Texture classification on block-transformed data

Bo Tao; Bradley W. Dickinson

doi:10.1117/12.263308

10 January 1997 Texture classification on block-transformed data

Bo Tao, Bradley W. Dickinson

Proceedings Volume 3024, Visual Communications and Image Processing '97; (1997) https://doi.org/10.1117/12.263308
Event: Electronic Imaging '97, 1997, San Jose, CA, United States

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.

Citation Download Citation

Bo Tao and Bradley W. Dickinson "Texture classification on block-transformed data", Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); https://doi.org/10.1117/12.263308

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