Measuring Agglomeration of Agglomerated Particles Pictures

TL;DR

This paper introduces a new geometrical index, δ_{agg}, derived from image processing, to quantify particle agglomeration in digital images, and demonstrates its effectiveness in correlating with a known agglomeration parameter.

Contribution

The paper presents a novel geometrical index δ_{agg} that accurately measures particle agglomeration from images, linking it to a Monte Carlo simulation parameter.

Findings

δ_{agg} correlates statistically with the agglomeration parameter γ_{agg}

The index effectively quantifies the degree of particle agglomeration

The method bridges image analysis with simulation parameters.

Abstract

In this article, we introduce a novel geometrical index $\delta_{agg}$, which is associated with the Euler number and is obtained by an image processing procedure for a given digital picture of aggregated particles such that $\delta_{agg}$ exhibits the degree of the agglomerations of the particles. In the previous work (Matsutani, Shimosako, Wang, Appl.Math.Modeling {\bf{37}} (2013), 4007-4022), we proposed an algorithm to construct a picture of agglomerated particles as a Monte-Carlo simulation whose agglomeration degree is controlled by $\gamma_{agg} \in (0,1)$. By applying the image processing procedure to the pictures of the agglomeration particles constructed following the algorithm, we show that $\delta_{agg}$ statistically reproduces the agglomeration parameter $\gamma_{agg}$.