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arXiv · 1304.1568

Multiscale Fractal Descriptors Applied to Texture Classification

João Batista Florindo·Odemir Martinez Bruno
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Abstract

This work proposes the combination of multiscale transform with fractal descriptors employed in the classification of gray-level texture images. We apply the space-scale transform (derivative + Gaussian filter) over the Bouligand-Minkowski fractal descriptors, followed by a threshold over the filter response, aiming at attenuating noise effects caused by the final part of this response. The method is tested in the classification of a well-known data set (Brodatz) and compared with other classical texture descriptor techniques. The results demonstrate the advantage of the proposed approach, achieving a higher success rate with a reduced amount of descriptors.

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BibTeXRIS

João Batista Florindo, Odemir Martinez Bruno. 2013-04-04. Multiscale Fractal Descriptors Applied to Texture Classification. https://doi.org/10.1088/1742-6596%2F410%2F1%2F012022

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