Analyse factorielle des correspondances pour l'indexation et la recherche d'information dans une grande base de données d'images

Khang-Nguyen Pham 1, 2
1 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : With the development of the digital world, the number of images stored in databases has significantly increased. Images indexing and information retrieval in image databases are more complicated than in the case of textual documents. Indexing methods already used in textual data analysis are proposed to process images, To transfer the results of the textual data analysis to images, new features are required: visual words an images are considered as documents. We are interested in the problem of indexing and information retrieval in a large database of images using data analysis methods and, more specifically, using Factorial Correspondence Analysis (FCA). First, we propose to use relevant indicators of FCA to speed up the retrieval step after adapting it to images. Next, we study the large-scale retrieval with FCA. TO this end, we propose an incremental FCA algorithm to deal with large contingency tables and its parallelization on Graphics Processing Units (GPU). We also develop a parallel version of our research algorithm using relevant indicators of FCA on GPUs. After that, we combine the use of FCA with other methods such as the Contextual Dissimilarity Measure and random forests in order to improve the retrieval quality. Finally, we present a visualization environment, CAViz, which allows us to display the results.
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Submitted on : Friday, November 5, 2010 - 10:54:15 AM
Last modification on : Friday, November 16, 2018 - 1:24:01 AM
Long-term archiving on : Sunday, February 6, 2011 - 2:31:20 AM

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  • HAL Id : tel-00532574, version 1

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Khang-Nguyen Pham. Analyse factorielle des correspondances pour l'indexation et la recherche d'information dans une grande base de données d'images. Interface homme-machine [cs.HC]. Université Rennes 1, 2009. Français. ⟨tel-00532574⟩

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