1. An image processing system, for correlating shapes in multi-dimensional images (m-D), comprising image data processing means for estimating a similarity measure including computing means for: estimating two image signals (f( x ), g( y )) representing shapes defined in respective windows (W 1 , W 2 ) in two multi-dimensional images; using a Hermite Transform (HT) applied to both said image signals for performing an evaluation of two first sets of scalar valued Hermite coefficients (f I , g I , F I , G I ), from which a combination yields a transformed set of scalar valued Hermite coefficients {K I }; applying the inverse Hermite Transform (HT −1 ) to the transformed set of scalar valued Hermite coefficients {K I } to achieve the computation of a windowed correlation function (K( v ); and estimating the maximum of said windowed correlation function as the wanted similarity measure to correlate the shapes; and means for displaying the correlated shapes and/or processed images.