Building Computer Vision Projects with OpenCV 4 and C++

coverpage

Title Page

Copyright and Credits

Building Computer Vision Projects with OpenCV 4 and C++

About Packt

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Contributors

About the authors

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Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Conventions used

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Reviews

Getting Started with OpenCV

Understanding the human visual system

How do humans understand image content?

Why is it difficult for machines to understand image content?

What can you do with OpenCV?

Inbuilt data structures and input/output

Image processing operations

GUI

Video analysis

3D reconstruction

Feature extraction

Object detection

Machine learning

Computational photography

Shape analysis

Optical flow algorithms

Face and object recognition

Surface matching

Text detection and recognition

Deep learning

Installing OpenCV

Windows

Mac OS X

Linux

Summary

An Introduction to the Basics of OpenCV

Technical requirements

Basic CMake configuration file

Creating a library

Managing dependencies

Making the script more complex

Images and matrices

Reading/writing images

Reading videos and cameras

Other basic object types

Vec object type

Scalar object type

Point object type

Size object type

Rect object type

RotatedRect object type

Basic matrix operations

Basic data persistence and storage

Writing to FileStorage

Summary

Learning Graphical User Interfaces

Technical requirements

Introducing the OpenCV user interface

Basic graphical user interface with OpenCV

Adding slider and mouse events to our interfaces

Graphic user interface with Qt

Adding buttons to the user interface

OpenGL support

Summary

Delving into Histogram and Filters

Technical requirements

Generating a CMake script file

Creating the graphical user interface

Drawing a histogram

Image color equalization

Lomography effect

Cartoonize effect

Summary

Automated Optical Inspection Object Segmentation and Detection

Technical requirements

Isolating objects in a scene

Creating an application for AOI

Preprocessing the input image

Noise removal

Removing the background using the light pattern for segmentation

Thresholding

Segmenting our input image

The connected components algorithm

The findContours algorithm

Summary

Learning Object Classification

Technical requirements

Introducing machine learning concepts

OpenCV machine learning algorithms

Computer vision and the machine learning workflow

Automatic object inspection classification example

Feature extraction