Show simple item record

dc.contributor.authorChatzichristofis, S. A.
dc.contributor.authorArampatzis, A.
dc.contributor.authorBoutalis, Y. S.
dc.date.accessioned2016-03-11T09:20:19Z
dc.date.available2016-03-11T09:20:19Z
dc.date.issued2010-12cs
dc.identifier.citationRadioengineering. 2010, vol. 19, č. 4, s. 725-733. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/57058
dc.description.abstractIn Content-Based Image Retrieval (CBIR) systems, the visual content of the images is mapped into a new space named the feature space. The features that are chosen must be discriminative and sufficient for the description of the objects. The key to attaining a successful retrieval system is to choose the right features that represent the images as unique as possible. A feature is a set of characteristics of the image, such as color, texture, and shape. In addition, a feature can be enriched with information about the spatial distribution of the characteristic that it describes. Evaluation of the performance of low-level features is usually done on homogenous benchmarking databases with a limited number of images. In real-world image retrieval systems, databases have a much larger scale and may be heterogeneous. This paper investigates the behavior of Compact Composite Descriptors (CCDs) on heterogeneous databases of a larger scale. Early and late fusion techniques are tested and their performance in distributed image retrieval is calculated. This study demonstrates that, even if it is not possible to overcome the semantic gap in image retrieval by feature similarity, it is still possible to increase the retrieval effectiveness.en
dc.formattextcs
dc.format.extent725-733cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2010/10_04_725_733.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectCBIRen
dc.subjectCompact Composite Descriptorsen
dc.subjectEarly Fusionen
dc.subjectLate Fusionen
dc.subjectDistributed Image Retrievalen
dc.titleInvestigating the Behavior of Compact Composite Descriptors in Early Fusion, Late Fusion and Distributed Image Retrievalen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue4cs
dc.coverage.volume19cs
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Creative Commons Attribution 3.0 Unported License
Except where otherwise noted, this item's license is described as Creative Commons Attribution 3.0 Unported License