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Learn OpenCV 4 by Building Projects

You're reading from   Learn OpenCV 4 by Building Projects Build real-world computer vision and image processing applications with OpenCV and C++

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789341225
Length 310 pages
Edition 2nd Edition
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Authors (3):
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David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
Vinícius G. Mendonça Vinícius G. Mendonça
Author Profile Icon Vinícius G. Mendonça
Vinícius G. Mendonça
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with OpenCV 2. An Introduction to the Basics of OpenCV FREE CHAPTER 3. Learning Graphical User Interfaces 4. Delving into Histogram and Filters 5. Automated Optical Inspection, Object Segmentation, and Detection 6. Learning Object Classification 7. Detecting Face Parts and Overlaying Masks 8. Video Surveillance, Background Modeling, and Morphological Operations 9. Learning Object Tracking 10. Developing Segmentation Algorithms for Text Recognition 11. Text Recognition with Tesseract 12. Deep Learning with OpenCV 13. Other Books You May Enjoy

Using the text API

Enough theory. It's time to see how the text module works in practice. Let's study how we can use it to perform text detection, extraction, and identification.

Text detection

Let's start by creating a simple program so that we can perform text segmentation using ERFilters. In this program, we will use the trained classifiers from text API samples. You may download this from the OpenCV repository, but they are also available in this book's companion code.

First, we start by including all of the necessary libs and usings:

#include  "opencv2/highgui.hpp" 
#include  "opencv2/imgproc.hpp" 
#include  "opencv2/text.hpp" 
 
#include  <vector> 
#include  &lt...
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