Work

A skeletonization-based approach for individual fiber separation in tomography images of biocomposites

Year: 2024

Type: article

Abstract: The separation individual fibers is a persistent challenge in analyzing fiber composites and fibrous materials with X-ray microtomography. A variety of approaches have been published, but they generally work poorly for heterogeneous fibers with varying cross sections, orientations, lengths and shapes. We present a skeletonization-based method that can separate highly curled and heterogeneous pulp fibers in biocomposites with thickness close to the resolution limit. Optical pulp analysis for fibers extracted from the composites is used as a reference. We show that while the mean length is underestimated by our method, the shape features are better analyzed than in the reference method as fibers are not extracted or swollen in water. Our analysis reveals that the shape factor and orientation of fibers have power law dependencies on fiber length. The fiber separation and analysis method can be used as a basis for numerical modeling of the materials. • A new method to separate individual fibers from X-ray microtomography data. • Can handle irregular fibers with varying length and sharp kinks. • The effectiveness is demonstrated with biocomposites containing pulp fibers. • Useful for extracting shape characteristics of the fibers. • Allows collecting statistics for building a reconstructed microstructure model.

Source: Computational Materials Science

DOI: 10.1016/j.commatsci.2024.113372

Authors: Tuukka Verho, Tuomas Turpeinen, Faizan Asad, Kirsi Immonen

Institution: VTT Technical Research Centre of Finland

Language: English

Topic: Digital Image Processing Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,190

Funders: Academy of Finland, Business Finland