A Flexible Image Retrieval Framework

Raoul Pascal Pein, Zhongyu Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

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 languageEnglish
Title of host publicationComputational Science - ICCS 2007
Subtitle of host publication7th International Conference, Proceedings
EditorsYong Shi, Geert Dick van Albada, Jack Dongarra, Peter M. A. Sloot
PublisherSpringer-Verlag Berlin Heidelberg
Pages754-761
Number of pages8
EditionPART 3
ISBN (Electronic)9783540725886
ISBN (Print)9783540725879
DOIs
Publication statusPublished - 1 Dec 2007
Event7th International Conference on Computational Science - Beijing, China
Duration: 27 May 200730 May 2007
Conference number: 7

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume4489 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Computational Science
Abbreviated titleICCS2007
CountryChina
CityBeijing
Period27/05/0730/05/07

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  • Cite this

    Pein, R. P., & Lu, Z. (2007). A Flexible Image Retrieval Framework. In Y. Shi, G. D. van Albada, J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science - ICCS 2007 : 7th International Conference, Proceedings (PART 3 ed., pp. 754-761). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4489 LNCS, No. PART 3). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-540-72588-6_124