Augmented reality, driving assistance, video monitoring; more and more applications are now using computer vision and image analysis technologies, and yet we are still in the infancy of the development of new computerized systems capable of understanding our world through the sense of vision. And with the advent of powerful and affordable computing devices and visual sensors, it has never been easier to create sophisticated imaging applications.
A multitude of software tools and libraries manipulating images and videos are available, but for anyone who wishes to develop smart vision-based applications, the OpenCV library is the tool to use. OpenCV is an open source library containing 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, which proposed important changes, especially the new C++ interface, which we use in this book. In 2012, OpenCV reshaped itself as a non-profit foundation (https://opencv.org/) relying on crowdfunding for its future development.
OpenCV 3 was introduced in 2013; changes were made mainly to improve the usability of the library. Its structure has been revised to remove the unnecessary dependencies, large modules have been split into smaller ones, and the API has been refined. This book is the fourth edition of OpenCV Computer Vision Application Programming Cookbook, and the first one that covers OpenCV 4. All the programming recipes of the previous editions have been reviewed and updated. We have also added new content and new chapters to provide readers with even better coverage of the essential functionalities of the library.
This book covers many of the library's features and explains 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. We also explore fundamental concepts in image analysis, and 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—but this is just the beginning. The good news is that OpenCV continues to evolve and expand. Just consult the OpenCV online documentation at https://opencv.org/ to stay updated about what the library can do for you. You can also visit the author’s website at http://www.laganiere.name/ for updated information about this cookbook.