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OpenCV Essentials

You're reading from   OpenCV Essentials Acquire, process, and analyze visual content to build full-fledged imaging applications using OpenCV

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Product type Paperback
Published in Aug 2014
Publisher
ISBN-13 9781783984244
Length 214 pages
Edition 1st Edition
Tools
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Toc

Table of Contents (10) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Something We Look At – Graphical User Interfaces 3. First Things First – Image Processing 4. What's in the Image? Segmentation 5. Focusing on the Interesting 2D Features 6. Where's Wally? Object Detection 7. What Is He Doing? Motion 8. Advanced Topics Index

Scene text detection


The scene text detection algorithm builds a component tree of an image by thresholding it step-by-step from 0 to 255. To enhance the results, this process is done for each color channel, intensity, and gradient magnitude images. After that, the connected components obtained from successive levels are hierarchically organized depending on their inclusion relationship as shown in the following diagram. This tree organization may contain a huge number of regions:

Tree organization example

Thus, the algorithm selects some regions following two stages. Firstly, area, perimeter, bounding box, and Euler number descriptors are computed for each region and used in order to estimate the class-condition probability. External regions with local maximum probabilities are selected if their values are above a global limit and the difference between their local maximum and minimum is also above a specified limit.

The second stage consists of classifying the external regions selected in...

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