Eigenparticles: characterizing particles using eigenfaces

• Published in: Granular matter 2019-08, Vol.21 (3), p.1-9, Article 45
• Main Authors: Higham, J. E., Vaidheeswaran, A., Benavides, K., Shepley, P.
• Format: Article
• Language: English
• Subjects: Coining; Complex Fluids and Microfluidics; Eigenfaces; Eigenfeatures; Eigenparticles; Engineering Fluid Dynamics; Engineering Thermodynamics; Foundations; Geoengineering; Heat and Mass Transfer; Hydraulics; Industrial Chemistry/Chemical Engineering; Materials Science; Multiphase flow; Original Paper; Particle characterization; Particle shape; Pattern recognition; Physics; Physics and Astronomy; PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; Principle components analysis; Roundness; Shape factor; Soft and Granular Matter
• ISSN: 1434-5021; 1434-7636
• DOI: 10.1007/s10035-019-0900-z

The shape characteristics of particles have a pinnacle role in microsopic and macroscopic features of a system. Several studies have highlighted the need for considering deviations from a spherical representation of particles for accurate modeling of granular and multiphase flow systems. Using a shape factor, sphericity or roundness parameter alone is proven to be inadequate to capture the physical phenomena. In the present study we propose a novel metric based on the pattern recognition method Eigenfaces, coining the technique ‘Eigenparticles’. Using this technique we create a single statistical distribution of basis shapes to describe the morphological composition. The proposed technique is successfully validated with test shapes and applied to real particles. When compared with a state-of-the-art Fourier based method, ‘Eigenparticles’ performs favorably, clearly distinguishing the different particles.