Multimedia Systems: Content Based Indexing and Retrieval

Multimedia data, such as text, audio, images and video, is rapidly evolving as the main form for the creation, exchange, and storage of information in the modern era. Primarily, this is attributed to rapid advances in the three major technologies that determine its growth: VLSI technology that is producing greater processing power; broad-band networks (ISDN, ATM, etc) that are providing much higher bandwidth for many practical applications, and multimedia compression standards (JPEG, H.263, MPEG, MP3, etc) that enable efficient storage and communication. The combination of these three advances is spurring the creation and processing of increasingly high-volume multimedia data, along with its efficient compression and transmission over high-bandwidth networks. This current trend towards the removal of any conceivable bottleneck in using multimedia and its impact on a whole spectrum of users, from advanced research organizations to home users, has led to the explosive growth of visual information available in the form of digital libraries and online multimedia archives. According to a press release by Google Inc. in December 2001, the search engine offers access to over 3 billion web documents and its Image search comprises more that 330 million images. AltaVista has been serving around 25 million search queries per day in more than 25 languages, with its multimedia search featuring over 45 million images, videos and audio clips. This explosive growth of multimedia data accessible to users poses a whole new set of challenges relating to its storage and retrieval. The current technology of text-based indexing and retrieval implemented for relational databases does not provide practical solutions for this problem of managing huge multimedia repositories. Most of the commercially available multimedia indexing and search systems index the media based on keyword annotations and use standard text based indexing and retrieval mechanisms to store and retrieve multimedia data. There are often many limitations with this method of keywords based indexing and retrieval especially in the context of multimedia databases. First, it is often difficult to describe with human languages the content of a multimedia object, for example an image having complicated texture patterns. Second, manual annotation of text phrases for a large database is prohibitively laborious in terms of time and effort. Third, since users may have different interests in the same multimedia object, it is difficult to describe it with a complete set of key words. Finally, even if all relevant object characteristics are annotated, difficulty may still arise …