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Proceedings Paper

Texture classification on block-transformed data
Author(s): Bo Tao; Bradley W. Dickinson
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Paper Abstract

We introduce two texture classification techniques applicable to images compressed using block DCT. The first technique is a parametric approach. It models a texture as a stationary Gaussian process and utilizes the diagonalizing property of DCT. The second one uses the concept of power spectrum in the DCT domain. The energy distribution is employed to discriminate different textures. Both techniques work on compressed data without decoding and are designed to be robust against quantization noise.

Paper Details

Date Published: 10 January 1997
PDF: 7 pages
Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); doi: 10.1117/12.263308
Show Author Affiliations
Bo Tao, Princeton Univ. (United States)
Bradley W. Dickinson, Princeton Univ. (United States)

Published in SPIE Proceedings Vol. 3024:
Visual Communications and Image Processing '97
Jan Biemond; Edward J. Delp III, Editor(s)

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