Ebook OpenCV 2 Computer Vision Application Programming Cookbook
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OpenCV 2 Computer Vision Application Programming Cookbook
Ebook OpenCV 2 Computer Vision Application Programming Cookbook
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About the Author
Robert Laganière
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Product details
Paperback: 304 pages
Publisher: Packt Publishing (May 23, 2011)
Language: English
ISBN-10: 9781849513241
ISBN-13: 978-1849513241
ASIN: 1849513244
Product Dimensions:
7.5 x 0.7 x 9.2 inches
Shipping Weight: 1.5 pounds (View shipping rates and policies)
Average Customer Review:
3.6 out of 5 stars
24 customer reviews
Amazon Best Sellers Rank:
#1,365,146 in Books (See Top 100 in Books)
I had already read the original Bradsky and Kaehler "Learning OpenCV" which was written against the original C interface, but later updated to OpenCV 2.3 with the new C++ interface. The new interface is much easier to work with and the OpenCV 2 Cookbook is a very good introduction. It touches on many of the capabilities of OpenCV and gives examples on how to use OpenCV for specific purposes. It's impossible for an introductory computer vision book to go into too much detail--any one of the topics could be an entire book on its own. But it gets you up and running.I am using OpenCV with OS X and Xcode so most of Chapter 1 was useless. But, thankfully, every chapter after that is platform-agnostic so I can definitely recommend this to my fellow Mac programmers. The OpenCV Wiki has a page dedicated to installing OpenCV under OS X and creating an Xcode project. For iOS programmers there are a few sites out there that describe how to use OpenCV. There is a Google Summer of Code 2011 project whose aim is to build iOS support into the official OpenCV code base.My biggest complaint with this book (and the thing that kept me from awarding five stars) is that the proofreading was dismal. I checked the book's website and it said there were no known errata. So I submitted a couple dozen. Most of them are grammatical errors. I only found a couple that affected the code. (One of which was code that attempted to modify a collection with a const_iterator.) None of the submitted errata have shown up on the book's website yet so you'll have to find them for yourself. I'm really spoiled by Pragmatic Programmers. They have a great book beta program that eliminates almost all errata before printing and they post all submitted errata immediately. Other publishers would do well to emulate the Prags' customer service.In the end, though, you should definitely get this book if you'd like to learn how to use OpenCV's C++ interface. (And keep an eye out for the next edition of Learning OpenCV. The authors are working on an update.)
I found this book and the source code that comes with it (download from publisher's web site) extremely useful for setting up a video tracking project for my work. I didn't have any C++ experience before (only Matlab, Python, Java), but the book did a good job of introducing me to an object-oriented approach to image analysis. (Especially the frame processor class introduced in the last chapter saved me from losing my mind.)I also found the explanation of how to set openCV up in the Qt IDE most useful.The various algorithms are presented in a nice, intro-level way, but if you want to know more about the math behind it, you should pick up another book (references to technical papers are presented throughout the book, though.) I give it 4 points only because the theory comes a bit short. (For that, I'd read "Learning OpenCV" Learning OpenCV: Computer Vision with the OpenCV Library)
When I bought this book, I was looking for a very practical approach in the subject of computer vision. And that's what I found.As a computer vision student, I had trouble understading the theory presented in other books, even those with "practical" in their titles. The subject is normally presented in a very theoretical way, with paper references and strong mathematical approach, and no working samples at all. In other books, each tracking step is discussed with so many details, and with so many alternative approachs, that was really difficult for me to understand when to use one approach or another.The book does not provide up to date computer vision information, and does not provide explanations of several opencv2.0 algorithms. That's why I took one star out. It's an opencv2 introduction book and enforces the C++ style and the new Opencv2 API.But, if you expect no more than that, it is a fairly good introduction to the subject of computer vision. Every algorithm is explained in a direct language, you can easily implement the proposed programs, change some algorithm parameters, and see the results for yourself. After reading it, it will be considerably simpler to read a more theoretical book, or to understand academic papers on the subject.
I'm not sure were to start ... this would be ok as a beginners books from a instruction viewpoint and people that really wanted to use opencv2. I think he explained opencv2 clearly ... but from a "machine vision" viewpoint the temporal aspect is very important ... and that was at the end of the book(i.e. he is mainly using static images and not comparing images sensors in time ... in almost all his examples). From a actual library perspective ... this is a bunch of easy matrix routines, not network mesh based, so the library is more old school image processing(i.e. the title of saying computer vision ... is missleading ... since this has very little to do with modern vision algorithms). It's terribly out of date from a viewpoint on where the state of the art is for vision processing ... (like 20 years) ... maybe that's in part of the library not included in the book. Using python/numpy/pil/etc.. is way easier to teach vision theory ... so I'm not sure who this book is for.
There are two issues which downgrade my rating from five stars to three stars:1. In Chapter 5, the majority of sample code failed to be compiled. I searched author's website, checked the errata listing without finding useful clues. I figured them out eventually by myself.2. In Chapter 7, there are also some source code failed to be compiled.Otherwise, this textbook is an excellent guidance for students on learning the OpenCV programming. The book provides many useful examples and the description is friendly to new users.
There wasn't all that much in this that isn't directly available via the web docs. Also, it's getting dated now. It's a cookbook, but I'd have liked to see more on the explanation side and more focus on things like recognition, etc. Not neccessarily the author doing a bad job, just sayin'.
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