Full Citation and Abstract
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Title: |
Object-driven content-based image retrieval |
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Author(s): |
Ioannis Pratikakis, Basilios Gatos, Stavros Perantonis, Iris Vanhamel, Hichem Sahli |
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Address: |
Computational Intelligence Laboratory,
Institute of Informatics and Telecommunications,
National Center for Scientific Research
Demokritos
,
153 10 Athens, Greece
Computational Intelligence Laboratory,
Institute of Informatics and Telecommunications,
National Center for Scientific Research
Demokritos
,
153 10 Athens, Greece
Computational Intelligence Laboratory,
Institute of Informatics and Telecommunications,
National Center for Scientific Research
Demokritos
,
153 10 Athens, Greece
Electronics & Informatics Department
Vrije Universiteit Brussel,
1050 Brussels,Belgium
Electronics & Informatics Department
Vrije Universiteit Brussel,
1050 Brussels,Belgium
ipratika @ iit.demokritos.gr, bgat @ iit.demokritos.gr, sper @ iit.demokritos.gr, iuvanham @ etro.vub.ac.be, hsahli @ etro.vub.ac.be |
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Reference: |
SSIP-SP1, 2005 pp. 189 - 193 |
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Abstract/
Summary |
This paper presents a novel unsupervised strategy for content-based image retrieval. It is based on a meaningful segmentation procedure that can provide proper distributions for matching via the Earth mover's distance as a similarity metric. The segmentation procedure is based on a hierarchical watershed-driven algorithm that extracts meaningful regions automatically. In this framework, the proposed robust feature extraction and the many-to-many region matching along with the novel region weighting for enhancing feature discrimination play a major role. Experimental results demonstrate the performance of the proposed strategy. |
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