Book Image

OpenCV Computer Vision Application Programming Cookbook Second Edition

By : Robert Laganiere
Book Image

OpenCV Computer Vision Application Programming Cookbook Second Edition

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 (18 chapters)
OpenCV Computer Vision Application Programming Cookbook Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Scanning an image with iterators


In object-oriented programming, looping over a data collection is usually done using iterators. Iterators are specialized classes that are built to go over each element of a collection, hiding how the iteration over each element is specifically done for a given collection. This application of the information-hiding principle makes scanning a collection easier and safer. In addition, it makes it similar in form no matter what type of collection is used. The Standard Template Library (STL) has an iterator class associated with each of its collection classes. OpenCV then offers a cv::Mat iterator class that is compatible with the standard iterators found in the C++ STL.

Getting ready

In this recipe, we again use the color reduction example described in the previous recipe.

How to do it...

An iterator object for a cv::Mat instance can be obtained by first creating a cv::MatIterator_ object. As is the case with cv::Mat_, the underscore indicates that this is a template...