Pattern classification and scene analysis

by Richard O. Duda

  • ★ ★ ★ ★ ★ 5.00
  • 2 Ratings
  • 20 Want to read
  • 5 Currently reading
  • 1 Have read

This edition was published in by Wiley in New York.

Written in English

— 482 pages

From the inside cover: Here is a unified, Comprehensive, and up–to–date treatment of the theoretical principles of pattern recognition. These principles are applicable to a great variety of problems of current interest, such as character recognition, speech recognition, speaker identification, fingerprint recognition, the analysis of biomedical photographs, aerial photoreconnaissance, automatic inspection for industrial quality control, and visual systems for robots. Throughout Pattern Classification and Scene Analysis, the authors have balanced their presentation to reflect the relative importance of the many theoretical topics in the field. Pattern Classification and Scene Analysis is the first book to provide comprehensive coverage of both statistical classification theory and computer analysis of pictures. Part I covers Bayesian decision theory, supervised and unsupervised learning, nonparametric techniques, discriminant analysis, and clustering. Part II describes many techniques of current interest in automatic scene analysis, including preprocessing of pictorial data, spatial filtering, shape–description techniques, perspective transformations, projective invariants, linguistic procedures, and artificial intelligence techniques for scene analysis. Although the theories and techniques of pattern recognition are largely mathematical, the authors have been more concerned with providing insight and understanding than with establishing rigorous mathematical foundations. The many illustrative examples, plausibility arguments, and discussions of the behavior of solutions reflect this concern. Extensive bibliographical and historical remarks at the end of each chapter further enhance the presentation. Standard notation is used wherever possible, and a comprehensive index is included. Typical first–year graduate students will find most of the mathematical arguments well within their grasp. Because the exposition is clear and balanced, Pattern Classification and Scene Analysis is suitable for both college and professional use. In particular, it will appeal to graduate students and professionals in the fields of computer science, electrical engineering, and statistics. Students and professionals in psychology, biomedical science, meteorology, and biology will also find it of value for the light it sheds on such areas as visual perception, image processing, and numerical taxonomy

Read more

Read less

Previews available in: English

Edition Availability
1

Cover of: Pattern classification and scene analysis

Pattern classification and scene analysis

1973, Wiley

in English

0471223611 9780471223610

aaaa

  • Borrow Listen

    Encrypted daisy lock Download for print-disabled

Libraries near you: WorldCat

Add another edition?

Pattern classification and scene analysis

First published in 1973

Work Description

From the inside cover: Here is a unified, Comprehensive, and up–to–date treatment of the theoretical principles of pattern recognition. These principles are applicable to a great variety of problems of current interest, such as character recognition, speech recognition, speaker identification, fingerprint recognition, the analysis of biomedical photographs, aerial photoreconnaissance, automatic inspection for industrial quality control, and visual systems for robots. Throughout Pattern Classification and Scene Analysis, the authors have balanced their presentation to reflect the relative importance of the many theoretical topics in the field. Pattern Classification and Scene Analysis is the first book to provide comprehensive coverage of both statistical classification theory and computer analysis of pictures. Part I covers Bayesian decision theory, supervised and unsupervised learning, nonparametric techniques, discriminant analysis, and clustering. Part II describes many techniques of current interest in automatic scene analysis, including preprocessing of pictorial data, spatial filtering, shape–description techniques, perspective transformations, projective invariants, linguistic procedures, and artificial intelligence techniques for scene analysis. Although the theories and techniques of pattern recognition are largely mathematical, the authors have been more concerned with providing insight and understanding than with establishing rigorous mathematical foundations. The many illustrative examples, plausibility arguments, and discussions of the behavior of solutions reflect this concern. Extensive bibliographical and historical remarks at the end of each chapter further enhance the presentation. Standard notation is used wherever possible, and a comprehensive index is included. Typical first–year graduate students will find most of the mathematical arguments well within their grasp. Because the exposition is clear and balanced, Pattern Classification and Scene Analysis is suitable for both college and professional use. In particular, it will appeal to graduate students and professionals in the fields of computer science, electrical engineering, and statistics. Students and professionals in psychology, biomedical science, meteorology, and biology will also find it of value for the light it sheds on such areas as visual perception, image processing, and numerical taxonomy

Pattern classification and scene analysis

This edition was published in by Wiley in New York.

Includes bibliographies.
"A Wiley-interscience publication."

Dewey Decimal Class
001.53/3
Library of Congress
Q327 .D83
Pagination
xvii, 482 p.
Number of pages
482

No community reviews have been submitted for this work.

November 2, 2020 Edited by Michel T. Talbot Added new cover
October 5, 2020 Edited by MARC Bot import existing book
August 17, 2019 Edited by ImportBot import existing book
November 17, 2018 Edited by MARC Bot import existing book
April 1, 2008 Created by an anonymous user Imported from Scriblio MARC record.