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1998
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Texture Recognition Using a Non-Parametric Multi-Scale Statistical Model

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Texture Recognition Using a Non-Parametric Multi-Scale Statistical Model
We describe a technique for using the joint occurrence of local features at multiple resolutions to measure the similarity between texture images. Though superficially similar to a number of "Gabor" style techniques, which recognize textures through the extraction of multi-scale feature vectors, our approach is derived from an accurate generative model of texture, which is explicitly multiscale and non-parametric. The resulting recognition procedure is similarly non-parametric, and can model complex non-homogeneous textures. We report results on publicly available texture databases. In addition, experiments indicate that this approach may have sufficient discrimination power to perform target detection in synthetic aperture radar images (SAR).
Jeremy S. De Bonet, Paul A. Viola
Added 12 Oct 2009
Updated 30 Oct 2009
Type Conference
Year 1998
Where CVPR
Authors Jeremy S. De Bonet, Paul A. Viola
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