Fourier-based Characterization of Roughness of Irregular Particles in SEM Images

Surface roughness plays a vital role in macro andmicro-scale granular behaviors. This paper presents a noveltechnique for the objective assessment of particle roughness. Thetechnique uses Fourier descriptors and image analysis ofscanning electron microscopy photographs. Low pass filtering ofFourier descriptors is used to produce several smooth versions ofthe shape boundary at different smoothing scales. To quantifyparticle irregularity and roughness, the perimeter of thesesmoothed boundaries compared with the perimeter of theoriginal particle boundary. The performance of the proposedcriterion evaluated on several random subsets of the particles inan SEM image dataset. These subsets ranked according to thecomputed roughness values, and the automatic rankingscompared to the manual rankings generated by a human expert.After rank-based analyzes of the proposed roughness metric, it isfound that the rankings generated by the proposed ۲D metric arewell correlated with manual rankings.

Keywords:

Roughness , image analysis , irregularity , morphology