Depriester Dorian, Rolland du Roscoat Sabine, Orgéas Laurent, Geindreau Christian, Levrard Benjamin, Brémond Florian
3SR, UMR 5521, Université Grenoble Alpes, CNRS, G-INP, Grenoble, France.
Michelin Corporation, European Center of Technologies, Clermont-Ferrand, France.
J Microsc. 2022 Jun;286(3):220-239. doi: 10.1111/jmi.13096. Epub 2022 Mar 23.
Modelling the physical behaviour of fibrous materials still remains a great challenge because it requires to evaluate the inner structure of the different phases at the phase scale (fibre or matrix) and the at constituent scale (fibre). X-ray computed tomography (CT) imaging can help to characterize and to model these structures, since it allows separating the phases, based on the grey level of CT scans. However, once the fibrous phase has been isolated, automatically separating the fibres from each other is still very challenging. This work aims at proposing a method which allows separating the fibres and localizing the fibre-fibre contacts for various fibres geometries, that is: straight or woven fibres, with circular or non-circular cross sections, in a way that is independent of the fibres orientations. This method uses the local orientation of the structure formed by the fibrous phase and then introduces the misorientation angle. The threshold of this angle is the only parameter required to separate the fibres. This paper investigates the efficiency of the proposed algorithm in various conditions, for instance by changing the image resolution or the fibre tortuosity on synthetic images. Finally, the proposed algorithm is applied to real images or samples made up of synthetic solid fibres.
对纤维材料的物理行为进行建模仍然是一个巨大的挑战，因为这需要在相尺度（纤维或基体）和组分尺度（纤维）上评估不同相的内部结构。X射线计算机断层扫描（CT）成像有助于对这些结构进行表征和建模，因为它可以根据CT扫描的灰度水平分离各相。然而，一旦分离出纤维相，自动将纤维彼此分离仍然非常具有挑战性。这项工作旨在提出一种方法，该方法能够以与纤维取向无关的方式，分离各种纤维几何形状（即直纤维或编织纤维，圆形或非圆形横截面）的纤维并定位纤维与纤维之间的接触点。该方法利用纤维相形成的结构的局部取向，然后引入取向差角。这个角度的阈值是分离纤维所需的唯一参数。本文研究了该算法在各种条件下的效率，例如通过改变合成图像的分辨率或纤维的曲折度。最后，将所提出的算法应用于由合成实心纤维组成的真实图像或样本。
