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Emgu CV Essentials

Book Description

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

  • 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

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.

Table of Contents

  1. Emgu CV Essentials
    1. Table of Contents
    2. Emgu CV Essentials
    3. Credits
    4. About the Author
    5. About the Reviewers
    6. www.PacktPub.com
      1. Support files, eBooks, discount offers and more
        1. Why Subscribe?
        2. Free Access for Packt account holders
    7. Preface
      1. What this book covers
      2. What you need for this book
      3. Who this book is for
      4. Conventions
      5. Reader feedback
      6. Customer support
        1. Downloading the example code and graphics
        2. Errata
        3. Piracy
        4. Questions
    8. 1. Introduction to Emgu CV
      1. What is Emgu CV?
      2. Comparing image-processing libraries
        1. License agreement
        2. Documentation and other material
        3. Ease of use
        4. Performance
        5. Summary of the comparison
      3. Advantages of Emgu CV
        1. Cross-platform
        2. Cross-language support with examples
        3. Other advantages
      4. Summary
    9. 2. Installing Emgu CV
      1. Downloading Emgu CV
      2. Installing Emgu CV
        1. Installing on Windows
        2. Installing on Linux
          1. Getting the dependency
            1. Fedora
            2. Ubuntu
          2. Building Emgu CV from source
        3. Installing on OS X
          1. Getting the dependency
          2. Building Emgu CV from source
      3. Troubleshooting
        1. Windows
        2. Linux
        3. OS X
      4. Summary
    10. 3. Hello World
      1. Hello World in C#
        1. Creating a new project
        2. Designing our form
        3. Coding
        4. Output
      2. Hello World in VB.NET
      3. Hello World in C++
      4. Summary
    11. 4. Wrapping OpenCV
      1. Architecture overview
        1. OpenCV
        2. Emgu CV
      2. Function mapping
      3. Structure mapping
      4. Enumeration mapping
      5. Summary
    12. 5. Working with Images
      1. Digital image representation
        1. Pixels and data
        2. Pixel resolution
        3. Color image representation
        4. Color depth
      2. Working with images
        1. Creating an image
        2. Loading an image from a file
        3. Operations with pixels
        4. Method naming rules
        5. Using operator overload
        6. Generic operations support
        7. Garbage collection
        8. XML serialization
      3. Summary
    13. 6. Working with Matrices
      1. Matrix and the Image class
      2. Definition and parameters
      3. Working with matrices
        1. Creating a matrix
        2. Operations with elements
      4. Summary
    14. 7. Shape Detection
      1. Canny Edge Detector
      2. Hough transforms
        1. Hough Line transform
        2. Hough Circle transform
      3. Contour
        1. Contour finding
        2. Representation of contours
          1. Sequences of vertexes
          2. Free chain codes
        3. Drawing contours
        4. Polygon approximations
        5. A contours example
      4. Summary
    15. 8. Face Detection
      1. Biometric systems
      2. Camera captures
      3. Machine learning
      4. Face detection or the Haar classifier
        1. Boosting theory and supervised learning
        2. Haar-like features
        3. Code for face detection
      5. Summary
    16. 9. License Plate Recognition
      1. License Plate Recognition
        1. Algorithms for LPR
      2. OCR
      3. Tesseract-OCR
      4. Code for License Plate Recognition
        1. Assumption
        2. Source code
          1. GetWhitePixelMask
          2. DetectLicensePlate
          3. FindLicensePlate
        3. Output
      5. Summary
    17. 10. Image Stitching
      1. Image stitching
      2. Algorithms for image stitching
        1. Image matching
        2. Image calibration
        3. Image blending
      3. Code
      4. Summary
    18. Index