Rotation-invariant texture retrieval with gaussianized steerable pyramids

G. Tzagkarakis, B. Beferull-Lozano, P. Tsakalides
2006 IEEE Transactions on Image Processing  
This paper presents a novel rotation-invariant image retrieval scheme based on a transformation of the texture information via a steerable pyramid. First, we fit the distribution of the subband coefficients using a joint alpha-stable sub-Gaussian model to capture their non-Gaussian behavior. Then, we apply a normalization process in order to Gaussianize the coefficients. As a result, the feature extraction step consists of estimating the covariances between the normalized pyramid coefficients.
more » ... he similarity between two distinct texture images is measured by minimizing a rotation-invariant version of the Kullback-Leibler Divergence between their corresponding multivariate Gaussian distributions, where the minimization is performed over a set of rotation angles. Index Terms-Fractional lower-order moments (FLOMs), rotation-invariant Kullback-Leibler divergence (KLD), statistical image retrieval, steerable model, sub-Gaussian distribution.
doi:10.1109/tip.2006.877356 pmid:16948315 fatcat:q23otywtnjanve2nhloxcbwmyy