Emgu CV Essentials

Emgu CV Essentials
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Table of Contents
Sample Chapters
  • 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

Book Details

Language : English
Paperback : 118 pages [ 235mm x 191mm ]
Release Date : November 2013
ISBN : 1783559527
ISBN 13 : 9781783559527
Author(s) : Shin Shi
Topics and Technologies : All Books, Other

Table of Contents

Chapter 1: Introduction to Emgu CV
Chapter 2: Installing Emgu CV
Chapter 3: Hello World
Chapter 4: Wrapping OpenCV
Chapter 5: Working with Images
Chapter 6: Working with Matrices
Chapter 7: Shape Detection
Chapter 8: Face Detection
Chapter 9: License Plate Recognition
Chapter 10: Image Stitching
  • Chapter 1: Introduction to Emgu CV
    • What is Emgu CV?
    • Comparing image-processing libraries
      • License agreement
      • Documentation and other material
      • Ease of use
      • Performance
      • Summary of the comparison
    • Advantages of Emgu CV
      • Cross-platform
      • Cross-language support with examples
      • Other advantages
    • Summary
    • Chapter 2: Installing Emgu CV
      • Downloading Emgu CV
      • Installing Emgu CV
        • Installing on Windows
        • Installing on Linux
          • Getting the dependency
          • Building Emgu CV from source
        • Installing on OS X
          • Getting the dependency
          • Building Emgu CV from source
      • Troubleshooting
        • Windows
        • Linux
        • OS X
      • Summary
      • Chapter 3: Hello World
        • Hello World in C#
          • Creating a new project
          • Designing our form
          • Coding
          • Output
        • Hello World in VB.NET
        • Hello World in C++
        • Summary
          • Chapter 5: Working with Images
            • Digital image representation
              • Pixels and data
              • Pixel resolution
              • Color image representation
              • Color depth
            • Working with images
              • Creating an image
              • Loading an image from a file
              • Operations with pixels
              • Method naming rules
              • Using operator overload
              • Generic operations support
              • Garbage collection
              • XML serialization
            • Summary
              • Chapter 7: Shape Detection
                • Canny Edge Detector
                • Hough transforms
                  • Hough Line transform
                  • Hough Circle transform
                • Contour
                  • Contour finding
                  • Representation of contours
                    • Sequences of vertexes
                    • Free chain codes
                  • Drawing contours
                  • Polygon approximations
                  • A contours example
                • Summary
                • Chapter 8: Face Detection
                  • Biometric systems
                  • Camera captures
                  • Machine learning
                  • Face detection or the Haar classifier
                    • Boosting theory and supervised learning
                    • Haar-like features
                    • Code for face detection
                  • Summary
                  • Chapter 9: License Plate Recognition
                    • License Plate Recognition
                      • Algorithms for LPR
                    • OCR
                    • Tesseract-OCR
                    • Code for License Plate Recognition
                      • Assumption
                      • Source code
                        • GetWhitePixelMask
                        • DetectLicensePlate
                        • FindLicensePlate
                      • Output
                    • Summary
                    • Chapter 10: Image Stitching
                      • Image stitching
                      • Algorithms for image stitching
                        • Image matching
                        • Image calibration
                        • Image blending
                      • Code
                      • Summary

                      Shin Shi

                      Shin Shi is a member of the Digital Art Lab at Shanghai Jiao Tong University. When he built his first robot at the age of fourteen in 2005, he became interested in the field of computer vision. Over the last two years, he created a real-time face recognition attendance system using Emgu CV at Huazhong University of Science and Technology. He obtained a B.E. in Software Engineering from HUST and is currently an M.S. candidate in DA Lab from SJTU. Now he is focusing on the field of computer graphics, such as creating physics-based simulations and the use of animation.

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                      Sample chapters

                      You can view our sample chapters and prefaces of this title on PacktLib or download sample chapters in PDF format.

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                      What you will learn from this book

                      • 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.


                      This book provides a practical guide to Emgu CV libraries, with sample code and examples used throughout to explain the concepts clearly. Each chapter deals with a different aspect of the Computer Vision field and the implementation of that topic in Emgu CV.

                      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#.

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