Search icon CANCEL
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 3 Computer Vision Application Programming Cookbook

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

Arrow left icon
Product type Paperback
Published in Feb 2017
Publisher
ISBN-13 9781786469717
Length 474 pages
Edition 3rd Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Robert Laganiere Robert Laganiere
Author Profile Icon Robert Laganiere
Robert Laganiere
Arrow right icon
View More author details
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

Processing the video frames

In this recipe, our objective is to apply some processing functions to each of the frames of a video sequence. We will do this by encapsulating the OpenCV video capture framework into our own class. Among other things, this class will allow us to specify a function that will be called each time a new frame is extracted.

How to do it...

What we want is to be able to specify a processing function (a callback function) that will be called for each frame of a video sequence. This function can be defined as receiving a cv::Mat instance and outputting a processed frame. Therefore, in our framework, the processing function must have the following signature to be a valid callback:

    void processFrame(cv::Mat& img, cv::Mat& out); 

As an example of such a processing function, consider the following simple function that computes the Canny edges of an input image:

    void canny(cv::Mat& img, cv::Mat& out) { 
      // Convert to gray 
      if (img.channels...
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