Data management and internet computing for image/pattern analysis
Author(s)
Bibliographic Information
Data management and internet computing for image/pattern analysis
(Kluwer international series on Asian studies in computer and information science, 11/a)
Kluwer Academic, c2001
Available at 10 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references and index
Description and Table of Contents
Description
Data Management and Internet Computing for Image/Pattern Analysis focuses on the data management issues and Internet computing aspect of image processing and pattern recognition research. The book presents a comprehensive overview of the state of the art, providing detailed case studies that emphasize how image and pattern (IAP) data are distributed and exchanged on sequential and parallel machines, and how the data communication patterns in low- and higher-level IAP computing differ from general numerical computation, what problems they cause and what opportunities they provide. The studies also describe how the images and matrices should be stored, accessed and distributed on different types of machines connected to the Internet, and how Internet resource sharing and data transmission change traditional IAP computing.
Data Management and Internet Computing for Image/Pattern Analysis is divided into three parts: the first part describes several software approaches to IAP computing, citing several representative data communication patterns and related algorithms; the second part introduces hardware and Internet resource sharing in which a wide range of computer architectures are described and memory management issues are discussed; and the third part presents applications ranging from image coding, restoration and progressive transmission.
Data Management and Internet Computing for Image/Pattern Analysis is an excellent reference for researchers and may be used as a text for advanced courses in image processing and pattern recognition.
Table of Contents
Preface. Acknowledgements. 1. Overview. Part I: Software Management: Models & Algorithms. 2. Issues of Data Management. 3. Typical PRIP Algorithms and IAP Data Management. 4. Neural Evolution Model for Gray Level Image Restoration. 5. Partial Fractal Model for Hybrid Image Coding. 6. Best Neighborhood Model for Block-Based Image Coding. 7. Impulse Noise Removal Algorithms For IAP. Part II: Hardware Management: Architectures & Resource Sharing. 8. Internet Resource Sharing. 9. Parallel Processing for Image Restoration. 10. Image Storage Management on Parallel Computers. 11. Data Management for Sequential Computer Systems. 12. Permutation Routing for Interconnection Network. Part III: Typical Examples: Applications & Implementations. 13. Compression Coding for IAP Data. 14. Reduction of Blocking Effects and Removal of Impulse Noise. 15. Image Restoration From Internet Transmission Corruption. 16. Encryption Coding for IAP Data. Index.
by "Nielsen BookData"