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

  • Obayashi I
  • Kimura M
N/ACitations
Citations of this article
7Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Obayashi, I., & Kimura, M. (2022). Persistent homology analysis with nonnegative matrix factorization for 3D voxel data of iron ore sinters. JSIAM Letters, 14(0), 151–154. https://doi.org/10.14495/jsiaml.14.151

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free