Refereed full papers (journals, book chapters, international conferences)

1999

@article{BeS1999a,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Andrew P. Berman and Linda G. Shapiro},
	title =	{A Flexible Image Database System for Content-Based
	Retrieval},
	journal =	{Computer Vision and Image Understanding (special issue on content-based access for image
	and video libraries)},
	volume =	{75},
	number =	{1/2},
	pages =	{175--195},
	month =	{July/August},
	year =	{1999},
	abstract =	{There is a growing need for the ability to query image
	databases based on similarity of image content rather than strict
	keyword search. As distance computations can be expensive, there is a
	need for indexing systems and algorithms that can eliminate candidate
	images without performing distance calculations. As user needs may
	change from session to session, there is also a need for run-time
	creation of distance measures. In this paper, we present FIDS,
	``flexible image database system.'' FIDS allows the user to query the
	database based on complex combinations of dozens of predefined distance
	measures. Using an indexing scheme and algorithms based on the triangle
	inequality, FIDS can often return matches to the query image without
	directly comparing the query image to more than a small percentage of
	the database. This paper describes the technical contributions of the
	FIDS approach to content-based image retrieval.},
}