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OpenCV Computer Vision Application Programming Cookbook Second Edition

You're reading from   OpenCV Computer Vision Application Programming Cookbook Second Edition Over 50 recipes to help you build computer vision applications in C++ using the OpenCV library

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Product type Paperback
Published in Aug 2014
Publisher Packt
ISBN-13 9781782161486
Length 374 pages
Edition 1st Edition
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Author (1):
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Robert Laganiere Robert Laganiere
Author Profile Icon Robert Laganiere
Robert Laganiere
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Table of Contents (13) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating 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. Processing Video Sequences Index

Opening and closing images using morphological filters


The previous recipe introduced you to the two fundamental morphological operators: dilation and erosion. From these, other operators can be defined. The next two recipes will present some of them. The opening and closing operators are presented in this recipe.

How to do it...

In order to apply higher-level morphological filters, you need to use the cv::morphologyEx function with the appropriate function code. For example, the following call will apply the closing operator:

   cv::Mat element5(5,5,CV_8U,cv::Scalar(1));
   cv::Mat closed;
   cv::morphologyEx(image,closed,cv::MORPH_CLOSE,element5);

Note that we used a 5 x 5 structuring element to make the effect of the filter more apparent. If we use the binary image of the preceding recipe as input, we will obtain an image similar to what's shown in the following screenshot:

Similarly, applying the morphological opening operator will result in the following screenshot:

The preceding image is...

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