Texture Feature Extraction and Indexing by Hermite Filters

Abstract : We present a texture feature extraction for image indexing and retrieval based on Gabor-like Hermite filters. These ones satisfy a frequency constraint of steered discrete Hermite filters, which form a local orthogonal basis and agree with the Gaussian derivative model of the human visual system. Fast implementation of such filters is performed by a normalized recurrence relation of their discrete representation, the Krawtchouk filters. In order to achieve dimensionality reduction for texture image indexing purposes, we apply a compact parametric texture model, which corresponds to the spatial autocorrelation of each subband output. Experimental results obtained from a texture image database are also presented.
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Carlos Rivero-Moreno, Stéphane Bres. Texture Feature Extraction and Indexing by Hermite Filters. International Conference on Pattern Recognition, ICPR 2004, Aug 2004, Cambridge, United Kingdom. pp.684-687, ⟨10.1109/ICPR.2004.1334266⟩. ⟨hal-01593800⟩



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