A Query Model with Relevance Feedback for Image Database Retrieval

Most of the solutions proposed in image database applications are limited to a specific application domain. Generic models attempt to ease the development of applications to researchers. In this paper, to overcome the difficulties faced by application-specific systems, we present a general purpose image management model, oriented to fill the gap between systems and users. To the retrieval process the most important issue is to have a query model that efficiently represents the image nature integrated with traditional data and a feedback mechanism to model the user's information needs. This work develops a query language to deal with the fuzzy nature of images. The query language, I-OQL, based on the ODMG standard, also is able to define high level concepts and to integrate different levels of abstraction. We also propose a general-purpose relevance feedback mechanism oriented to fill the gap between systems and users, expressing user subjectivity in the retrieval process. Experiment results are presented to explore and validate the query refinement process