Determination of Fibre Orientation Distribution from Images of Fibre Networks

Abstract

We recall two categories of algorithms for estimating fibre orientation distribution from an image of a spatial fibre system. In the first algorithm, the estimate is a magnitude-weighted distribution from angles perpendicular to the directions of the gradients in the image. The second algorithm is based on the scaled variogram of grey values scanned along a sampling line and its relation to the fibre orientation distribution. Using lines in several directions and assuming a parametric model for the orientation distribution, the orientation parameters are estimated numerically from a least-squares type procedure. Two versions of variogram-based methods are used in this work. We compare the potential of these three methods by simulated images of fibrous layers and their thresholded versions. All the methods were found to reproduce the original distribution with a good accuracy in the case of greyscale images where grammage, anisotropy and orientation angle are within the typical ranges of paper parameters. On the contrary, the variogram-based methods seem to handle the estimation of anisotropy in binary images more efficiently.