Persistent homology analysis with nonnegative matrix factorization for 3D voxel data of iron ore sinters

TL;DR

This paper introduces a novel method combining persistent homology and nonnegative matrix factorization to analyze 3D voxel data of iron ore sinters, effectively capturing complex structural coexistences.

Contribution

The paper presents a new approach that integrates persistent homology with nonnegative matrix factorization for detailed structural analysis of 3D voxel data.

Findings

Successfully captures coexistence structures in iron ore sinters

Demonstrates effectiveness of the method on X-ray CT data

Provides a new tool for analyzing complex 3D material structures

Abstract

This paper proposes a data analysis method using persistent homology and nonnegative matrix factorization. A concatenated persistence image technique is used to extract coexisting structures from the persistence diagrams of different dimensions hidden behind the data. To demonstrate the potential of our method, we apply the method to 3D voxel data of iron ore sinters obtained by X-ray computed tomography. The analysis successfully captures the coexistence structures in these iron ore sinters.