Table Of Content

OpenCV Essentials Table of Contents OpenCV Essentials Credits About the Authors About the Reviewers www.PacktPub.com Support files, eBooks, discount offers, and more Why subscribe? Free access for Packt account holders Preface What this book covers What you need for this book Who this book is for Conventions Reader feedback Customer support Downloading the example code Downloading the color images of this book Errata Piracy Questions 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 – reading and writing images and videos The qmake project file Reading and playing a video file Live input from a camera Summary 2. Something We Look At – 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 3. First Things First – 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 transforms Arithmetic transform Geometrical transforms Summary What else? 4. What’s in the Image? Segmentation Thresholding Contours and connected components Flood fill Watershed segmentation GrabCut Summary What else? 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 descriptors Matching the AKAZE descriptors Summary What else? 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? 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 templates The Motion history template The Motion gradient The Background subtraction technique Image alignment Summary What else? 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? Index OpenCV Essentials