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Image retrieval using noisy query

Zhang, Jun and Ye, Lei 2009, Image retrieval using noisy query, in ICME 2009 : Proceedings of the 2009 IEEE International Conference on Multimedia and Expo, IEEE, Piscataway, N. J., pp. 866-869, doi: 10.1109/ICME.2009.5202632.

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Title Image retrieval using noisy query
Author(s) Zhang, JunORCID iD for Zhang, Jun orcid.org/0000-0002-2189-7801
Ye, Lei
Conference name International Conference on Multimedia & Expo (2009 : New York, N. Y.)
Conference location New York, N. Y.
Conference dates 28 June-3 July 2009
Title of proceedings ICME 2009 : Proceedings of the 2009 IEEE International Conference on Multimedia and Expo
Editor(s) [Unknown]
Publication date 2009
Conference series International Conference on Multimedia and Expo
Start page 866
End page 869
Total pages 4
Publisher IEEE
Place of publication Piscataway, N. J.
Keyword(s) content-based image retrieval
noisy query
data cleaning
noise tolerant classifier
Summary In conventional content based image retrieval (CBIR) employing relevance feedback, one implicit assumption is that both pure positive and negative examples are available. However it is not always true in the practical applications of CBIR. In this paper, we address a new problem of image retrieval using several unclean positive examples, named noisy query, in which some mislabeled images or weak relevant images present. The proposed image retrieval scheme measures the image similarity by combining multiple feature distances. Incorporating data cleaning and noise tolerant classifier, a twostep strategy is proposed to handle noisy positive examples. Experiments carried out on a subset of Corel image collection show that the proposed scheme outperforms the competing image retrieval schemes.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 9781424442904
ISSN 1945-7871
Language eng
DOI 10.1109/ICME.2009.5202632
Field of Research 080704 Information Retrieval and Web Search
080109 Pattern Recognition and Data Mining
Socio Economic Objective 890301 Electronic Information Storage and Retrieval Services
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2009, IEEE
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30039522

Document type: Conference Paper
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.