Journal article 41 views 7 downloads
Computer vision for high-throughput analysis of pickering emulsions
Kieran Richards,
Ella Comish,
Rachel C Evans 
Soft Matter
Swansea University Author: Kieran Richards
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© The Royal Society of Chemistry 2025. This Open Access Article is licensed under a Creative Commons Attribution 3.0 Unported Licence.
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DOI (Published version): 10.1039/d4sm01252f
Abstract
The quanitative analysis of solid-particle stabilized emulsions, known as Pickering emulsions, is crucial for their application in food, cosmetics, and pharmaceuticals. However, size analysis of these emulsion droplets, with diameters ranging from 5 to 500 μm, is challenging due to their non-uniform...
| Published in: | Soft Matter |
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| ISSN: | 1744-683X 1744-6848 |
| Published: |
Royal Society of Chemistry (RSC)
2025
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa68987 |
| Abstract: |
The quanitative analysis of solid-particle stabilized emulsions, known as Pickering emulsions, is crucial for their application in food, cosmetics, and pharmaceuticals. However, size analysis of these emulsion droplets, with diameters ranging from 5 to 500 μm, is challenging due to their non-uniform spatial and polydisperse size-distribution. Here, we investigate the application of the circle-Hough transform (CHT), a well-established computer-vision technique characterised by its ability to detect circular features in noisy images, for the seldom explored quantitative assessment of droplet size from optical microscopy images. This is particularly relevant to images where emulsions are captured in a single 2D focal plane. To implement the CHT with optical images, we have developed an open-source software application (“Hough-Scan”), which incorporates a user-friendly graphical interface for ease of use, and a tiling algorithm allowing localised regions of circles to be processed in parallel and improving computational efficiency. Using Hough-Scan, we demonstrate that the CHT has superior precision, recall and accuracy for the identification of Pickering emulsion droplets and determination of their size, compared to both manual identification and established computer vision methods. Our study demonstrates that CHT implementation using Hough-Scan can significantly increase the ease of image analysis for a diverse range of Pickering emulsion systems of varying spatial and size distribution, as well as visual artefacts common to example microscopy images. |
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| College: |
Faculty of Science and Engineering |
| Funders: |
Engineering and Physical Sciences Research Council Grant: EP/R513180/1 |