visual field Reconstruct 3D images from stereo vision Discover basic and advanced machine learning techniques in OpenCV--Provided by publisher