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dc.contributor.authorWang, Binen_US
dc.contributor.authorGao, Yongshengen_US
dc.contributor.editorJean-Philippe Thiran, Fabrice Labeauen_US
dc.description.abstractA novel shape descriptor, termed multi-scale bisector integrals, is proposed in this paper. Different from the existing Radon transform based descriptors which integrate the shape image function over all the possible lines in its domain, the proposed method restrains the integrals only over a special class of lines, termed shape bisectors, for characterizing the essence of the shape. Integrating the shape image over the multi-orders of shape bisectors yields a multi-scale descriptor. The proposed descriptor is completely invariant to translation, scaling and rotation. The experimental results on the standard MEPG-7 CE-2 shape database demonstrate its superiority over the state-of-the-art approaches.en_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.publisher.placeUnited Statesen_US
dc.relation.ispartofconferencenameICIP 2015en_US
dc.relation.ispartofconferencetitleProceedings of the 2015 IEEE International Conference on Image Processingen_US
dc.relation.ispartoflocationQuebec City, Canadaen_US
dc.subject.fieldofresearchImage Processingen_US
dc.titleMulti-scale bisector integrals: An invariant descriptor for accurate shape retrievalen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.hasfulltextNo Full Text

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