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Automated dynamic image analysis for particle size and shape classification in three dimensions

Lookup NU author(s): Dr Sadegh NadimiORCiD, Vasileios AngelidakisORCiD, Dr Sadaf MaramizonouzORCiD, Dr Chao Zhang

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).


Abstract

We introduce OCULAR, an innovative hardware and software solution for three-dimensional dynamic image analysis of micron-sized 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 repeatability, and compares its results against X-ray micro-computed tomography, highlighting its potential for efficient and reliable particle analysis.


Publication metadata

Author(s): Nadimi S, Angelidakis V, Maramizonouz S, Zhang C

Publication type: Article

Publication status: Published

Journal: Powder Technology

Year: 2025

Volume: 458

Pages: 120973

Print publication date: 31/05/2025

Online publication date: 27/03/2025

Acceptance date: 25/03/2025

Date deposited: 14/07/2025

ISSN (print): 0032-5910

ISSN (electronic): 1873-328X

Publisher: Elsevier

URL: https://doi.org/10.1016/j.powtec.2025.120973

DOI: 10.1016/j.powtec.2025.120973

Data Access Statement: Data will be made available on request.


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Funding

Funder referenceFunder name
EP/R511584/1EPSRC

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