Gaussian MRF rotation-invariant features for image classification

@article{Deng2004GaussianMR,
  title={Gaussian MRF rotation-invariant features for image classification},
  author={Huawu Deng and David A. Clausi},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2004},
  volume={26},
  pages={951-955}
}
Features based on Markov random field (MRF) models are sensitive to texture rotation. This paper develops an anisotropic circular Gaussian MRF (ACGMRF) model for retrieving rotation-invariant texture features. To overcome the singularity problem of the least squares estimate method, an approximate least squares estimate method is designed and implemented. Rotation-invariant features are obtained from the ACGMRF model parameters using the discrete Fourier transform. The ACGMRF model is… CONTINUE READING
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