"This library is useful for practitioners, and is an excellent tool for those entering the it is a set of computer vision algorithms that work as advertised." -William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology
Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to "see" and make decisions based on that data.
Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time.
Learning OpenCV will teach any developer or hobbyist to use the framework quickly with the help of hands-on exercises in each chapter. This book Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started.
If you are a serious computer vision researcher, you should consider to read this book. I started to use OpenCV since its beta version, and now I am still using the latest version. OpenCV helps me a lot in building real-time application that requires fast computation. Five stars for OpenCV authors, thanks for sharing a useful software and book for the rest of us
Complete material of what is OpenCV. The programming of computer vision. Theory, basis, implementation, and it's explanation. Including viewed from the physics science, it's describing it with a simple way but clear enough.
It was an ok introduction back when I read it, but new, matlab inspired, C++ API of OpenCV 2.0 weren't around back then, so the code samples are to a great extent outdated.