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Pattern Recognition and Image AnalysisBy Earl Gose, Richard Johnsonbaugh, Steve Jost
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Over the past 20 to 25 years, pattern recognition has become an important part of image processing applications where the input data is an image. This book is a complete introduction to pattern recognition and its increasing role in image processing. It covers the traditional issues of pattern recognition and also introduces two of the fastest growing areas: Image Processing and Artificial Neural Networks. Examples and digital images illustrate the techniques, while an appendix describes pattern recognition using the SAS statistical software system.
- Sales Rank: #2042649 in Books
- Published on: 1996-05
- Original language: English
- Number of items: 1
- Dimensions: 9.75" h x 7.25" w x 1.25" l,
- Binding: Hardcover
- 483 pages
From the Publisher
Pattern Recognition is concerned with the classification of objects into categories, especially by machine. Over the past 20 to 25 years, pattern recognition has become an important part of image processing applications. This book is a complete introduction to pattern recognition that introduces it's increasing role in image processing.
From the Back Cover
Pattern recognition is at the heart of applications ranging from the identification of white blood cells to the selection of tax returns for auditing, from earthquake prediction to speech recognition. Pattern Recognition and Image Analysis is an ideal introduction to pattern recognition for both higher-level undergraduate and beginning graduate courses.
The book relies extensively on worked examples and realistic applications that have been thoroughly classroom-tested. Since images are often the input to pattern recognition systems, a survey of image processing theory is included, covering techniques such as scene segmentation, Hough transforms, least squares, Eigenvector line fitting, and Fourier transforms. These important aspects of pattern recognition are also presented:
*Probability theory
*Statistical decision making, including Bayes' Theorem
*Nonparametric decision making, including histograms
*Hierarchical and partitional clustering: the advantages and risks
*Artificial neural networks—and how they work in real applications, such as classifying sex from facial images
Readers do not need computer science expertise, or a mathematics background beyond elementary calculus.
Pattern Recognition and Image Analysis includes a disk with sample digital images and data files, SAS programs, and C program implementations of several major algorithms discussed in the book.
About the Author
EARL GOSE is a professor at the Department of Electrical Engineering and Computer Science, University of Illinois and Chicago.
RICHARD JOHNSONBAUGH and STEVE JOST are faculty members at the School of Computer Science, Telecommunications and Information Systems, DePaul University.
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