Abstract
This paper addresses the problem of texture retrieval by using a perceptual approach based on multiple viewpoints. We use a set of features that have a perceptual meaning corresponding to human visual perception. These features are estimated using a set of computational features that can be based on two viewpoints: the original images viewpoint and the autocovariance function viewpoint. The set of computational measures is applied to content-based image retrieval (CBIR) on a large image data set, the well-known Brodatz database, and is shown to give better results compared to related approaches. Furthermore, results fusion returned by each of the two viewpoints allows significant improvement in search effectiveness.
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Abbadeni, N. (2006). Perceptual Image Retrieval. In: Bres, S., Laurini, R. (eds) Visual Information and Information Systems. VISUAL 2005. Lecture Notes in Computer Science, vol 3736. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590064_23
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DOI: https://doi.org/10.1007/11590064_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30488-3
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