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

Chapter 11. Text Recognition with Tesseract

In the previous chapter, 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 3.0 text module, which deals specifically with scene text detection. Using this API, it is possible to detect 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 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:

  • Understand what is scene text recognition

  • Understand how the text API works

  • Use the OpenCV 3.0 text API to detect text

  • Extract the detected text to an image

  • Use the text API and Tesseract integration to identify letters