Abstract
In this paper we describe the architecture and implementation of a digital library framework for scientific data, particularly imagery, with a focus on support for content-based search. Content is specified by the user at one or more of the following abstraction levels: pixel, feature, and semantic. An object-definition mechanism has been developed that supports examplebased and constraint-based specification of both simple and complex query targets.This framework incorporates a methodology yielding a computationally efficient implementation of image processing algorithms, thus allowing the interactive, real-time extraction and manipulation of user-specified features and content during the execution of queries. The framework is well-suited for searching scientific databases, including satellite imagery, and medical and seismic data repositories, where the richness of the information does not allow the a priori generation of exhaustive indexes. © 2000 Springer-Verlag.