Image Databases: Search and Retrieval of Digital Imagery - Hardcover

Über die Autorin bzw. den Autor

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.

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An up-to-date, expert guide to modern digital image databases

This volume presents the state of the art in digital image database design, with a concentration on storage and retrieval techniques, and includes a set of selected application case studies.

Chapters by experts from around the world explore a variety of techniques for accessing images based on color, texture, shape, and semantic descriptions. Underlying principles are stressed, including compression, indexing, storage organization, and transmission.

Image Databases also features detailed coverage of these important issues:
* Hierarchical storage management
* Database support
* Search at multiple abstraction levels
* Content extraction from compressed imagery
* Standards for representation and search

Case studies cover important application areas including:
* Photographic images
* Satellite imagery
* Images in the oil industry
* Medical imagery

A wide range of introductory material and an extensive bibliography makes Image Databases an excellent text for graduate-level students. It also serves as a valuable reference for developers and researchers in the field, and as a guide for helping IT professionals more fully understand the discipline.

Aus dem Klappentext

An up-to-date, expert guide to modern digital image databases

This volume presents the state of the art in digital image database design, with a concentration on storage and retrieval techniques, and includes a set of selected application case studies.

Chapters by experts from around the world explore a variety of techniques for accessing images based on color, texture, shape, and semantic descriptions. Underlying principles are stressed, including compression, indexing, storage organization, and transmission.

Image Databases also features detailed coverage of these important issues:
* Hierarchical storage management
* Database support
* Search at multiple abstraction levels
* Content extraction from compressed imagery
* Standards for representation and search

Case studies cover important application areas including:
* Photographic images
* Satellite imagery
* Images in the oil industry
* Medical imagery

A wide range of introductory material and an extensive bibliography makes Image Databases an excellent text for graduate-level students. It also serves as a valuable reference for developers and researchers in the field, and as a guide for helping IT professionals more fully understand the discipline.