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De l'usage des méthodes bas niveau pour la recherche d'image par le contenu

Abstract : The matter of this work is content based image retrieval and more precisely the contribution
of the low level methods.
After having discussed the various existing approaches, we recall the semantic gap between
the user expectations and what really the systems of research propose. Most of these approaches
rely on a preliminary step of segmentation whose validity and robustness must be studied. Then
we propose a protocol of evaluation and a practical example of benchmarks. The originality
consists in not comparing a segmentation with a theoretical reference but judging its stability
The third part of this document introduces three specific contributions likely to improve the
chain of research. Initially, a detector of blur allows to extract a meta-data carried by the image:
the unblur regions, a priori of focusing. Secondly, we expose a descriptor based on the extraction
of emergent areas using only the color criteria. This process, combined with adapted distances,
may allow for example a color pre-filtering before the step of similarity research . Finally, we
briefly introduce an algebra of histograms able as well as possible to exploit the information
contained in this type of descriptors, via a specific query language.
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Contributor : Jérôme Da-Rugna Connect in order to contact the contributor
Submitted on : Saturday, May 20, 2006 - 2:22:07 PM
Last modification on : Wednesday, November 20, 2019 - 3:12:03 AM
Long-term archiving on: : Sunday, April 4, 2010 - 9:57:02 PM


  • HAL Id : tel-00070811, version 1



Jérôme da Rugna. De l'usage des méthodes bas niveau pour la recherche d'image par le contenu. Interface homme-machine [cs.HC]. Université Jean Monnet - Saint-Etienne, 2004. Français. ⟨NNT : ⟩. ⟨tel-00070811⟩



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