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Application of Higher-Order Statistics Features of ICA Coefficients in Texture Classification |
XU Xiao-Hong, YANG Xue-Zhi, YANG De-Mei, Gao Jun |
Laboratory of Image Information Processing, School of Computer and Information, Hefei University of Technology, Hefei 230009 |
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Abstract ICA coefficients are non-Gaussian in independent component analysis model. The high-order statistical features are used in characterization of non-Gaussian feature. The combined moments of variance, skewness and kurtosis are proposed to describe the ICA coefficients probability distributing characteristic. The combined moments are used in texture classification and it can achieve better classification performance than the previously reported ICA features. Furthermore, L-moments are used to improve robustness in moments estimation and to get better performance than the ordinary moments.
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Received: 11 June 2008
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