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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

Computing components' shape descriptors


A connected component often corresponds to the image of an object in a pictured scene. To identify this object, or to compare it with other image elements, it can be useful to perform some measurements on the component in order to extract some of its characteristics. In this recipe, we will look at some of the shape descriptors available in OpenCV that can be used to describe the shape of a connected component.

How to do it...

Many OpenCV functions are available when it comes to shape description. We will apply some of them on the components that we have extracted in the preceding recipe. In particular, we will use our vector of four contours corresponding to the four buffaloes we previously identified. In the following code snippets, we compute a shape descriptor on the contours (contours[0] to contours[3]) and draw the result (with a thickness of 2) over the image of the contours (with a thickness of 1). This image is shown at the end of this section...

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