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Statistical texture image classification using two-dimensional nonminimum-phase Fourier series based model
Conference paper

Statistical texture image classification using two-dimensional nonminimum-phase Fourier series based model

Chii-Horng Chen and Chong-Yung Chi
IEEE Xplore Digital Library IEEE Signal Processing Workshop on Higher-Order Statistics, p.400
1999

Abstract

statistical analysis;parameter estimation;image texture;image classification;Fourier series;higher order statistics
Using the 2-D extension of Chi's real 1-D parametric nonminimum-phase Fourier series based model (FSBM) for or as an approximation to any arbitrary nonminimum-phase linear time-invariant (LTI) systems, we propose a system identification algorithm for 2-D nonminimum-phase linear shift-invariant (LSI) systems supported by some simulation results. The estimated 2-D FSBM parameters and second- and higher-order statistics obtained using the proposed algorithm constitute effective features for texture image classification supported by some experimental results.

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