Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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++

Arrow left icon
Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789340723
Length 494 pages
Edition 4th Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
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
Arrow right icon
View More author details
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 distinctive regions using MSER

In the previous recipe, you learned how an image can be segmented into regions by gradually flooding it and creating watersheds. The maximally stable external regions (MSER) algorithm uses the same immersion analogy in order to extract meaningful regions in an image. These regions will also be created by flooding the image level by level, but this time, we will be interested in the basins that remain relatively stable for a period of time during the immersion process. It will be observed that these regions correspond to some distinctive parts of the scene objects that are pictured in the image.

How to do it...

The basic class to compute the MSER of an image is cv::MSER. An instance...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image