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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

Extracting the foreground objects in a video

When a fixed camera observes a scene, the background remains mostly unchanged. In this case, the interesting elements are the moving objects that evolve inside this scene. In order to extract these foreground objects, we need to build a model of the background, and then compare this model with a current frame in order to detect any foreground objects. This is what we will do in this recipe. Foreground extraction is a fundamental step in intelligent surveillance applications.

If we had an image of the background of the scene (that is, a frame that contains no foreground objects) at our disposal, then it would be easy to extract the foreground of a current frame through a simple image difference:

  // compute difference between current image and background
  cv::absdiff(backgroundImage,currentImage,foreground);

Each pixel for which this difference is high enough would then be declared as a foreground pixel. However, most of the time, this background...

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