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A Flexible Image Retrieval Framework.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Shi, Yong
van Albada, Geert Dick
Dongarra, Jack
Sloot, Peter M. A.
Pein, Raoul Pascal
Source :
Computational Science: ICCS 2007 (9783540725879); 2007, p754-761, 8p
Publication Year :
2007

Abstract

This paper discusses a framework for image retrieval. Most current systems are based on a single technique for feature extraction and similarity search. Each technique has its advantages and drawbacks concerning the result quality. Usually they cover one or two certain features of the image, e.g. histograms or shape information. The proposed framework is designed to be highly flexible, even if performance may suffer. The aim is to give people a platform to implement almost any kind of retrieval issues very quickly, whether it is content based or somehing else. The second advantage of the framework is the possibility to change retrieval characteristics within the program completely. This allows users to configure the ranking process as needed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540725879
Database :
Complementary Index
Journal :
Computational Science: ICCS 2007 (9783540725879)
Publication Type :
Book
Accession number :
33155327
Full Text :
https://doi.org/10.1007/978-3-540-72588-6_124