The Internet world makes increasing use of XML-based technologies. In multimedia data indexing and retrieval, the MPEG-7 standard for Multimedia Description Scheme is specified using XML. The flexibility of XML allows users to define other markup semantics for special contexts, construct data-centric XML documents, exchange standardized data between computer systems, and present data in different applications. In this paper, the Inverted Image Indexing paradigm is presented and modeled using XML Schema.
The management of visual object databases is an essential function of visual information systems, and the efficient retrieval the associated data objects is vital to operation of these systems. In this paper, we use the number of visual objects retrieved per second as a measure of the throughput of visual object databases. An efficient storage organization technique for executing visual queries is studied: we group similar visual objects together as visual object groups and store each visual object group at consecutive physical locations. We propose a structured high-level indexing system that can cater for the similarity criteria employed in the application domain. Our system incorporates classification hierarchies into an indexing superstructure of metadata, context and content, using high- level content descriptions. Database performance is quantified using queuing analyses, and we show that our technique is able to significantly increase throughput and database performance.
Inverted file indexing and its compression have proved to be highly successful for free-text retrieval. Although the 'inverted' nature of the data structure provides an efficient mechanism for searching key words or terms in large documents, for image retrieval, the application of inverted files to the title, caption, or description of the images are not sufficient. One must be able to index and retrieve images based on the visual contents. Many content-based image retrieval techniques are used for the images as a whole picture. Analogous to free-text retrieval, a novel technique, called inverted image indexing and compression, is proposed in this paper. Similar to works in a document, each image can have multiple areas which are perceived to be meaningful visual contents. These areas are selected by users and then undergo two processes: automatic signature generation based on wavelet signatures, and users specification of high-level contents using ternary fact model. The contents in compressed form are inserted into an inverted image file. The concept of composite bitplane signature is also introduced.