OpenCV Essentials

330 Pages·07.586 MB·English

by  Oscar Deniz Suarez et al.

OpenCV Essentials
Table of Contents
OpenCV Essentials
Credits
About the Authors
About the Reviewers
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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