An Image-Processing Tool for Size and Shape Analysis of Manufactured Irregular Polyethylene Microparticles

Abstract

Microplastics (MPs) pose a significant risk to humans and animals due to their ability to absorb, adsorb, and desorb organic pollutants. MPs catchment from either sediments or water bodies is crucial for risk assessment, but fast and effective particle quantification of irregularly shaped particles is only marginally addressed. Many studies used microscopy methods to count MP particles, which are tedious for large sample sizes. Alternatively, this work presents an algorithm developed in the free software GNU Octave to analyze microscope images of MP particles with variable sizes and shapes. The algorithm can detect and distinguish different particles, compensate for uneven illumination and low image contrast, find high-contrast areas, unify edge regions, and fill the remaining pixels of stacked particles. The fully automatic algorithm calculates shape parameters such as convexity, solidity, reciprocal aspect ratio, rectangularity, and the Feret major axis ratio and generates the particle size distribution. The study tested low-density polyethylene particles with sizes of 50–100 µm and 200–300 µm. A scanning electron microscope image series analyzed with Octave was compared to a manual evaluation using ImageJ. Although the fully automatic algorithm did not identify all particles, the comprehensive tests demonstrate a qualitatively accurate particle size and shape monitoring applicable to any MPs, which processes larger data sets in a short time and is compatible with MATLAB-based codes.

Keywords

• microplastic
• quantification
• particle size distribution
• shape classification
• scanning electron microscopy
• GNU Octave