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TMM
2002

Rotation invariant texture characterization and retrieval using steerable wavelet-domain hidden Markov models

8 years 11 months ago
Rotation invariant texture characterization and retrieval using steerable wavelet-domain hidden Markov models
We present a new statistical model for characterizing texture images based on wavelet-domain hidden Markov models. With a small number of parameters, the new model captures both the subband marginal distributions and the dependencies across scales and orientations of the wavelet descriptors. Applying to the steerable pyramid, once it is trained for an input texture image, the model can be easily steered to characterize that texture at any other orientation. Furthermore, after a diagonalization operation, we obtain a rotation-invariant model of the texture image. We also propose a fast algorithm to approximate the Kullback
Minh N. Do, Martin Vetterli
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where TMM
Authors Minh N. Do, Martin Vetterli
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