OpenCV Essentials电子书

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