Book Image

Learn OpenCV 4 By Building Projects - Second Edition

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

Learn OpenCV 4 By Building Projects - Second Edition

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

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. Whether you’re completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects – Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. You’ll begin with the installation of OpenCV and the basics of image processing. Then, you’ll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module. By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch.
Table of Contents (14 chapters)

Developing Segmentation Algorithms for Text Recognition

In the previous chapters, we learned about a wide range of image processing techniques such as thresholding, contours descriptors, and mathematical morphology. In this chapter, we will discuss common problems that you may face while 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 those problems. By the end of this chapter, we will have segmented regions of text that can be sent to an optical character recognition (OCR) library.

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

  • What kind of OCR applications exists?
  • What are the common problems while writing an OCR application?
  • How do I identify regions of documents?
  • How do I deal with problems like skewing...