The increasing use of multimedia in computer applications has increased the relevance of visual databases. These visual databases require new methods for archiving and retrieving information, as traditional approaches used previously to index textual data are no longer appropriate. Visual Information Retrieval concentrates on solutions for representation, indexing, and querying by content of visual information, reviewing the main approaches and techniques available. Single image indexing, querying and retrieval by content, video segmentation, annotation, and content-based indexing are all examined. The book will appeal to practitioners and graduates/researchers involved in visual database issues in multimedia and image processing.

A growing percentage of stored computer information is visual media, whether it's still images or video clips. This kind of data has a very different format and structure than text-based data, and cataloging, sorting, and searching non-text-based data presents a tremendous challenge to the contemporary database programmer.

This is not a book for the casual programmer. It offers high-level suggestions on how to build the architecture for such systems, key theories on how to represent this kind of visual content, how to build similarity models, and indexing methods.

It continues with examples of how to index and catalog still images based on color, texture, shape, and spatial relationship similarity.

Chapter 6 details the problems and current solutions for content-based video retrieval. Detecting sharp transitions, how to analyze compressed and uncompressed streams, and gradual transition detection are just a few of the problems presented. The solutions presented are practical and fascinating.

Visual Information Retrieval is a clearly written, although sometimes dense, handbook. The author uses a generous amount of examples of mathematical formulas, illustrations, and color plates. Clearly not a book for every database programmer--but a mandatory reference book for anyone building visual retrieval systems. --Mike Caputo