TY - GEN
T1 - An integrative semantic framework for image annotation and retrieval
AU - Osman, Taha
AU - Thakker, Dhavalkumar
AU - Schaefer, Gerald
AU - Lakin, Phil
N1 - © 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
PY - 2008/1/7
Y1 - 2008/1/7
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=48349123381&partnerID=8YFLogxK
UR - http://wwwusers.di.uniroma1.it/~velardi/WI07_sub.pdf
UR - https://ieeexplore.ieee.org/document/4427064/
U2 - 10.1109/WI.2007.17
DO - 10.1109/WI.2007.17
M3 - Conference publication
AN - SCOPUS:48349123381
SN - 0769530265
SN - 9780769530260
SP - 366
EP - 373
BT - Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
T2 - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
Y2 - 2 November 2007 through 5 November 2007
ER -