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On the Usage of Clustering for Content Based Image Retrieval.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Pandu Rangan, C.
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Diekert, Volker
Volkov, Mikhail V.
Voronkov, Andrei
Manjarrez Sanchez, Jorge R.
Martinez, Jose
Source :
Computer Science - Theory & Applications (9783540745099); 2007, p281-289, 9p
Publication Year :
2007

Abstract

Retrieval of images based on the content is a process that requires the comparison of the multidimensional representation of the contents of a given example with all of those images in the database. To speed up this process, several indexing techniques have been proposed. All of them do efficiently the work up to 30 dimensions [8]. Above that, their performance is affected by the properties of the multidimensional space. Facing this problem, one alternative is to reduce the dimensions of the image representation which however conveys an additional loss of precision. Another approach that has been studied and seems to exhibit good performance is the clustering of the database. On this article we analyze this option from a computational complexity approach and devise a proposal for the number of clusters to obtain from the database, which can lead to sublinear algorithms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540745099
Database :
Complementary Index
Journal :
Computer Science - Theory & Applications (9783540745099)
Publication Type :
Book
Accession number :
33422055
Full Text :
https://doi.org/10.1007/978-3-540-74510-5_29