Stammdaten

Titel: Localizing global descriptors for content-based image retrieval
Untertitel:
Kurzfassung:

In this paper, we explore, extend and simplify the localization of the description ability of the well-established MPEG-7 (Scalable Colour Descriptor (SCD), Colour Layout Descriptor (CLD) and Edge Histogram Descriptor (EHD)) and MPEG-7-like (Color and Edge Directivity Descriptor (CEDD)) global descriptors, which we call the SIMPLE family of descriptors. Sixteen novel descriptors are introduced that utilize four different sampling strategies for the extraction of image patches to be used as points of interest. Designing with focused attention for content-based image retrieval tasks, we investigate, analyse and propose the preferred process for the definition of the parameters involved (point detection, description, codebook sizes and descriptors’ weighting strategies). The experimental results conducted on four different image collections reveal an astonishing boost in the retrieval performance of the proposed descriptors compared to their performance in their original global form. Furthermore, they manage to outperform common SIFT- and SURF-based approaches while they perform comparably, if not better, against recent state-of-the-art methods that base their success on much more complex data manipulation.

Schlagworte:
Publikationstyp: Beitrag in Zeitschrift (Autorenschaft)
Erscheinungsdatum: 09.2015 (Online)
Erschienen in: EURASIP Journal on Advances in Signal Processing
EURASIP Journal on Advances in Signal Processing
zur Publikation
 ( Springer Verlag GmbH; )
Titel der Serie: -
Bandnummer: -
Heftnummer: -
Erstveröffentlichung: Ja
Version: -
Seite: -

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Keine Version vorhanden
Erscheinungsdatum: 09.2015
ISBN (e-book): -
eISSN: 1687-6180
DOI: http://dx.doi.org/10.1186/s13634-015-0262-6
Homepage: http://link.springer.com/article/10.1186%2Fs13634-015-0262-6
Open Access
  • Online verfügbar (nicht Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Österreich
   martina.steinbacher@aau.at
http://itec.aau.at/
zur Organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 1020 - Informatik
Forschungscluster
  • Selbstorganisierende Systeme
Zitationsindex
  • Science Citation Index Expanded (SCI Expanded)
Informationen zum Zitationsindex: Master Journal List
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: II)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Distributed Multimedia Systems

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Beiträge der Publikation

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