ABSTRACT
In order to maximize the benefit of the huge repository of digital images available both publicly and in private collections, intelligent matchmaking tools are required. Unfortunately, most image search engines rely on free-text search which often returns inaccurate sets of results based on the recurrence of the search keywords in the text accompanying the images. In this paper we present a semantically-enabled image annotation and retrieval engine that relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query.
- Berners-Lee, Tim. 2000. Weaving the Web: the original design of the World Wide Web by its inventor / Tim Berners-Lee with Mark Fischetti. Harper Collins. 2000. pp 157--160. Google ScholarDigital Library
- Fujii A., Ishikawa T. 2005. Toward the Automatic Compilation of Multimedia Encyclopaedias: Association Images with Term Descriptions on the Web. In Proceedings of the 2005 International Conference on Web Intelligence -- WIC05. Compiègne, France. September 19--22, 2005. 536--542. Google ScholarDigital Library
- Hare JS et al. 2006. Mind the gap: another look at the problem of the semantic gap in image retrieval. Multimedia Content Analysis, Management, and Retrieval 2006, Vol. 6073, No. 1. (2006).Google Scholar
- L. Hollink et al. 2003. Semantic annotation of image collections. In Workshop on Knowledge Markup and Semantic Annotation.Google Scholar
- Huan Wang et al. 2006. Does ontology help in image retrieval?: a comparison between keyword, text ontology and multi-modality ontology approaches. Proceedings of the 14th annual ACM international conference on Multimedia. 109--112 Semantic Annotation, KCAP'03. Google ScholarDigital Library
- Jeremy J. Carroll et al. 2004. Jena: implementing the semantic web recommendations. Proceedings of the 13th international World Wide Web conference. New York, USA. 74--83. Google ScholarDigital Library
- J. Jeon et al. 2003. Automatic image annotation and retrieval using cross-media relevance models. Proceedings of the 26th annual international ACM SIGIR conference on Research and development in information retrieval. Toronto, Canada. Google ScholarDigital Library
- Ka-Ping Yee et al. 2003. Facated meta data for image search and browsing. Proceedings of the SIGCHI conference on Human factors in computing systems. 401--408 Google ScholarDigital Library
Index Terms
- Semantic based search technology for images
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