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Image Moment Invariants as Local Features for Content Based Image Retrieval using the Bag-of-Visual-Words Model

dc.contributor.authorKarakasis, Evangelos G.
dc.contributor.authorAmanatiadis, Angelos
dc.contributor.authorGasteratos, Antonios
dc.contributor.authorChatzichristofis, Savvas A.
dc.date.accessioned2017-10-24T10:43:26Z
dc.date.available2017-10-24T10:43:26Z
dc.date.issued2015
dc.identifier.issn0167-8655
dc.identifier.urihttp://hdl.handle.net/11728/10143
dc.description.abstractThis paper presents an image retrieval framework that uses affine image moment invariants as descriptors of local image areas. Detailed feature vectors are generated by feeding the produced moments into a Bag-of-Visual-Words representation. Image moment invariants have been selected for their compact representation of image areas as well as due to their ability to remain unchanged under affine image transformations. Three different setups were examined in order to evaluate and discuss the overall approach. The retrieval results are promising compared with other widely used local descriptors, allowing the proposed framework to serve as a reference point for future image moment local descriptors applied to the general task of content based image retrieval.en_UK
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.relation.ispartofseriesPattern Recognition Letters;Volume 55
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.subjectBag of visual wordsen_UK
dc.subjectAffine moment invariantsen_UK
dc.subjectContent based image retrievalen_UK
dc.titleImage Moment Invariants as Local Features for Content Based Image Retrieval using the Bag-of-Visual-Words Modelen_UK
dc.typeArticleen_UK
dc.doi10.1016/j.patrec.2015.01.005en_UK


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