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.
Original language | English |
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Title of host publication | Computational Science - ICCS 2007 |
Subtitle of host publication | 7th International Conference, Proceedings |
Editors | Yong Shi, Geert Dick van Albada, Jack Dongarra, Peter M. A. Sloot |
Publisher | Springer-Verlag Berlin Heidelberg |
Pages | 754-761 |
Number of pages | 8 |
Edition | PART 3 |
ISBN (Electronic) | 9783540725886 |
ISBN (Print) | 9783540725879 |
DOIs | |
Publication status | Published - 1 Dec 2007 |
Event | 7th International Conference on Computational Science - Beijing, China Duration: 27 May 2007 → 30 May 2007 Conference number: 7 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Number | PART 3 |
Volume | 4489 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 7th International Conference on Computational Science |
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Abbreviated title | ICCS2007 |
Country/Territory | China |
City | Beijing |
Period | 27/05/07 → 30/05/07 |