Book Image

Learn OpenCV 4 By Building Projects - Second Edition

By : David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi
Book Image

Learn OpenCV 4 By Building Projects - Second Edition

By: David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi

Overview of this book

OpenCV is one of the best open source libraries available, and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. Whether you’re completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects – Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. You’ll begin with the installation of OpenCV and the basics of image processing. Then, you’ll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module. By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch.

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Table of Contents (14 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Getting Started with OpenCV
Getting Started with OpenCV
Understanding the human visual system
How do humans understand image content?
What can you do with OpenCV?
Installing OpenCV
Summary
2
An Introduction to the Basics of OpenCV
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
Basic matrix operations
Basic data persistence and storage
Summary
3
Learning Graphical User Interfaces
Learning Graphical User Interfaces
Technical requirements
Introducing the OpenCV user interface
Basic graphical user interface with OpenCV
Graphic user interface with Qt
OpenGL support
Summary
4
Delving into Histogram and Filters
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
5
Automated Optical Inspection, Object Segmentation, and Detection
Automated Optical Inspection, Object Segmentation, and Detection
Technical requirements
Isolating objects in a scene
Creating an application for AOI
Preprocessing the input image
Segmenting our input image
Summary
6
Learning Object Classification
Learning Object Classification
Technical requirements
Introducing machine learning concepts
Computer vision and the machine learning workflow
Automatic object inspection classification example
Summary
7
Detecting Face Parts and Overlaying Masks
Detecting Face Parts and Overlaying Masks
Technical requirements
Understanding Haar cascades
What are integral images?
Overlaying a face mask in a live video
Get your sunglasses on
Tracking the nose, mouth, and ears
Summary
8
Video Surveillance, Background Modeling, and Morphological Operations
Video Surveillance, Background Modeling, and Morphological Operations
Technical requirements
Understanding background subtraction
Naive background subtraction
Frame differencing
The Mixture of Gaussians approach
Morphological image processing
Slimming the shapes
Thickening the shapes
Other morphological operators
Summary
9
Learning Object Tracking
Learning Object Tracking
Technical requirements
Tracking objects of a specific color
Building an interactive object tracker
Detecting points using the Harris corner detector
Good features to track
Feature-based tracking
Summary
10
Developing Segmentation Algorithms for Text Recognition
Developing Segmentation Algorithms for Text Recognition
Technical requirements
Introducing optical character recognition
Preprocessing stage
Installing Tesseract OCR on your operating system
Using the Tesseract OCR library
Summary
11
Text Recognition with Tesseract
Text Recognition with Tesseract
Technical requirements
How the text API works
Using the text API
Summary
12
Deep Learning with OpenCV
Deep Learning with OpenCV
Technical requirements
Introduction to deep learning
Deep learning in OpenCV
YOLO – real-time object detection
Face detection with SSD
Summary
Further reading
13
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An Introduction to the Basics of OpenCV

After covering OpenCV installation on different operating systems in Chapter 1, Getting Started with OpenCV, we are going to introduce the basics of OpenCV development in this chapter. It begins with showing how to create our project using CMake. We are going to introduce the basic image data structures and matrices, along with other structures that are required to work in our projects. We are going to introduce how to save our variables and data into files using the XML/YAML persistence OpenCV functions.

In this chapter, we will cover the following topics:

  • Configuring projects with CMake
  • Reading/writing images from/to disk
  • Reading videos and accessing camera devices
  • The main image structures (for example, matrices)
  • Other important and basic structures (for example, vectors and scalars)
  • An introduction to basic matrix operations
  • File storage...
Previous Section
End of Section 1
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