OpenCV 3 by Example [Video]

OpenCV 3 by Example [Video]

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David Millán Escrivá, Prateek Joshi, Vinícius Godoy

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

ISBN 139781787287259
Course Length

3 hours 57 minutes

Video 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 video 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 video, 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

Style and Approach

This video is a practical tutorial with lots of tips, and is closely focused on developing Computer vision applications with OpenCV. Beginning with the fundamentals, the complexity increases with each chapter. Sample applications are developed throughout the course that you can execute and use in your own projects.

Table of Contents

Getting Started with OpenCV
The Course Overview
The Human Visual System and Understanding Image Content
What Can You Do with OpenCV?
Installing OpenCV
An Introduction to the Basics of OpenCV
Basic CMakeConfiguration and 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, Data Persistence, and Storage
Learning the Graphical User Interface and Basic Filtering
The OpenCVUser Interface and a Basic GUI
The Graphical User Interface with QT
Adding Slider and Mouse Events to Our Interfaces
Adding Buttons to a User Interface
OpenGL Support
Delving into Histograms and Filters
Generating a CMakeScript File
Creating the Graphical User Interface
Drawing a Histogram
Image Color Equalization
Lomography Effect
The CartoonizeEffect
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
Learning Object Classification
Introducing Machine Learning Concepts
Computer Vision and the Machine Learning Workflow
Automatic Object Inspection Classification Example
Feature Extraction
Detecting Face Parts and Overlaying Masks
Understanding HaarCascades
What Are Integral Images
Overlaying a Facemask in a Live Video
Get Your Sunglasses On
Tracking Your Nose, Mouth, and Ears
Video Surveillance, Background Modeling, and Morphological Operations
Background Subtraction
Frame Differencing
The Mixture of Gaussians Approach
Morphological Image processing
Other Morphological Operators
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
Developing Segmentation Algorithms for Text Recognition
Introducing Optical Character Recognition
The Preprocessing Step
Installing Tesseract OCR on Your Operating System
Using Tesseract OCR Library

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

Getting Started with OpenCV
The Course Overview
The Human Visual System and Understanding Image Content
What Can You Do with OpenCV?
Installing OpenCV
An Introduction to the Basics of OpenCV
Basic CMakeConfiguration and 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, Data Persistence, and Storage
Learning the Graphical User Interface and Basic Filtering
The OpenCVUser Interface and a Basic GUI
The Graphical User Interface with QT
Adding Slider and Mouse Events to Our Interfaces
Adding Buttons to a User Interface
OpenGL Support
Delving into Histograms and Filters
Generating a CMakeScript File
Creating the Graphical User Interface
Drawing a Histogram
Image Color Equalization
Lomography Effect
The CartoonizeEffect
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
Learning Object Classification
Introducing Machine Learning Concepts
Computer Vision and the Machine Learning Workflow
Automatic Object Inspection Classification Example
Feature Extraction
Detecting Face Parts and Overlaying Masks
Understanding HaarCascades
What Are Integral Images
Overlaying a Facemask in a Live Video
Get Your Sunglasses On
Tracking Your Nose, Mouth, and Ears
Video Surveillance, Background Modeling, and Morphological Operations
Background Subtraction
Frame Differencing
The Mixture of Gaussians Approach
Morphological Image processing
Other Morphological Operators
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
Developing Segmentation Algorithms for Text Recognition
Introducing Optical Character Recognition
The Preprocessing Step
Installing Tesseract OCR on Your Operating System
Using Tesseract OCR Library

Video Details

ISBN 139781787287259
Course Length

3 hours 57 minutes

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