An integrative semantic framework for image annotation and retrieval

Taha Osman*, Dhavalkumar Thakker, Gerald Schaefer, Phil Lakin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most public image retrieval engines utilise free-text search mechanisms, which often return inaccurate matches as they in principle rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. 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. Our semantic retrieval technology is designed to satisfy the requirements of the commercial image collections market in terms of both accuracy and efficiency of the retrieval process. We also present our efforts in further improving the recall of our retrieval technology by deploying an efficient query expansion technique.

Original languageEnglish
Title of host publicationProceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
Pages366-373
Number of pages8
DOIs
Publication statusPublished - 7 Jan 2008
EventIEEE/WIC/ACM International Conference on Web Intelligence, WI 2007 - Silicon Valley, CA, United Kingdom
Duration: 2 Nov 20075 Nov 2007

Conference

ConferenceIEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
CountryUnited Kingdom
CitySilicon Valley, CA
Period2/11/075/11/07

Bibliographical note

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    Osman, T., Thakker, D., Schaefer, G., & Lakin, P. (2008). An integrative semantic framework for image annotation and retrieval. In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007 (pp. 366-373). [4427118] https://doi.org/10.1109/WI.2007.17