The current question is mostly about the compromise between image resolution and volume of data being analyzed, to extract accurate information allowing for the characterization of the fibrous material. Among those statistics, we focus here particularly on the distribution of fiber orientations within the material. We will highlight three different approaches that may operate at different resolutions to provide insights about the fiber orientations.
After presenting these different methods in a first part, we will then describe the data used for this study. We will apply the described procedures to real data that has been acquired by a state of the art µCT system. We will also work with an artificial dataset generated with user-defined properties, which provides us with a gold standard reference against which the result methods can be evaluated. For both real and synthetic data, we will also investigate the behavior of the proposed approaches with respect to the scanning resolution, simulated here by applying them on down-sampled versions of the same original images. The obtained results will be presented in section 3, allowing us to draw conclusions on the respective merits of the proposed estimation methods.
