Segmentation of 2d and 3d Textures From Estimates of the Local Orientation

Abstract

We use a method to estimate local orientations in the n-dimensional space from the covariance matrix of the gradient, which can be implemented either in the image space or in the Fourier space. In a second step, two methods allow us to detect sudden changes of orientation in images. The first one uses an index of confidence of the estimated orientation, and the second one the detection of minima of scalar products in a neighbourhood. This is illustrated on 2D Transmission Electrons Microscope images of cellulose cryofracture (to display the organisation of cellulose whiskers and the points of germination), and to 3D images of a TA6V alloy (lamellar microstructure) obtained by microtomography.

3d Directional Mathematical Morphology for Analysis of Fiber Orientations

“…There exist also theoretical solutions for the eigenvalue problem in 3D (Jeulin and Moreaud, 2008). With this, it is possible to deduce an equation for the inertia moments and the inertia vectors.…”

3D composite reinforcement meso F.E. analyses based on X-ray computed tomography

“…This phase of the process is critical because it impacts the quality of the model significantly. Several segmentation methods are available, one of them, based on the image's structural tensor, seems interesting [42,46,47]. This tensor defines the orientation of fibres in a yarn.…”

Multistage Segmentation of Lamellae Colonies Based on Directional Filter Bank and PCA Analysis

“…The algorithm has been already used by Jeulin and Moreaud [7] to extract local gradient map which in turn is an input for PCA to detect orientation discontinuities in textured images. This has been further coupled with a semi-automatic watershed-based method to separate α-colonies in microtomographic images of titanium alloy [14].…”

“…In addition, the [8] proposed a method based on the gradient of brightnes. The method was an attempt to modify the algorithm proposed in [7], the orientation of directional alpha-colony was determined by the gradient brightness, image segmentation relied on the use of clustering and classification methods of information direction.…”