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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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Kaehler, Adrian
Otros Autores: Bradski, Gary R.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Sebastopol, CA : O'Reilly Media, 2016.
Edición:First edition.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • 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.
  • 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.
  • 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.
  • 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().
  • 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().