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CoMo: a scale and rotation invariant compact composite moment-based descriptor for image retrieval

dc.contributor.authorVassou, S. A.
dc.contributor.authorAnagnostopoulos, N.
dc.contributor.authorAmanatiadis, A.
dc.contributor.authorChatzichristofis, Savvas A.
dc.contributor.authorChristodoulou, Klitos
dc.date.accessioned2018-03-19T13:04:27Z
dc.date.available2018-03-19T13:04:27Z
dc.date.issued2018-03-01
dc.identifier.issn1573-7721
dc.identifier.urihttp://hdl.handle.net/11728/10590
dc.description.abstractLow level features play a significant role in image retrieval. Image moments can effectively represent global information of image content while being invariant under translation, rotation, and scaling. This paper presents CoMo: a moment based composite and compact low-level descriptor that can be used effectively for image retrieval and robot vision tasks. The proposed descriptor is evaluated by employing the Bag-of-Visual-Words representation over various well-known benchmarking image databases. The findings from the experimental evaluation provide strong evidence of high and competitive retrieval performance against various state-of-the-art local descriptors.en_UK
dc.language.isoenen_UK
dc.publisherSpringer International Publishingen_UK
dc.relation.ispartofseriesMultimedia Tools and Applications;
dc.rightsSpringer International Publishingen_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.subjectContent based image retrievalen_UK
dc.subjectLow level featuresen_UK
dc.subjectCompact composite descriptorsen_UK
dc.titleCoMo: a scale and rotation invariant compact composite moment-based descriptor for image retrievalen_UK
dc.typeArticleen_UK
dc.affiliation
dc.doihttps://doi.org/10.1007/s11042-018-5854-3en_UK


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