Automated Dynamic Image Analysis for Particle Size and Shape Classification in Three Dimensions

TL;DR

OCULAR is a cost-effective hardware and software system for 3D dynamic particle analysis, overcoming limitations of 2D imaging and static 3D methods, enabling accurate, real-time particle size and shape classification.

Contribution

The paper introduces OCULAR, a novel synchronized camera array system for dynamic 3D particle imaging and shape analysis, improving accuracy and efficiency over existing static and 2D methods.

Findings

OCULAR provides reproducible 3D particle shape data.

It compares favorably with X-ray micro CT in accuracy.

The system is cost-effective and suitable for continuous particle streams.

Abstract

We introduce OCULAR, an innovative hardware and software solution for three-dimensional dynamic image analysis of fine particles. Current state-of-the art instruments for dynamic image analysis are largely limited to two-dimensional imaging. However, extensive literature has demonstrated that relying on a single two-dimensional projection for particle characterisation can lead to inaccuracies in many applications. Existing three-dimensional imaging technologies, such as computed tomography, laser scanning, and orthophotography, are limited to static objects. These methods are often not statistically representative and come with significant post-processing requirements, as well as the need for specialised imaging and computing resources. OCULAR addresses these challenges by providing a cost-effective solution for imaging continuous particle streams using a synchronised array of optical cameras. Particle shape characterisation is achieved through the reconstruction of their three-dimensional surfaces. This paper details the OCULAR methodology, evaluates its reproducibility, and compares its results against X-ray micro computed tomography, highlighting its potential for efficient and reliable particle analysis.