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Mastering OpenCV with Practical Computer Vision Projects

You're reading from   Mastering OpenCV with Practical Computer Vision Projects This is the definitive advanced tutorial for OpenCV, designed for those with basic C++ skills. The computer vision projects are divided into easily assimilated chapters with an emphasis on practical involvement for an easier learning curve.

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Product type Paperback
Published in Dec 2012
Publisher Packt
ISBN-13 9781849517829
Length 340 pages
Edition 1st Edition
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Table of Contents (15) Chapters Close

Mastering OpenCV with Practical Computer Vision Projects
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Cartoonifier and Skin Changer for Android FREE CHAPTER 2. Marker-based Augmented Reality on iPhone or iPad 3. Marker-less Augmented Reality 4. Exploring Structure from Motion Using OpenCV 5. Number Plate Recognition Using SVM and Neural Networks 6. Non-rigid Face Tracking 7. 3D Head Pose Estimation Using AAM and POSIT 8. Face Recognition using Eigenfaces or Fisherfaces Index

Chapter 5. Number Plate Recognition Using SVM and Neural Networks

This chapter introduces us to the steps needed to create an application for Automatic Number Plate Recognition (ANPR). There are different approaches and techniques based on different situations, for example, IR cameras, fixed car positions, light conditions, and so on. We can proceed to construct an ANPR application to detect automobile license plates in a photograph taken between 2-3 meters from a car, in ambiguous light condition, and with non-parallel ground with minor perspective distortions of the automobile's plate.

The main purpose of this chapter is to introduce us to image segmentation and feature extraction, pattern recognition basics, and two important pattern recognition algorithms Support Vector Machines and Artificial Neural Networks. In this chapter, we will cover:

  • ANPR

  • Plate detection

  • Plate recognition

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