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Proceedings Paper

A new texture representation with multi-scale wavelet feature
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Paper Abstract

The existing methods for texture modeling include co-occurrence statistics, filter banks and random fields. However most of these methods lack of capability to characterize the different scale of texture effectively. In this paper, we propose a texture representation which combines local scale feature, amplitude and phase of wavelet modules in multi-scales. The self-similarity of texture is not globally uniform and could be measured in both correlations across the multi-scale and statistical feature within a single-scale. In our approach, the local scale feature is represented by optimal scale obtained through the evolution of wavelet modulus across multi-scales. Then, for all the blocks of the same optimal scale, the statistical measurement of amplitude is extracted to represent the energy within the corresponding frequency band; the statistical measurement of the phase of modulus is extracted to represent the texture's orientation. Our experiment indicates that, in the proposed texture representation the separability of different texture patterns is larger than the one of the traditional features.

Paper Details

Date Published: 12 May 2006
PDF: 12 pages
Proc. SPIE 6246, Visual Information Processing XV, 62460X (12 May 2006); doi: 10.1117/12.664388
Show Author Affiliations
Sheng Yi, Huazhong Univ. of Science and Technology (China)
Hanqiang Cao, Huazhong Univ. of Science and Technology (China)
Xutao Li, Huazhong Univ. of Science and Technology (China)
Miao Liu, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 6246:
Visual Information Processing XV
Zia-ur Rahman; Stephen E. Reichenbach; Mark A. Neifeld, Editor(s)

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