"This library is useful for practitioners, and is an excellent tool for those entering the field: 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 includes:

• A thorough introduction to OpenCV

• Getting input from cameras

• Transforming images

• Segmenting images and shape matching

• Pattern recognition, including face detection

• Tracking and motion in 2 and 3 dimensions

• 3D reconstruction from stereo vision

• Machine learning algorithms

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.

Amazon.com® Reader Reviews (Ranked by Helpfulness)

Average Amazon.com® Rating:  Based on 16 Ratings

A Great Book!!! - 2009-09-14
Reviewer Rating:
The book contains a quite complete description of OpenCV library. In addition to code examples a reader can find in many cases valuable mathematical background. The 3d Vision and Camera Calibration parts are especially interesting. The book material is very useful for practical software engineering goals as well as for algorithms research. Both beginners and professionals can consider this book as an excellent reference for the work.

Good book for practical Computer Vision - 2009-06-13
Reviewer Rating:
I'm a grad student in robotics and I found this book to be extremely practical for implementation of computer vision work. The only downside is that some of the work is not spelled out in as much detail as I would like. For example, some of the algorithms are easy to understand conceptually, but if I had to implement them, I would struggle a bit to do it from the details provided in the book. This book definitely fits the purpose of being a practical guide to computer vision.

Fantastic reference / textbook - 2009-10-09
Reviewer Rating:
Although I'm new to OpenCV and am only a few chapters into the book I already can tell that Using OpenCV is very well written and makes a fantastic source of information for the OpenCV project. Details are given as well as sample code that clearly explain the nuances of using this library. The authors make it clear that they intend this text to be used to teach/learn about using OpenCV and do a great job of covering the basics before moving on to more advanced topics.

Be aware you will need to be knowledgeable about the C language and need a decent math background. The former because OpenCV is written in C and the later because computer vision processing is math intensive and while OpenCV has man routines to handle the details you still need an understanding of the basic math involve to properly utilize them.

A hardcopy - 2009-10-08
Reviewer Rating:
This book reflects essentially what are in the several web sites, including OpenCv documentation. If you want a hardcopy of online documentation (as I wanted), then that's a nice option. However, don't expect be surprised by the contents of the book.

A good primer on Open CV - 2009-09-17
Reviewer Rating:
This book provides more background and context than found on the source library doc files. If, like me, you are new to computer vision, I'd strongly recommend giving it a read before starting to use the library. It starts with some of the basic concepts and the dives into the various key algorithms implemented in the library.

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