Abstract. The graphene is a material obtained when carbon atoms form large planar molecules. Well organized, large graphene molecules stacked ontop each other convey to graphene particularly interesting properties useful in nuclear industry. Understanding how the organization on the molecular scale influences the mechanical properties of the material is a key element in the material manufacturing process. In this scope, features like local orientation and length have already been largely explored in the literature. This paper brings a new feature evaluating the number of plans stacked ontop each other and the length of this stacking. It allows obtaing other features such as the overall rate of organization or locality and preferential orientation. These informations, synthesized in the form of histograms provides a key information in the processus the material design. Experimental results obtained on images taken by an electronic scanning microscope are presented to illustrate the proposed method.

This paper addresses a registration problem for an industrial control application: it meets the need to registrate a model on an image of a flexible object. We propose a non-rigid shape registration approach that deals with a great disparity of the number of points in the model and in the manufactured object. We have developed a method based on a classical minimization process combining a distance term and a regularization term. We observed that, even if the control points fall on the object boundary, the registration failed on high curvature points. In this paper we add a curvature-based term in order to improve the registration on object extremities. We validate our approach on a real industrial application. The addition of this curvature term reduces by two the error of the inner boundaries location on the previously problematic cases of our database.

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