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Learning OpenCV 3: computer vision in C++ with the OpenCV library
Author
Publisher
O'Reilly Media
Publication Date
2016.
Language
English
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ISBN
9781491938003
9781491937969
9781491937969
Table of Contents
From the eBook - First edition.
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().
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