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PubMed · 12446034

A spectral histogram model for texton modeling and texture discrimination.

Xiuwen Liu·DeLiang Wang
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Abstract

We suggest a spectral histogram, defined as the marginal distribution of filter responses, as a quantitative definition for a texton pattern. By matching spectral histograms, an arbitrary image can be transformed to an image with similar textons to the observed. We use the chi(2)-statistic to measure the difference between two spectral histograms, which leads to a texture discrimination model. The performance of the model well matches psychophysical results on a systematic set of texture discrimination data and it exhibits the nonlinearity and asymmetry phenomena in human texture discrimination. A quantitative comparison with the Malik-Perona model is given, and a number of issues regarding the model are discussed.

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Discrimination, PsychologicalHumansModels, BiologicalPattern Recognition, VisualJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, Non-P.H.S.

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Xiuwen Liu, DeLiang Wang. 2002. A spectral histogram model for texton modeling and texture discrimination.. https://doi.org/10.1016/s0042-6989(02)00297-3

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