A practical image retrieval framework for tourism industry

Abstract

Image Retrieval (IR) is one of the most exciting and fastest growing research domains in the field of multimedia technology. And in the industrial ecosystems, images of products, activities, marketing materials etc are needed to be managed and fetched in an efficient way to support and facilitate business processes. Current techniques for IR including keyword based, content based and ontology based image retrieval have several unsolved issues. We promote the ontology based IR approach and focus on two issues: firstly, the difficulty in constructing ontologies of images for those industries without ontology professionals, and, secondly, none of the existing approaches consider image content ranking in search results. In this paper, we propose a practical framework to tackle these issues by introducing an Abstract Image Ontology that serves as a blueprint of image ontologies and by incorporating a Concept Instance Ranking Scheme to allow ranking of each of the contents expressed in images, thus providing extra information for IR process. An application scenario in the tourism industry area is also presented.