Autocorrelation fitting for texture orientation estimation

The problem of short-term texture orientation is dealt with in this paper through autocorrelation fitting. Actually, the computation of the estimated autocorrelation sequence from a textured oriented image brings about the apparition of an oriented pattern. This pattern is looked upon, in this work, as a Gaussian curve, the parameters of which give an estimated orientation. Those parameters are estimated by a two-dimensional (2-D) curve fitting on a particular region of the autocorrelation. The determination of this region is done automatically thanks to watersheds. The algorithm is developed for synthetic textured images but appears to be effective when applied to real life oriented images.