Rotational Invariant Operators Based on Steerable Filter Banks

We introduce a technique for designing rotation invariant operators based on steerable filter banks. Steerable filters are widely used in computer vision as local descriptors for texture analysis. Rotation invariance has been shown to improve texture-based classification in certain contexts. Our approach to invariance is based on solving the partial differential equation associated with the formulation of invariance in a Lie group framework.