Progressive Query Based Search and Retrieval in Large Image Archives

In this paper, we describe the architecture and implementation of a framework to perform content based search of an image database, where content is specified by the user at one or more of the following three abstraction levels: pixel, feature, and semantic. Query based Image Acquisition System deals with query passing, query parsing, SQL query generation and image retrieval. The image is retrieved just based on the query given by the user. It provides a user friendly interface for user to pass his query. The required image is returned to the user based on his query by performing a search on the database. All this procedure is carried on in semantic level. This framework is well suited for searching scientific databases, such as satellite image, medical, and seismic data repositories, where the volume and diversity of the information do not allow the apriori generation of exhaustive indices, but we have successfully demonstrated its usefulness on still-image archives.