Outline Shape Retrieval Using Textual Descriptors and Geometric Features

Saliha Aouat and Slimane Larabi
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Saliha Aouat: LRIA Laboratory, Department of Computer Science, University of Sciences and Technology– Houari Boumediene, Algiers, Algeria
Slimane Larabi: LRIA Laboratory, Department of Computer Science, University of Sciences and Technology– Houari Boumediene, Algiers, Algeria

International Journal of Information Retrieval Research (IJIRR), 2012, vol. 2, issue 4, 60-81

Abstract: Content_based image retrieval is a promising approach because of its automatic indexing, recognition and retrieval. This paper is a contribution in the field of the content Based Image Retrieval (CBIR). Objects are represented by their outlines shapes (silhouettes) and described following the XLWDOS Textual Description (Larabi et al., 2003). Textual Descriptors are sensitive to noise. The authors have already developed an approach to smooth the outlines at different scales (Aouat & Larabi, 2010). The smoothing is performed by applying a convolution using the Gaussian Filter to process noisy shapes in order to match shapes descriptors. The authors have also applied an indexing process after silhouettes smoothing (Aouat & Larabi, 2009). The approaches (Aouat & Larabi, 2010; Aouat & Larabi, 2009) are very interesting for shape matching and indexing, but unfortunately, they are not appropriate to the recognition and retrieval processes because there is no use of similarity measures. In order to perform the retrieval process and select the best model for a query silhouette, the authors use in this paper Geometric features extracted from Textual Description of Outline Shapes.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jirr00:v:2:y:2012:i:4:p:60-81

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