OpenCV essentials : acquire, process, and analyze visual content to build full-fledged imaging applications using OpenCV /

This book is intended for C++ developers who want to learn how to implement the main techniques of OpenCV and get started with it quickly. Working experience with computer vision / image processing is expected.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Suarez, Oscar Deniz (Autor)
Otros Autores: Leeuwesteijn, Arie (Diseñador de portada)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, England : Packt Publishing, 2014.
Colección:Community experience distilled.
Temas:
Computer vision.
Image processing > Digital techniques.
Vision par ordinateur.
Traitement d'images > Techniques numériques.
digital imaging.
COMPUTERS > General.
Computer vision
Image processing > Digital techniques
Acceso en línea:Texto completo
Tabla de Contenidos:
  • ""Cover""; ""Copyright""; ""Credits""; ""About the Authors""; ""About the Reviewers""; ""www.PacktPub.com""; ""Table of Contents""; ""Preface""; ""Chapter 1: Getting Started""; ""Setting up OpenCV""; ""Compiled versus precompiled library""; ""Configuring OpenCV with Cmake""; ""Building and installing the library""; ""Quick recipe for setting up OpenCV""; ""API concepts and basic datatypes""; ""Our first program â€? reading and writing images and videos""; ""The qmake project file""; ""Reading and playing a video file""; ""Live input from a camera""; ""Summary""
  • ""Chapter 2: Something We Look at â€? Graphical User Interfaces""""Using OpenCV's highgui module""; ""Text and drawing""; ""Selecting regions""; ""Using Qt-based functions""; ""Text overlays and status bar""; ""The properties dialog""; ""Windows properties""; ""Qt images""; ""Summary""; ""Chapter 3: First Things First â€? Image Processing""; ""Pixel-level access and common operations""; ""Image histogram""; ""Histogram equalization""; ""Brightness and contrast modeling""; ""Histogram matching and LUT""; ""Conversion from RGB to other color spaces""; ""Filtering with the retina model""
  • Arithmetic and geometrical transformsArithmetic transform
  • Geometrical transforms
  • Summary
  • What else?
  • Chapter 4: What's in the Image? Segmentation
  • Thresholding
  • Contours and connected components
  • Flood fill
  • Watershed segmentation
  • GrabCut
  • Summary
  • What else?
  • Chapter 5: Focusing on the Interesting 2D Features
  • Interest points
  • Feature detectors
  • The FAST detector
  • The SURF detector
  • The ORB detector
  • The KAZE and AKAZE detectors
  • Feature descriptor extractors
  • Descriptor matchers
  • Matching the SURF descriptorsMatching the AKAZE descriptors
  • Summary
  • What else?
  • Chapter 6: Where's Wally? Object Detection
  • Object detection
  • Detecting objects with OpenCV
  • Cascades are beautiful
  • Object detection using cascades
  • Training your own cascade
  • Latent SVM
  • Scene text detection
  • Summary
  • What else?
  • Chapter 7: What Is He Doing? Motion
  • Motion history
  • Reading video sequences
  • The Lucas-Kanade optical flow
  • The Gunnar-Farneback optical flow
  • The Mean-Shift tracker
  • The CamShift tracker
  • The Motion templatesThe Motion history template
  • The Motion gradient
  • The Background subtraction technique
  • Image alignment
  • Summary
  • What else?
  • Chapter 8: Advanced Topics
  • Machine learning
  • The KNN classifier
  • The Random Forest classifier
  • SVM for classification
  • What about GPUs?
  • Setting up OpenCV with CUDA
  • Configuring the OpenCV build
  • Building and installing the library
  • A quick recipe for setting up OpenCV with CUDA
  • Our first GPU-based program
  • Going real time
  • Performance
  • Summary
  • What else?

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