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OpenCV 4 Computer Vision Application Programming Cookbook

You're reading from   OpenCV 4 Computer Vision Application Programming Cookbook Build complex computer vision applications with OpenCV and C++

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789340723
Length 494 pages
Edition 4th Edition
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Authors (2):
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Robert Laganiere Robert Laganiere
Author Profile Icon Robert Laganiere
Robert Laganiere
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
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Table of Contents (17) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating the Pixels 3. Processing Color Images with Classes 4. Counting the Pixels with Histograms 5. Transforming Images with Morphological Operations 6. Filtering the Images 7. Extracting Lines, Contours, and Components 8. Detecting Interest Points 9. Describing and Matching Interest Points 10. Estimating Projective Relations in Images 11. Reconstructing 3D Scenes 12. Processing Video Sequences 13. Tracking Visual Motion 14. Learning from Examples 15. OpenCV Advanced Features 16. Other Books You May Enjoy

Extracting the components' contours

Images generally contain representations of objects. One of the goals of image analysis is to identify and extract these objects. In object detection/recognition applications, the first step is often to produce a binary image that shows you where certain objects of interest could be located. No matter how this binary map is obtained (for example, from the histogram back projection as we did in Chapter 4, Counting the Pixels with Histograms, or from motion analysis as we will learn in Chapter 11, Reconstructing 3D Scenes), the next step is to extract the objects that are contained in this collection of one's and zero's. Consider, for example, the image of buffaloes in a binary form that we manipulated in Chapter 5, Transforming Images with Morphological Operations, as shown in the following image:

We obtained this image from a...

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