E-Book Overview
Learning OpenCV 3.0 puts you in the middle of the 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. It’s thoroughly updated to cover new features and changes in OpenCV 3.0.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. написал: (3 февраля 2017 18:01)
E-Book Content
Preface This book provides a working guide to the Open Source Computer Vision Library (OpenCV) and also provides a general background to the field of computer vision sufficient to use OpenCV effectively. Purpose Computer vision is a rapidly growing field, partly as a result of both cheaper and more capable cameras, partly because of affordable processing power, and partly because vision algorithms are starting to mature. OpenCV itself has played a role in the growth of computer vision by enabling thousands of people to do more productive work in vision. With its focus on real-time vision, OpenCV helps students and professionals efficiently implement projects and jump-start research by providing them with a computer vision and machine learning infrastructure that was previously available only in a few mature research labs. The purpose of this text is to: • Better document OpenCV—detail what function calling conventions really mean and how to use them correctly. • Rapidly give the reader an intuitive understanding of how the vision algorithms work. • Give the reader some sense of what algorithm to use and when to use it. • Give the reader a boost in implementing computer vision and machine learning algorithms by providing many working coded examples to start from. • Provide intuitions about how to fix some of the more advanced routines when something goes wrong. Simply put, this is the text the authors wished we had in school and the coding reference book we wished we had at work. This book documents a tool kit, OpenCV, that allows the reader to do interesting and fun things rapidly in computer vision. It gives an intuitive understanding as to how the algorithms work, which serves to guide the reader in designing and debugging vision applications and also to make the formal descriptions of computer vision and machine learning algorithms in other texts easier to comprehend and remember. After all, it is easier to understand complex algorithms and their associated math when you start with an intuitive grasp of how those algorithms work. Who This Book Is For This book contains descriptions, working coded examples, and explanations of the computer vision tools contained in the OpenCV library. As such, it should be helpful to many different kinds of users. Professionals For those practicing professionals who need to rapidly implement computer vision systems, the sample code provides a quick framework with which to start. Our descriptions of the intuitions behind the algorithms can quickly teach or remind the reader how they work. Students As we said, this is the text we wish had back in school. The intuitive explanations, detailed documentation, and sample code will allow you to boot up faster in computer vision, work on more interesting class projects, and ultimately contribute new research to the field. Teachers Computer vision is a fast-