Characterization of nanostructured material images using fractal descriptors

TL;DR

This paper introduces a fractal descriptor-based methodology for analyzing and characterizing the complex surface morphology of nanostructured materials in SEM images, demonstrating its effectiveness on titanium oxide samples.

Contribution

It presents a novel application of volumetric fractal descriptors based on Bouligand-Minkowski dimension for nanostructure image analysis.

Findings

Successfully characterized titanium oxide nanostructures

Demonstrated sensitivity to morphological variations

Validated approach with experimental SEM data

Abstract

This work presents a methodology to the morphology analysis and characterization of nanostructured material images acquired from FEG-SEM (Field Emission Gun-Scanning Electron Microscopy) technique. The metrics were extracted from the image texture (mathematical surface) by the volumetric fractal descriptors, a methodology based on the Bouligand-Minkowski fractal dimension, which considers the properties of the Minkowski dilation of the surface points. An experiment with galvanostatic anodic titanium oxide samples prepared in oxalyc acid solution using different conditions of applied current, oxalyc acid concentration and solution temperature was performed. The results demonstrate that the approach is capable of characterizing complex morphology characteristics such as those present in the anodic titanium oxide.