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OpenCV Computer Vision Application Programming Cookbook Second Edition

OpenCV Computer Vision Application Programming Cookbook Second Edition

By : Robert Laganiere
3.7 (3)
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OpenCV Computer Vision Application Programming Cookbook Second Edition

OpenCV Computer Vision Application Programming Cookbook Second Edition

3.7 (3)
By: Robert Laganiere

Overview of this book

OpenCV 3 Computer Vision Application Programming Cookbook is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers wishing to be introduced to the concepts of computer vision programming. It can also be used as a companion book in a university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision.
Table of Contents (13 chapters)
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12
Index

Backprojecting a histogram to detect specific image content


A histogram is an important characteristic of an image's content. If you look at an image area that shows a particular texture or a particular object, then the histogram of this area can be seen as a function that gives the probability that a given pixel belongs to this specific texture or object. In this recipe, you will learn how the concept of histogram backprojection can be advantageously used to detect specific image content.

How to do it...

Suppose you have an image and you wish to detect specific content inside it (for example, in the following image, the clouds in the sky). The first thing to do is to select a region of interest that contains a sample of what you are looking for. This region is the one inside the rectangle drawn on the following test image:

In our program, the region of interest is obtained as follows:

   cv::Mat imageROI;
   imageROI= image(cv::Rect(216,33,24,30)); // Cloud region

You then extract the histogram...

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