Journal of Visual Languages and Computing (2000) 11, 405–438 doi:10.1006 / jvlc.2000.0169, available online at http://www.idealibrary.com on Multimedia Indexing with the SMART system P. MARESCA,* A. GUERCIO,- T. ARNDT? AND G. TORTORA- * Dipartimento di Informatica e Sistemistica, University of Napoli, Italy, - Dipartimento di Matematica ed Informatica , University of Salerno, Italy and ?Department of Computer and Information Science, Cleveland State University, 1860 E. 18th St., Cleveland, OH 44114, U.S.A. Received 30 November 1999; in revised form 8 April 2000; accepted 22 May 2000 The storage and retrieval of multimedia data is a crucial problem in multimedia information systems due to the huge storage requirements. It is necessary to provide an efficient methodology for the indexing of multimedia data for rapid retrieval. The aim of this paper is to introduce a methodology to represent, simplify, store, retrieve and reconstruct an image from a repository. An algebraic representation of the spatio- temporal relations present in a document is constructed from an equivalent graph representation and used to index the document. We use this representation to simplify and later reconstruct the complete index. This methodology has been tested by implementation of a prototype system called Simplified Modeling to Access and ReTrieve multimedia information (SMART). Experimental results show that the com- plexity of an index of a 2D document is O (n*(n!1)/k) with k52 as opposed to the O (n* (n!1)/2) known so far. Since k depends on the number of objects in an image more complex documents have lower overall complexity.  2000 Academic Press Keywords: multimedia database, content-based retrieval, multimedia indexing 1. Introduction THE STORAGE AND RETRIEVAL of multimedia data is a crucial problem in multimedia information systems due to the huge storage requirements of multimedia data. There- fore, it is necessary to provide an efficient methodology for the indexing of multimedia data for rapid retrieval of the data. The time complexity for handling such indexes is an important consideration. Multimedia data can be divided into image data, audio data, video data, etc. In this paper we will refer to a multimedia document when we want to specify an object which can be of any multimedia type. In general, our discussion will refer to images and image indexing, since our prototype system handles images. However, the methodology introduced in this work can be easily extended to handle audio, video, and three- dimensional scenes, and in fact some of our examples will refer to multimedia documents of these types. Several methodologies have been introduced for indexing multimedia data. An extended survey on these techniques can be found in [1]. For brevity, in this paper we review only some of the most important results connected to our research. 1045-926X/00/080405 # 34 $35.00/0  2000 Academic Press