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Machine Vision Algorithms in Java: Techniques and Implementation
 
 
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Machine Vision Algorithms in Java: Techniques and Implementation [Hardcover]

Paul F. Whelan (Author), Derek Molloy (Author)
4.0 out of 5 stars  See all reviews (3 customer reviews)

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Book Description

1852332182 978-1852332181 December 12, 2000 1st Edition.
This book presents key machine vision techniques and algorithms, along with the associated Java source code. Special features include a complete self-contained treatment of all 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 real-world image processing and analysis functions; an introduction to the Java 2D imaging and Java Advanced Imaging (JAI) API; and a wide range of illustrative examples.

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Product Details

  • Hardcover: 301 pages
  • Publisher: Springer; 1st Edition. 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 Best Sellers Rank: #2,670,905 in Books (See Top 100 in Books)

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4 of 4 people found the following review helpful:
4.0 out of 5 stars Not for robotics, September 12, 2005
This review is from: Machine Vision Algorithms in Java: Techniques and Implementation (Hardcover)
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.
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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
This review is from: Machine Vision Algorithms in Java: Techniques and Implementation (Hardcover)
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".
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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
This review is from: Machine Vision Algorithms in Java: Techniques and Implementation (Hardcover)
If you need to learn and apply machine vision techniques this is a good place to start.
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Inside This Book (learn more)
First Sentence:
The purpose of this chapter is to introduce the reader to the basic principles of machine vision. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
connection status indicator, component explorer, linear local operators, visual workspace, mesh viewer, flow control components, colour triangle, conditional dilation, geodesic dilation, machine vision algorithms, feedback subsystem, colour cube, machine vision systems, visual program, conditional input, scale dilation, colour planes, grey scale image, colour representation, imaging model, colour filter, cumulative histogram, virtual desktop, image processing operation, pixel information
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Neat Vision, Operational Summary, Sun Java, Buffered Image, Case Study, Inverse Fourier, Sun Microsystems, Artificial Neural Networks, Java Language Basics, Morphological Segmentation
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