An Integrated Approach to Digital Objects Storage and Retrieval

Abstract

Image retrieval systems are becoming increasingly important in areas of research and commercial use. The storage of digital objects in the traditional databases is considered inadequate because of the extensive precise data required for successful retrieval. In addition, the retrieval process has been implemented using content-based image retrieval (CBIR) that relies on retrieving stored images from a collection by comparing low level features (binary form) that are automatically extracted from the images themselves. Data retrieval requires knowledge of attributes stored along with an adequate and flexible query language. For image repositories and retrieval, we noted that the integration of XML technology and case-based reasoning is more efficient and of great benefit in this area. This is mainly because users both in indexing and retrieval processes, tend to use old cases by associating images that reveal similar features. It is also because XML extends the original theory and offers a flexible approach with accurate data modelling and management tools. In this work, we also used fuzzy reasoning to convert the quantitative attributes into qualitative terms for indexing and retrieval.