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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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Toc

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 foreground objects with the GrabCut algorithm

OpenCV proposes the implementation of another popular algorithm for image segmentation—the GrabCut algorithm. This algorithm is not based on mathematical morphology, but we have presented it here since it shows some similarities in its use with the watershed segmentation algorithm we presented earlier in this chapter. GrabCut is computationally more expensive than watershed, but it generally produces more accurate results. It is the best algorithm to use when you want to extract a foreground object in a still image (for example, to cut and paste an object from one picture to another).

How to do it...

The cv::grabCut function is easy to use. You just need to input...

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