OpenCV (Open source Computer Vision) is an open source library that contains more than 500 optimized algorithms for image and video analysis. Since its introduction in 1999, it has been largely adopted as the primary development tool by the community of researchers and developers in computer vision. OpenCV was originally developed at Intel by a team led by Gary Bradski as an initiative to advance research in vision and promote the development of rich vision-based, CPU-intensive applications. After a series of beta releases, Version 1.0 was launched in 2006. A second major release occurred in 2009 with the launch of OpenCV 2 that proposed important changes, especially the new C++ interface that we use in this book. In 2012, OpenCV reshaped itself as a nonprofit foundation (http://opencv.org/) that relies on crowdfunding for its future development.

This book is a new edition of OpenCV Computer Vision Application Programming Cookbook. All the programming recipes of the previous editions have been reviewed and updated. We also have added new content to provide readers with even better coverage of the essential functionalities of the library. This book covers many of the library's features and shows you how to use them to accomplish specific tasks. Our objective is not to provide detailed coverage of every option offered by the OpenCV functions and classes, but rather to give you the elements you need to build your applications from the ground up. In this book, we also explore fundamental concepts in image analysis, and we describe some of the important algorithms in computer vision.

This book is an opportunity for you to get introduced to the world of image and video analysis. However, this is just the beginning. The good news is that OpenCV continues to evolve and expand. Just consult the OpenCV online documentation at http://opencv.org/ to stay updated on what the library can do for you. You can also visit the author's website at www.laganiere.name for updated information about this Cookbook.