Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/70813
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dc.titleLocal radon transform and earth mover's distances for content-based image retrieval
dc.contributor.authorXiong, W.
dc.contributor.authorOng, S.H.
dc.contributor.authorLee, W.
dc.contributor.authorFoong, K.
dc.date.accessioned2014-06-19T03:16:34Z
dc.date.available2014-06-19T03:16:34Z
dc.date.issued2008
dc.identifier.citationXiong, W.,Ong, S.H.,Lee, W.,Foong, K. (2008). Local radon transform and earth mover's distances for content-based image retrieval. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4903 LNCS : 436-445. ScholarBank@NUS Repository.
dc.identifier.isbn3540774076
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/70813
dc.description.abstractContent-based image retrieval based on feature extraction is still a highly challenging task. Traditional features are either purely statistical, thus losing spatial information, or purely spatial without statistical information. The Radon transform (RT) is a geometrical transform widely used in computer tomography. The projections transformed embed spatial relationships while integrating information in certain directions. The RT has been used to design invariant features for retrieval. Spatial resolutions in RT are inhomogeneous resulting in non-uniform feature representation across the image. We employ the local RT by aligning the centre of the RT with the centroids of the region of interest and use a sufficient number of projections. Finally the earth mover's distance method is utilized to combine local matching results. Using the proposed approach, image retrieval accuracy is maintained, while reducing computational cost. © Springer-Verlag Berlin Heidelberg 2008.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentPREVENTIVE DENTISTRY
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume4903 LNCS
dc.description.page436-445
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

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