Emgu CV Essentials

Develop your own computer vision application using the power of Emgu CV

Emgu CV Essentials

Starting
Shin Shi

Develop your own computer vision application using the power of Emgu CV
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Book Details

ISBN 139781783559527
Paperback118 pages

About This Book

  • Packed with clear explanations and examples of how to deal with computer vision problems in Emgu CV
  • Learn the main features of Emgu CV from the basics to more advanced techniques
  • Each chapter covers a different computer vision application and teaches developers how to implement it using EmguCV

Who This Book Is For

If you are a C# programmer working on computer vision projects, this book is for you. You should have prior experience with C#.

Table of Contents

Chapter 1: Introduction to Emgu CV
What is Emgu CV?
Comparing image-processing libraries
Advantages of Emgu CV
Summary
Chapter 2: Installing Emgu CV
Downloading Emgu CV
Installing Emgu CV
Troubleshooting
Summary
Chapter 3: Hello World
Hello World in C#
Hello World in VB.NET
Hello World in C++
Summary
Chapter 4: Wrapping OpenCV
Architecture overview
Function mapping
Structure mapping
Enumeration mapping
Summary
Chapter 5: Working with Images
Digital image representation
Working with images
Summary
Chapter 6: Working with Matrices
Matrix and the Image class
Definition and parameters
Working with matrices
Summary
Chapter 7: Shape Detection
Canny Edge Detector
Hough transforms
Contour
Summary
Chapter 8: Face Detection
Biometric systems
Camera captures
Machine learning
Face detection or the Haar classifier
Summary
Chapter 9: License Plate Recognition
License Plate Recognition
OCR
Tesseract-OCR
Code for License Plate Recognition
Summary
Chapter 10: Image Stitching
Image stitching
Algorithms for image stitching
Code
Summary

What You Will Learn

  • Install Emgu CV across multiple platforms
  • Understand the advantages of Emgu CV, and generate a “Hello World” computer vision project
  • Harness the power of Emgu CV methods to perform shape detection
  • Work on matrices and images using Emgu CV methods
  • Perform face and eye detection with Haar Classifier
  • Implement license plate detection and optical character recognition using OCR namespaces

In Detail

Computer vision is an up and coming field within the field of Computer Science that combines image processing with machine learning. Emgu CV is a cross-platform library that can be used to practically explore really interesting features from image capturing to character recognition.

Emgu CV Essentials is a practical guide to the Emgu CV library, a .Net wrapper for the OpenCV image processing library. The main features and code samples are explained in order to give a better understanding of Emgu CV, with a wide variety of topics covered, from working with images and shape detection to creating a panorama from a series of images.

Learn the basics of Emgu CV, from creating your first project to covering the main areas of the computer vision field, with Emgu CV Essentials. Each chapter presents a separate project to the reader, and provides the background knowledge necessary to understand how the examples work. Learn how to start with EmguCV and try practical computer vision projects, or go straight to the topics you are most interested in, such as image processing, shape detection, face detection, optical character recognition, and more.

Emgu CV Essentials gives you the chance to explore the main areas of computer vision with helpful projects.

Authors

Table of Contents

Chapter 1: Introduction to Emgu CV
What is Emgu CV?
Comparing image-processing libraries
Advantages of Emgu CV
Summary
Chapter 2: Installing Emgu CV
Downloading Emgu CV
Installing Emgu CV
Troubleshooting
Summary
Chapter 3: Hello World
Hello World in C#
Hello World in VB.NET
Hello World in C++
Summary
Chapter 4: Wrapping OpenCV
Architecture overview
Function mapping
Structure mapping
Enumeration mapping
Summary
Chapter 5: Working with Images
Digital image representation
Working with images
Summary
Chapter 6: Working with Matrices
Matrix and the Image class
Definition and parameters
Working with matrices
Summary
Chapter 7: Shape Detection
Canny Edge Detector
Hough transforms
Contour
Summary
Chapter 8: Face Detection
Biometric systems
Camera captures
Machine learning
Face detection or the Haar classifier
Summary
Chapter 9: License Plate Recognition
License Plate Recognition
OCR
Tesseract-OCR
Code for License Plate Recognition
Summary
Chapter 10: Image Stitching
Image stitching
Algorithms for image stitching
Code
Summary

Book Details

ISBN 139781783559527
Paperback118 pages
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