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

Chapter 11. Text Recognition with Tesseract

In Chapter 10, Developing Segmentation Algorithms for Text Recognition, we covered the very basic OCR processing functions. Although they are quite useful for scanned or photographed documents, they are almost useless when dealing with text that casually appears in a picture.

In this chapter, we'll explore the OpenCV 4.0 text module, which deals specifically with scene text detection. Using this API, it is possible to detect the text that appears in a webcam video, or to analyze photographed images (like the ones in Street View or taken by a surveillance camera) to extract text information in real time. This allows for a wide range of applications to be created, from accessibility, to marketing, and even robotics fields.

By the end of this chapter, you will be able to do the following:

  • Understand what scene text recognition is
  • Understand how the text API works
  • Use the OpenCV 4.0 text API to detect text
  • Extract the detected text into an image
  • Use the text...