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A Generalized Metric Distance between Hierarchically Partitioned Images

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Date
2005
Dewey
Programmation, logiciels, organisation des données
Sujet
recursive image decomposition; quad/quin/nona-tree; Image database; content-based image retrieval; multi-level filtering; image region similarity
Conference country
UNITED STATES
Book title
Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data
Author
Masseglia, Florent
Publisher
ACM
Year
2005
ISBN
1-59593-216-X
URI
https://basepub.dauphine.fr/handle/123456789/5996
Collections
  • LAMSADE : Publications
Metadata
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Author
Jomier, Geneviève
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Manouvrier, Maude
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Rukoz, Marta
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Type
Communication / Conférence
Item number of pages
33-41
Abstract (EN)
This article presents a generalized metric distance, called $\Delta$-distance, between images represented by a tree structure resulting from a recursive image partition. This distance is used to perform content-based image retrieval queries in databases. Delta-distance allows to retrieve images globally similar to a query image. This distance takes into account the location of the image visual features. It can be performed using a multi-level filtering algorithm. Moreover, Delta-distance allows region-based queries. In this case, the resulting images contain quadrants similar to the quadrants selected by the user in the query image or contain quadrants similar to the entire query image. Because it is a generalized distance function, some particular cases of the $\Delta$-distance appear in existing content-based image retrieval systems.

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