Dr Taha Osman
School of Computing and Informatics, Nottingham Trent University
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Date: 18th March 2008 (Tuesday) |
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Time: 14:00 - 15:00 |
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Venue: MB146 |
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.
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