Machine Vision Algorithms in Java: Techniques and Implementation (Hardcover)

by Paul F. Whelan (Author), Derek Molloy (Author) "The purpose of this chapter is to introduce the reader to the basic principles of machine vision..." (more)
Key Phrases: connection status indicator, component explorer, linear local operators, Neat Vision, Operational Summary, Sun Java (more...)

Editorial Reviews

Product Description
Machine Vision Algorithms in Java provides a comprehensive introduction to the algorithms and techniques associated with machine vision systems. The Java programming language is also introduced, with particular reference to its imaging capabilities. The book contains explanations of key machine vision techniques and algorithms, along with the associated Java source code. Special features include: - A complete self-contained treatment of the topics and techniques essential to the understanding and implementation of machine vision. - An introduction to object-oriented programming and to the Java programming language, with particular reference to its imaging capabilities. - Java source code for a wide range of practical image processing and analysis functions. - Readers will be given the opportunity to download a fully functional Java-based visual programming environment for machine vision, available via the WWW. This contains over 200 image processing, manipulation and analysis functions and will enable users to implement many of the ideas covered in this book. - Details relating to the design of a Java-based visual programming environment for machine vision. - An introduction to the Java 2D imaging and Java Advanced Imaging (JAI) APIs - A wide range of illustrative examples. - Practical treatment of the subject matter. This book is aimed at senior undergraduate and postgraduate students in engineering and computer science as well as practitioners in machine vision who may wish to update or expand their knowledge of the subject. The techniques and algorithms of machine vision are expounded in a way that will be understood not only by specialists but also by those who are less familiar with the topic.

Product Details

• Hardcover: 284 pages
• Publisher: Springer; 1 edition (December 12, 2000)
• Language: English
• ISBN-10: 1852332182
• ISBN-13: 978-1852332181
• Product Dimensions: 9.3 x 6.2 x 0.9 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars See all reviews (3 customer reviews)
• Amazon.com Sales Rank: #1,322,625 in Books (See Bestsellers in Books)

  Popular in this category: (What's this?)

  #22 in

  Books > Computers & Internet > Computer Science > Artificial Intelligence > Computer Vision

Customer Reviews

Most Helpful Customer Reviews

4 of 4 people found the following review helpful:

4.0 out of 5 stars Not for robotics , September 12, 2005

By	Burak Ozcan "Buraque" (Istanbul, TURKEY) - See all my reviews (REAL NAME)

This is a good book on algorithms in machine vision, not computer vision. It is important that you know the difference before you buy this book. Machine vision is used in manufacturing plants for detecting the parts according to your needs. On the other hand, computer vision is integrated into AI where you can create vision input for your robotics or AI system.

That's why this book is good for those who wants to create Photoshop-like effects or implement systems for part analysis. If you are looking for something related with robotics, look for elsewhere.

1 of 1 people found the following review helpful:

3.0 out of 5 stars A kind of Schaum's outline of machine vision algorithms, November 26, 2005

By	calvinnme "Texan refugee" (Fredericksburg, Va) - See all my reviews (TOP 10 REVIEWER)

There are better books on Java imaging and better books on machine vision. However, where this book stands out is in its catalogue of machine vision algorithms. The book is really a vehicle for the author's machine vision application, complete with user interface, entitled "NeatVision". You can download it off the web complete with a developer's guide on how to extend the application. There's really nothing unique about the built-in transforms. If you are already familiar with computer vision- and you should be if you buy this book- you will most likely already have heard of most of them. What it does enable you to do is to chain transforms together to perform larger more complex machine vision tasks.
As for the book itself, the first chapter is a forgettable overview of machine vision, and the second chapter is an equally forgettable chapter on Java and imaging in Java. Chapters three through six comprise the meat of the book. These chapters talk about the specific algorithms for machine vision transformations divided into the categories of general machine vision techniques, morphology, texture analysis, and color analysis. Chapter seven switches gears and talks about the author's full visual application, Neatvision. Details are given on how to use and and to extend the application. The appendices are about NeatVision's graphic file formats, API specification, and visual interface components respectively. My advice to the potential buyer of this book is to visit the application's website, and if you find NeatVision very interesting you will find the book valuable. I would type the address into this review myself, but Amazon usually kicks out reviews with web addresses in them. The search engine keyword is just "NeatVision".

0 of 4 people found the following review helpful:

5.0 out of 5 stars If you need to learn machine vision techniques, March 26, 2004

By	Niall Murphy "Niall" (London) - See all my reviews (REAL NAME)

If you need to learn and apply machine vision techniques this is a good place to start.