Rotation invariant texture analysis: A comparative study


The problem of recognizing rotated homogeneous textured images is addressed. The aim is to provide some comparison results between two classical non-parametric techniques — namely Zernike moments and Fourier-Mellin descriptors — and a new parametric approach involving the Wold decomposition of 1-D processes. In order to obtain translation invariance, all these methods start with the computation of the 2-D normalized autocovariance of textures. The techniques and numerical aspects of the computation of invariant features are briefly described. Experiments performed on a texture database show that the parametric model provides encouraging recognition rates comparable with the Zernike moments, along with the important advantage of its parcimony w.r.t. the classical approaches.

Cite this paper

@article{Rosenberger2000RotationIT, title={Rotation invariant texture analysis: A comparative study}, author={Christophe Rosenberger and Claude Cariou and Kacem Chehdi}, journal={2000 10th European Signal Processing Conference}, year={2000}, pages={1-4} }