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
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Chapter 10. Developing Segmentation Algorithms for Text Recognition

In the previous chapters, we learned about a wide range of image processing techniques, such as thresholding, contour descriptors, and mathematical morphology. In this chapter, we will discuss the common problems with dealing with scanned documents, such as identifying where the text is or adjusting its rotation. We will also learn how to combine techniques presented in the previous chapters to solve these problems. Finally, we'll have segmented regions of text that can be sent to an OCR (optical character recognition) library.

By the end of this chapter, you should be able to answer the following questions:

  • What kind of OCR applications exist?

  • What are the common problems while writing an OCR application?

  • How do we identify regions of documents?

  • How do we deal with problems such as skewing and other elements in the middle of the text?

  • How do we use Tesseract OCR to identify the text?