Rotation-invariant texture features from the steered Hermite transform

Authors:
Alfonso Estudillo-Romero;Boris Escalante-Ramirez
Affiliations:
Universidad Nacional Autonoma de Mexico, Fac. de Ingenieria, Edif. de Posgrado e Investigacion, Ciudad Universitaria, C.P. 04510, Mexico, D.F., Mexico;Universidad Nacional Autonoma de Mexico, Fac. de Ingenieria, Edif. de Posgrado e Investigacion, Ciudad Universitaria, C.P. 04510, Mexico, D.F., Mexico
Venue:
Pattern Recognition Letters
Year:
2011

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Abstract

We propose the steered Hermite transform to analyze and capture visual patterns from textures regardless their orientation. Visual texture information is locally described as one dimensional patterns by steering the Cartesian Hermite coefficients according to the energy direction; therefore, no predefined orientation selective filters are required. We evaluate classification accuracy of some texture features individually. During the training stage, a filter selection strategy based on the augmented variance ratio analysis of the training features is employed in order to determine the filters that provide better classification accuracy and reduce computational costs during the classification stage.