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**Free e-Book Learning OpenCV**

**Author(s): Gary Bradski, Adrian Kaehler**

**Publisher: O'Reilly, Year: 2008**

**ISBN: 0596516134,978-0-596-51613-0**

**Describe**

**The book provides a practical guide to an open source computer vision library**

**(OpenCV) provides general background on enough computing field to use OpenCV effectively.**

**Goal**

**Computer vision is a rapidly growing field, partly due to both cheaper and more**

**Capable cameras, partly due to reasonable processing power, and partly because vision algorithms are starting to mature. OpenCV itself played a role in growth**

**Computer vision by enabling thousands of people to do more productive work in vision.**

**With its focus on real-time visibility, OpenCV helps students and professionals efficiently**

**Implement projects and start research by providing them with a computer vision**

**And machine learning infrastructure previously available only at a few maturity**

**Research laboratories. The purpose of this text is to:**

**Better OpenCV Document - detailing the meaning of job calling conventions**

**And how to use it properly.**

**• Quickly give the reader an intuitive understanding of how to use vision algorithms**

**Action.**

**Give the reader an idea of the algorithm to use and when to use it.**

**• Give the reader a boost in implementing computer vision and machine learning algorithms by providing many coded examples working to start from them.**

**• Provide ideas on how to fix some of the more advanced procedures when something goes wrong.**

**Simply put, this is the text that school authors wished for and the coding reference**

**A book we wish we could have at work.**

**This book documents a toolkit, OpenCV, that allows the reader to do interesting work**

**Fun things quickly see the computer.**

**It gives an intuitive understanding of how**

**Algorithms, which guide the reader in designing and correcting the vision**

**Applications as well as to make official descriptions of computer vision and machine**

**Learning algorithms in other texts are easier to understand and remember.**

**After all, it is easier to understand the complex algorithms and mathematics associated with them when**

**You begin with an intuitive understanding of how these algorithms work.**

**For whom is this book**

**This book is for new developers on OpenCV and they want to develop their own computers Visibility applications using OpenCV in C ++.**

**It will be basic knowledge of C ++ Good for understanding this book.**

**This book is also useful for anyone who wants it Start with computer vision and understand basic concepts.**

**they You should be familiar with basic mathematical concepts, such as vectors, matrices, and matrix Multiplication, etc. to get the most out of this book.**

**during This book, you will learn how to build different computer vision applications from Scan with OpenCV.**

**Agreements**

**In this book, you will get a number of text styles that distinguish between**

**Various types of information. Here are some examples of these patterns, and**

**Explain its meaning.**

**Code words are displayed in the text as follows: "For a basic project based on an executable file Build from a single source code, all you need from the CMakeLists.txt line. "**

**What is not this book**

**This book is not an official text. We go into mathematical details at various points, * however All this at the service of developing a deeper intuition behind algorithms or for clarity Implications for any assumptions included in those algorithms. We did not try A formal sports show is here and might cause some anger along the way**

**Of those who write official exhibitions.**

**This book is not for theorists as it contains more "applied" nature. the book It will definitely be a general help, but it doesn't target any of the niches for computer vision (for example, medical imaging or remote sensing analysis).**

**In it, the authors believe that after reading the interpretations here first, the student will not only learn the theory better, but rather remember it for a longer period.**

**Before that, this book**

**It will make a good helpful text for a theoretical course and it will be a great text for**

**Introductory or project-focused course.**

**About programs in this book**

**All program examples in this book are based on OpenCV version 2.0. Should symbol**

**It definitely works with Linux or Windows and maybe under OS-X as well. Source code**

**Examples in the book can be obtained from the book's website**

**(http: //www.oreilly Com / catalog / 9780596516130).**

**OpenCV can be downloaded from its source forgery website**

**(http: // sourceforge.net/projects/opencvlibrary).**

**OpenCV is in constant development, with official releases once or twice**

**Year. As a general rule, you should obtain your code updates from source formulation**

**CVS Server (http://sourceforge.net/cvs/?group_id=22870).**

**Basic requirements**

**For the most part, readers only need to know how to code in C and perhaps some C++.**

**Many mathematics departments are optional and are classified accordingly.**

**Mathematics includes simple algebra and basic algebra for the matrix, and assumes some familiarity with the methods of solving problems of improving least squares in addition to some basic knowledge Gaussian distributions, Pays law and simple function derivatives.**

**Mathematics supports the development of intuition for algorithms. The reader may skip Mathematics and algorithm descriptions, using only function and code definitions**

**Examples of getting and running vision applications.**

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