Computing oriented texture fields

Abstract

A novel algorithm for computing the orientation field for a flowlike texture is presented. The basic idea behind the algorithm is to use an oriented filter, namely the gradient of the Gaussian, and perform manipulations on the resulting gradient vector field. The most important aspect of the algorithm is that it is provably optimal in estimating the local orientations of an oriented texture. An added strength of the algorithm is that it is simpler and has a better signal-to-noise ratio than previous approaches, because it utilizes fewer derivative operations. Also proposed is a measure of coherence which is based on the use of the angle and coherence images as intrinsic images. An analysis of oriented textures requires the computation of these intrinsic images as a first step. In this sense, the computation of the orientation field, resulting in the intrinsic images, is indispensable in the analysis of oriented textures. Results from a number of experiments indicate the usefulness of the angle and coherence intrinsic images.