In this communication, a robust, fast and efficient surface registration approach for 3D surfaces is presented. The robusteness of such approach is based on particular features points involved in the process and that make the matching step more precise. Such feature descriptors are extracted from the superposition of two surfacic curves: geodesic levels and radial ones from local neighborhoods defined around reference points already picked on the surface. Moreover, by a generalized version of Shannon theorem, an optimal number of such descriptors points is identified in order to reduce the computational time. Thus, the obtained discretized parametrisation (ordered descriptors) is the basis of the matching phase that becomes obvious and more robust comparing to the classic ICP algorithm. An evaluation of the proposed approach is realized in the mean of complexity time, robusteness of the matching and efficiency. Experimentations are conducted on facial surfaces from the Bosphorus database to estimate the discriminative power in face description.