Content Based Visual Information Retrieval for Management Information Systems

This paper presents the results of our research devoted to development of efficient methods for retrieval and indexing of documents with multimedia information that can help a business work smarter and gain an important advantage in whatever that business does. Particularly, a novel hybrid method for visual information retrieval (VIR) is proposed. It combines shape analysis of objects in image with their automatic indexing by textual descriptions applying semantic Web approaches. A decision about similarity between a retrieved image and user queries is taken by computing the shape star field or two-segment turning functions combining them with matching of ontological annotations of objects in image providing in this way the machine-understandable semantics. For analysis of this method the image retrieval IRONS (Image Retrieval by Ontological Description of Shapes) system has been implemented and evaluated in some specific image domains.