Book Image

Building Computer Vision Projects with OpenCV 4 and C++

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

Building Computer Vision Projects with OpenCV 4 and C++

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

Overview of this book

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: •Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá •Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi
Table of Contents (28 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Using the Tesseract OCR library


While Tesseract OCR is already integrated with OpenCV 3.0, it's still worth studying its API since it allows for finer grained control over Tesseract parameters. This integration will be studied in Chapter 11, Text Recognition with Tesseract.

Creating an OCR function

We'll change the previous example to work with Tesseract. Start by adding tesseract/baseapi.h and fstream to the include 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; 

Note

The ocr engine is completely self-contained. If you want to create a multi-threaded piece of OCR software, just add a different TessBaseAPI object in 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...