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OpenCV By Example

You're reading from   OpenCV By Example Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3

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Product type Paperback
Published in Jan 2016
Publisher Packt
ISBN-13 9781785280948
Length 296 pages
Edition 1st Edition
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Authors (3):
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Vinícius G. Mendonça Vinícius G. Mendonça
Author Profile Icon Vinícius G. Mendonça
Vinícius G. Mendonça
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
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with OpenCV FREE CHAPTER 2. An Introduction to the Basics of OpenCV 3. Learning the Graphical User Interface and Basic Filtering 4. Delving into Histograms 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 Index

Using the text API

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

Text detection

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

First, we start with including all the necessary libs and using:

#include  "opencv2/highgui.hpp"
#include  "opencv2/imgproc.hpp"
#include  "opencv2/text.hpp"

#include  <vector>
#include  <iostream>

using namespace std;
using namespace cv;
using namespace cv::text;

Recall from our previous section that the ERFilter works separately in each image channel. So, we must provide a way to separate each desired channel in a different single cv::Mat channel. This is done by the separateChannels...

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