Computer vision for high-throughput analysis of pickering emulsions

Richards, Kieran; Comish, Ella; Evans, Rachel C

doi:10.1039/d4sm01252f

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Computer vision for high-throughput analysis of pickering emulsions

Kieran Richards, Ella Comish, Rachel C Evans

Soft Matter, Volume: 21, Issue: 12, Pages: 2339 - 2348

Swansea University Author: Kieran Richards

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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...

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Published in:	Soft Matter
ISSN:	1744-683X 1744-6848
Published:	Royal Society of Chemistry (RSC) 2025
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa68987

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last_indexed	2025-04-03T06:16:46Z
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spelling	2025-04-02T10:11:45.9180555 v2 68987 2025-02-28 Computer vision for high-throughput analysis of pickering emulsions fb57f5875df72bd56ff676a2b7bb007c Kieran Richards Kieran Richards true false 2025-02-28 EAAS 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. Journal Article Soft Matter 21 12 2339 2348 Royal Society of Chemistry (RSC) 1744-683X 1744-6848 28 3 2025 2025-03-28 10.1039/d4sm01252f COLLEGE NANME Engineering and Applied Sciences School COLLEGE CODE EAAS Swansea University Another institution paid the OA fee Engineering and Physical Sciences Research Council Grant: EP/R513180/1 2025-04-02T10:11:45.9180555 2025-02-28T09:41:29.2531251 Faculty of Science and Engineering School of Engineering and Applied Sciences - Chemistry Kieran Richards 1 Ella Comish 2 Rachel C Evans 0000-0003-2956-4857 3 68987__33704__5366e4238ce14d69ba63212d102a3ffd.pdf 68987.VOR.pdf 2025-02-28T09:46:27.9595109 Output 1773894 application/pdf Version of Record true © The Royal Society of Chemistry 2025. This Open Access Article is licensed under a Creative Commons Attribution 3.0 Unported Licence. true eng http://creativecommons.org/licenses/by/3.0/
title	Computer vision for high-throughput analysis of pickering emulsions
spellingShingle	Computer vision for high-throughput analysis of pickering emulsions Kieran Richards
title_short	Computer vision for high-throughput analysis of pickering emulsions
title_full	Computer vision for high-throughput analysis of pickering emulsions
title_fullStr	Computer vision for high-throughput analysis of pickering emulsions
title_full_unstemmed	Computer vision for high-throughput analysis of pickering emulsions
title_sort	Computer vision for high-throughput analysis of pickering emulsions
author_id_str_mv	fb57f5875df72bd56ff676a2b7bb007c
author_id_fullname_str_mv	fb57f5875df72bd56ff676a2b7bb007c_***_Kieran Richards
author	Kieran Richards
author2	Kieran Richards Ella Comish Rachel C Evans
format	Journal article
container_title	Soft Matter
container_volume	21
container_issue	12
container_start_page	2339
publishDate	2025
institution	Swansea University
issn	1744-683X 1744-6848
doi_str_mv	10.1039/d4sm01252f
publisher	Royal Society of Chemistry (RSC)
college_str	Faculty of Science and Engineering
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hierarchy_top_title	Faculty of Science and Engineering
hierarchy_parent_id	facultyofscienceandengineering
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department_str	School of Engineering and Applied Sciences - Chemistry{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Chemistry
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description	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.
published_date	2025-03-28T08:40:47Z
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Computer vision for high-throughput analysis of pickering emulsions

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