Texture Analysis using Level-crossing Statistics

Abstract

We present a novel statistical texture descriptor employing level-crossing statistics. Images are first mapped into 1D signals using space-filling curves, such as Peano or Hilbert curves, and texture features are extracted via signaldependent sampling. Texture parameters are based on the level-crossing statistics of the 1D signal, i.e. crossing rate, crossing slope and sojourn time. Despite the simplicity of texture features used, our approach offers state-of-the art performance in the texture classification and texture segmentation tasks, outperforming other tested algorithms.

DOI: 10.1109/ICPR.2004.1334358

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@inproceedings{Santamaria2004TextureAU, title={Texture Analysis using Level-crossing Statistics}, author={Carlos Santamaria and Miroslaw Bober and Wieslaw Szajnowski}, booktitle={ICPR}, year={2004} }