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OpenCV By Example

You're reading from   OpenCV By Example Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3

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Product type Paperback
Published in Jan 2016
Publisher Packt
ISBN-13 9781785280948
Length 296 pages
Edition 1st Edition
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Authors (3):
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Vinícius G. Mendonça Vinícius G. Mendonça
Author Profile Icon Vinícius G. Mendonça
Vinícius G. Mendonça
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with OpenCV 2. An Introduction to the Basics of OpenCV FREE CHAPTER 3. Learning the Graphical User Interface and Basic Filtering 4. Delving into Histograms and Filters 5. Automated Optical Inspection, Object Segmentation, and Detection 6. Learning Object Classification 7. Detecting Face Parts and Overlaying Masks 8. Video Surveillance, Background Modeling, and Morphological Operations 9. Learning Object Tracking 10. Developing Segmentation Algorithms for Text Recognition 11. Text Recognition with Tesseract Index

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
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