Analysis of Granules and Pellets

Volume rendering of gravel
© Photo ITWM

Volume rendering of separate pieces of gravel. The false coloring demonstrates the segmentation of individual grains. μ-CT ProCon XRay.

MAVI comes with a set of algorithms enabling the segmentation of three dimensional image data of powders and particles. Common questions e.g. regarding the shape or size distributions of these objects can be addressed. Length, width, and height of complex shaped particles can be derived robustly from the edge lengths of the minimal bounding cuboid.

In the ZIM project "Development of innovative high performance grout based on the criteria of grain shape through new 3D image data measuring and analyzing techniques" the Fraunhofer ITWM develops algorithms for a robust and as far as possible automatic extraction of the compound's important parameters from 3D image data.

Partikelkenngrößen in 3D: Maximaler Feret Durchmesser.
© Photo ITWM

Characterization of particles in 3D: Maximum Feret diameter.

Partikelkenngrößen in 3D: Maximale Elongation.
© Photo ITWM

Partikelkenngrößen in 3D: Maximale Elongation.

Characterization of particles with the maximal local thickness.
© Photo ITWM

Partikelkenngrößen in 3D: Maximale lokale Dicke.


  • Vecchio, I.; Schladitz, K.; Godehardt, M.; Heneka, M.:
    3D Geometric Characterization of Particles Applied to Technical Cleanliness.
    Image Analysis & Stereology, Volume 31, n.3, pp.163-174, (2012).

  • O. Weber, A. Rack, C. Redenbach, M. Schulz, O. Wirjadi:
    Micropowder Injection Molding: Investigation of Powder-Binder Separation Using Synchrotron-Based Microtomography and 3D Image Analysis.
    J. Materials Science, 46 (10), pp. 3568-3573, (2011).