Image analysis framework with focus evaluation for in situ characterisation of particle size and shape attributes. (14th December 2018)
- Record Type:
- Journal Article
- Title:
- Image analysis framework with focus evaluation for in situ characterisation of particle size and shape attributes. (14th December 2018)
- Main Title:
- Image analysis framework with focus evaluation for in situ characterisation of particle size and shape attributes
- Authors:
- Cardona, Javier
Ferreira, Carla
McGinty, John
Hamilton, Andrew
Agimelen, Okpeafoh S.
Cleary, Alison
Atkinson, Robert
Michie, Craig
Marshall, Stephen
Chen, Yi-Chieh
Sefcik, Jan
Andonovic, Ivan
Tachtatzis, Christos - Abstract:
- Highlights: Image analysis framework for particle size and shape characterisation from in-line imaging sensors. Representative particle size and shape statistics by discarding partially out-of-focus objects. Evaluation of the image analysis framework against standard spherical and elongated particles. Abstract: Particle processing industries, such as pharmaceutical, food processing and consumer goods sectors, increasingly require strategies to control and engineer particle attributes. In both traditional batch and continuous processes, particle size and shape need to be effectively monitored through in-line measurements from Process Analytical Technologies. However, obtaining quantitative information from these measurements has proven to be challenging and in-line imaging techniques are primarily used for qualitative purposes. Two key challenges are: (1) the presence of out-of-focus objects and (2) images only represent 2D projections of three-dimensional objects. In this work, a novel framework to process frames from in-line imaging probes incorporates a focus evaluation step in order to extract meaningful quantitative shape and size information through rejection of out-of-focus particles. Furthermore, a model is proposed that simulates the 2D projection of three-dimensional particles onto the focal plane and computes the corresponding size and shape distributions. The framework is quantified and evaluated against standard particles of well-defined size and shape such asHighlights: Image analysis framework for particle size and shape characterisation from in-line imaging sensors. Representative particle size and shape statistics by discarding partially out-of-focus objects. Evaluation of the image analysis framework against standard spherical and elongated particles. Abstract: Particle processing industries, such as pharmaceutical, food processing and consumer goods sectors, increasingly require strategies to control and engineer particle attributes. In both traditional batch and continuous processes, particle size and shape need to be effectively monitored through in-line measurements from Process Analytical Technologies. However, obtaining quantitative information from these measurements has proven to be challenging and in-line imaging techniques are primarily used for qualitative purposes. Two key challenges are: (1) the presence of out-of-focus objects and (2) images only represent 2D projections of three-dimensional objects. In this work, a novel framework to process frames from in-line imaging probes incorporates a focus evaluation step in order to extract meaningful quantitative shape and size information through rejection of out-of-focus particles. Furthermore, a model is proposed that simulates the 2D projection of three-dimensional particles onto the focal plane and computes the corresponding size and shape distributions. The framework is quantified and evaluated against standard particles of well-defined size and shape such as polystyrene microspheres and needle-like cuboid silicon particles. … (more)
- Is Part Of:
- Chemical engineering science. Volume 191(2018)
- Journal:
- Chemical engineering science
- Issue:
- Volume 191(2018)
- Issue Display:
- Volume 191, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 191
- Issue:
- 2018
- Issue Sort Value:
- 2018-0191-2018-0000
- Page Start:
- 208
- Page End:
- 231
- Publication Date:
- 2018-12-14
- Subjects:
- Particle sizing -- In-line monitoring -- Particle attributes -- Size and shape distributions -- Imaging -- Forward model -- Focus
Chemical engineering -- Periodicals
Génie chimique -- Périodiques
Chemical engineering
Periodicals
Electronic journals
660 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00092509 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ces.2018.06.067 ↗
- Languages:
- English
- ISSNs:
- 0009-2509
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3146.000000
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British Library HMNTS - ELD Digital store - Ingest File:
- 11134.xml