Region-based image indexing and retrieval inspired by text search (Contributo in atti di convegno)

Type
Label
  • Region-based image indexing and retrieval inspired by text search (Contributo in atti di convegno) (literal)
Anno
  • 2007-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/ICIAPW.2007.37 (literal)
Alternative label
  • Amato G.; Magionami V.; Savino P. (2007)
    Region-based image indexing and retrieval inspired by text search
    in International Workshop on Visual and Multimedia Digital Libraries. In conjunction to ICIAP 2007, Modena, 11-13 Sept. 2007
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Amato G.; Magionami V.; Savino P. (literal)
Pagina inizio
  • 101 (literal)
Pagina fine
  • 106 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4427484&tag=1 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • In: International Workshop on Visual and Multimedia Digital Libraries. In conjunction to ICIAP 2007 (Modena, 10-14 September 2007). Proceedings, pp. 101 - 106. IEEE Computer Society, 2007. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto
  • ABSTRACT: In this paper we present an approach for image similarity search that takes inspiration from text retrieval. Images are indexed using visual terms chosen from a visual lexicon. Each visual term represents a typology of visual regions, according to various criteria. The visual lexicon is obtained by analyzing a training set of images, to infer which are the relevant typology of visual regions. We have defined a weighting and matching schema that are able respectively to associate visual terms with images and to compare images by means of the associated terms. We show that the proposed approach do not lose performance, in terms of effectiveness, with respect to other methods existing in literature, and at the same time offers higher performance, in terms of efficiency, given the possibility of using inverted files to support similarity searching. The proposed techniques were implemented in a running prototype. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • ISTI-CNR (literal)
Titolo
  • Region-based image indexing and retrieval inspired by text search (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-0-7695-2921-9 (literal)
Abstract
  • In this paper we present an approach for image similarity search that takes inspiration from text retrieval. Images are indexed using visual terms chosen from a visual lexicon. Each visual term represents a typology of visual regions, according to various criteria. The visual lexicon is obtained by analyzing a training set of images, to infer which are the relevant typology of visual regions. We have defined a weighting and matching schema that are able respectively to associate visual terms with images and to compare images by means of the associated terms. We show that the proposed approach do not lose performance, in terms of effectiveness, with respect to other methods existing in literature, and at the same time offers higher performance, in terms of efficiency, given the possibility of using inverted files to support similarity searching. The proposed techniques were implemented in a running prototype. (literal)
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