Exploring Data Fusion under the Image Retrieval Domain

Advanced services in data compression, data storage, and data transmission have been developed and are widely used to address the required capabilities of an assortment of systems across diverse application domains. In order to reuse, integrate, unify, manage, and support heterogeneous resources, a number of works and concepts have emerged with the aim of facilitating aggregation of content and helping system developers. In particular, images, along with existing Content-Based Image Retrieval services, have the potential to play a key role in information systems, due to the large availability of images and the need to integrate them with existing collections, metadata, and available image manipulation softwares and applications. In this work, we explore a data fusion approach for solving data value conflicts in the context of image retrieval domain. In particular, we target the process of solving value conflicts resulted from different features integrating the data resulted from the Content-Based Image Retrieval process, along with the image metadata, provided from a number of sources and applications. Our approach reduces the need of human intervention for keeping a clean and integrated view of an image repository when new data sources are added to an image management