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Semantic Indexing Of Images Using A Web Ontology Language

Semantic Indexing Of Images Using A Web Ontology Language Gowri Allampalli-Nagaraj Chair of the Supervisory Committee: Professor Isabelle Bichindaritz Computing and Software Systems This paper presents a system implemented to evaluate the retrieval efficiency of images when they are semantically indexed using a combination of a Web Ontology Language and the low level features of the image. Finding a similarity measure algorithm to retrieve images based on the semantic metadata can be very challenging due to diverse image content and inadequate domain specific ontologies describing the content. Existing methods for indexing images are primarily based on text. While this method is widely used due to its simplicity, it is not very efficient as it requires a domain expert and the textual interpretations of image content vary from person to person. In our approach, we leverage sophisticated image processing techniques to extract image content information and associate them to existing domain ontologies developed by experts thereby, bridging the gap between low level features and high level semantics. The work described in this paper shows that a high retrieval accuracy rate is obtained when all the image descriptors are combined with an ontology while building the semantic metadata for indexing images.