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OpenCV 3 Computer Vision Application Programming Cookbook

You're reading from   OpenCV 3 Computer Vision Application Programming Cookbook Recipes to make your applications see

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Product type Paperback
Published in Feb 2017
Publisher
ISBN-13 9781786469717
Length 474 pages
Edition 3rd 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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Toc

Table of Contents (15) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating Pixels 3. Processing the Colors of an Image 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

Reading video sequences

In order to process a video sequence, we need to be able to read each of its frames. OpenCV has put in place an easy-to-use framework that can help us perform frame extraction from video files or even from USB or IP cameras. This recipe shows you how to use it.

How to do it...

Basically, all you need to do in order to read the frames of a video sequence is create an instance of the cv::VideoCapture class. You then create a loop that will extract and read each video frame. Here is a basic main function that displays the frames of a video sequence:

    int main() 
    { 
      // Open the video file 
      cv::VideoCapture capture("bike.avi"); 
      // check if video successfully opened 
      if (!capture.isOpened()) 
        return 1; 
 
      // Get the frame rate 
      double rate= capture.get(CV_CAP_PROP_FPS); 
 
      bool stop(false); 
      cv::Mat frame;    // current video frame 
      cv::namedWindow("Extracted Frame"); 
 
      // Delay...
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