Automated document content characterization for a multimedia document retrieval system

We propose a new approach to automate document image layout extraction for an object-oriented database feature population using rapid low level feature analysis, preclassification and predictive coding. The layout information comprised of region location and classification data is transformed into 'feature object(s)'. The information is then fed into an intelligent document image retrieval system (IDIR) to be utilized in document retrieval schemes. The IDIR system consists of user interface, object-oriented database and a variety of document image analysis algorithms. In this paper the object-oriented storage model and the database system are presented in formal and functional domains. Moreover, the graphical user interface and a visual document image browser are described. The document analysis techniques used at document characterization are also presented. In this context the documents consist of text, picture and other media (possibly embedded) data. Documents are stored in the database as document, page and region objects. Our test system has been implemented and tested using a document database of 10 000 documents.