Book Image

OpenCV By Example

By : Prateek Joshi, David Millán Escrivá, Vinícius G. Mendonça
Book Image

OpenCV By Example

By: Prateek Joshi, David Millán Escrivá, Vinícius G. Mendonça

Overview of this book

Open CV is a cross-platform, free-for-use library that is primarily used for real-time Computer Vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. Whether you are completely new to the concept of Computer Vision or have a basic understanding of it, this book will be your guide to understanding the basic OpenCV concepts and algorithms through amazing real-world examples and projects. Starting from the installation of OpenCV on your system and understanding the basics of image processing, we swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly used Computer Vision techniques to build your own Open CV projects from scratch. By the end of this book, you will be familiar with the basics of Open CV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition.
Table of Contents (18 chapters)
OpenCV By Example
About the Authors
About the Reviewers

Using Tesseract OCR library

As Tesseract OCR is already integrated with OpenCV 3.0, it still worth studying its API since it allows a finer-grained control over Tesseract parameters. The integration will be studied in the next chapter.

Creating a OCR function

We'll change the previous example to work with Tesseract. We will start with adding baseapi and fstream tesseracts to the list:

#include <opencv2/opencv.hpp>
#include <tesseract/baseapi.h>

#include <vector>
#include <fstream>

Then, we'll create a global TessBaseAPI object that represents our Tesseract OCR engine:

tesseract::TessBaseAPI ocr;


The ocr engine is completely self-contained. If you want to create multithreaded OCR software, just add a different TessBaseAPI object to each thread, and the execution will be fairly thread-safe. You just need to guarantee that file writing is not done over the same file; otherwise, you'll need to guarantee safety for this operation.

Next, we will create a function called identify...