Texture Feature Extraction and Indexing by Hermite Filters

  • Authors:
  • Carlos Joel Rivero-Moreno;Stephane Bres

  • Affiliations:
  • LIRIS, France;LIRIS, France

  • Venue:
  • ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
  • Year:
  • 2004

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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.