Image Databases: Search and Retrieval of DigitalImagery
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More About This Title Image Databases: Search and Retrieval of DigitalImagery


The explosive growth of multimedia data transmission has generated a critical need for efficient, high-capacity image databases, as well as powerful search engines to retrieve image data from them. This book brings together contributions by an international all-star team of innovators in the field who share their insights into all key aspects of image database and search engine construction. Readers get in-depth discussions of the entire range of crucial image database architecture, indexing and retrieval, transmission, display, and user interface issues. And, using examples from an array of disciplines, the authors present cutting-edge applications in medical imagery, multimedia communications, earth science, remote sensing, and other major application areas.


VITTORIO CASTELLI received his MS in both statistics and electrical engineering and his PhD in electrical engineering from Stanford University. He currently works at the IBM Thomas J. Watson Research Center, where his main research interests include information theory, statistics, classification, and their applications to performance analysis and computer architecture.

LAWRENCE D. BERGMAN received his PhD in Computer Science from the University of North Carolina at Chapel Hill, and currently works at the IBM Thomas J. Watson Research Center. His research interests include user-interfaces and visualization tools for content-based retrieval, and application development environments for pervasive computing.





Digital Imagery: Fundamentals (V. Castelli & L. Bergman).


Visible Image Retrieval (C. Colombo & A. Del Bimbo).

Satellite Imagery in Earth Science Applications (H. Ramapriyan).

Medical Imagery (S. Wong & K. Hoo).

Images in the Exploration for Oil and Gas (P. Tilke).


Storage Architectures for Digital Imagery (H. Vin).

Database Support for Multimedia Applications (M. Ortega-Binderberger and K. Chakrabarti).

Image Compression--A Review (S. Hemami).

Transmission of Digital Imagery (J. Percival).


Introduction to Content-Based Image Retrieval-Overview of Key Techniques (Y. Li and C. Kuo).

Color for Image Retrieval (J. Smith).

Texture Features for Image Retreival (B. Manjunath & W. Ma).

Shape Representation for Image Retrieval (B. Kimia).

Multidimensional Indexing Structures for Content-Based Retrieval (V. Castelli).

Multimedia Indexing (C. Faloutsos).

Compressed or Progressive Image Search (S. Panchanathan).

Concepts and Techniques for Indexing Visual Semantics (A. Jaimes & S. Chang).