OpenCV By Example

Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3

OpenCV By Example

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Prateek Joshi, David Millán Escrivá, Vinícius Godoy

Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3
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Book Details

ISBN 139781785280948
Paperback296 pages

Book Description

Open CV is a cross-platform, free-for-use library that is primarily used for real-time Computer Vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation.

Whether you are completely new to the concept of Computer Vision or have a basic understanding of it, this book will be your guide to understanding the basic OpenCV concepts and algorithms through amazing real-world examples and projects.

Starting from the installation of OpenCV on your system and understanding the basics of image processing, we swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly used Computer Vision techniques to build your own Open CV projects from scratch.

By the end of this book, you will be familiar with the basics of Open CV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition.

Table of Contents

Chapter 1: Getting Started with OpenCV
Understanding the human visual system
How do humans understand image content?
What can you do with OpenCV?
Installing OpenCV
Summary
Chapter 2: An Introduction to the Basics of OpenCV
Basic CMake configuration files
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
Chapter 3: Learning the Graphical User Interface and Basic Filtering
Introducing the OpenCV user interface
A basic graphical user interface with OpenCV
The graphical user interface with QT
Adding slider and mouse events to our interfaces
Adding buttons to a user interface
OpenGL support
Summary
Chapter 4: Delving into Histograms and Filters
Generating a CMake script file
Creating the Graphical User Interface
Drawing a histogram
Image color equalization
Lomography effect
The cartoonize effect
Summary
Chapter 5: Automated Optical Inspection, Object Segmentation, and Detection
Isolating objects in a scene
Creating an application for AOI
Preprocessing the input image
Segmenting our input image
Summary
Chapter 6: Learning Object Classification
Introducing machine learning concepts
Computer Vision and the machine learning workflow
Automatic object inspection classification example
Feature extraction
Summary
Chapter 7: Detecting Face Parts and Overlaying Masks
Understanding Haar cascades
What are integral images?
Overlaying a facemask in a live video
Get your sunglasses on
Tracking your nose, mouth, and ears
Summary
Chapter 8: Video Surveillance, Background Modeling, and Morphological Operations
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
Chapter 9: Learning Object Tracking
Tracking objects of a specific color
Building an interactive object tracker
Detecting points using the Harris corner detector
Shi-Tomasi Corner Detector
Feature-based tracking
Summary
Chapter 10: Developing Segmentation Algorithms for Text Recognition
Introducing optical character recognition
The preprocessing step
Installing Tesseract OCR on your operating system
Using Tesseract OCR library
Summary
Chapter 11: Text Recognition with Tesseract
How the text API works
Using the text API
Summary

What You Will Learn

  • Install OpenCV 3 on your operating system
  • Create the required CMake scripts to compile the C++ application and manage its dependencies
  • Get to grips with the Computer Vision workflows and understand the basic image matrix format and filters
  • Understand the segmentation and feature extraction techniques
  • Remove backgrounds from a static scene to identify moving objects for video surveillance
  • Track different objects in a live video using various techniques
  • Use the new OpenCV functions for text detection and recognition with Tesseract

Authors

Table of Contents

Chapter 1: Getting Started with OpenCV
Understanding the human visual system
How do humans understand image content?
What can you do with OpenCV?
Installing OpenCV
Summary
Chapter 2: An Introduction to the Basics of OpenCV
Basic CMake configuration files
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
Chapter 3: Learning the Graphical User Interface and Basic Filtering
Introducing the OpenCV user interface
A basic graphical user interface with OpenCV
The graphical user interface with QT
Adding slider and mouse events to our interfaces
Adding buttons to a user interface
OpenGL support
Summary
Chapter 4: Delving into Histograms and Filters
Generating a CMake script file
Creating the Graphical User Interface
Drawing a histogram
Image color equalization
Lomography effect
The cartoonize effect
Summary
Chapter 5: Automated Optical Inspection, Object Segmentation, and Detection
Isolating objects in a scene
Creating an application for AOI
Preprocessing the input image
Segmenting our input image
Summary
Chapter 6: Learning Object Classification
Introducing machine learning concepts
Computer Vision and the machine learning workflow
Automatic object inspection classification example
Feature extraction
Summary
Chapter 7: Detecting Face Parts and Overlaying Masks
Understanding Haar cascades
What are integral images?
Overlaying a facemask in a live video
Get your sunglasses on
Tracking your nose, mouth, and ears
Summary
Chapter 8: Video Surveillance, Background Modeling, and Morphological Operations
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
Chapter 9: Learning Object Tracking
Tracking objects of a specific color
Building an interactive object tracker
Detecting points using the Harris corner detector
Shi-Tomasi Corner Detector
Feature-based tracking
Summary
Chapter 10: Developing Segmentation Algorithms for Text Recognition
Introducing optical character recognition
The preprocessing step
Installing Tesseract OCR on your operating system
Using Tesseract OCR library
Summary
Chapter 11: Text Recognition with Tesseract
How the text API works
Using the text API
Summary

Book Details

ISBN 139781785280948
Paperback296 pages
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