Image analysis framework with focus evaluation for in situ characterisation of particle size and shape attributes

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  • 3 Citations

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.
LanguageEnglish
Pages208-231
Number of pages24
JournalChemical Engineering Science
Volume191
Early online date25 Jun 2018
DOIs
Publication statusPublished - 14 Dec 2018

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image analysis
Image analysis
Particle size
evaluation
Imaging techniques
Food processing
Polystyrenes
Silicon
Microspheres
Needles
Drug products
Engineers
projection
food processing
Processing
Pharmaceutical Preparations
Industry
imaging techniques
needles
rejection

Keywords

  • particle sizing
  • in-line monitoring
  • particle attributes
  • size and shape distributions
  • imaging
  • forward model

Cite this

@article{67b434ad7895453aa877fc97773e36d8,
title = "Image analysis framework with focus evaluation for in situ characterisation of particle size and shape attributes",
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.",
keywords = "particle sizing, in-line monitoring, particle attributes, size and shape distributions, imaging, forward model",
author = "Javier Cardona and Carla Ferreira and John McGinty and Andrew Hamilton and Agimelen, {Okpeafoh S.} and Alison Cleary and Robert Atkinson and Craig Michie and Stephen Marshall and Yi-Chieh Chen and Jan Sefcik and Ivan Andonovic and Christos Tachtatzis",
year = "2018",
month = "12",
day = "14",
doi = "10.1016/j.ces.2018.06.067",
language = "English",
volume = "191",
pages = "208--231",
journal = "Chemical Engineering Science",
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T1 - Image analysis framework with focus evaluation for in situ characterisation of particle size and shape attributes

AU - Cardona, Javier

AU - Ferreira, Carla

AU - McGinty, John

AU - Hamilton, Andrew

AU - Agimelen, Okpeafoh S.

AU - Cleary, Alison

AU - Atkinson, Robert

AU - Michie, Craig

AU - Marshall, Stephen

AU - Chen, Yi-Chieh

AU - Sefcik, Jan

AU - Andonovic, Ivan

AU - Tachtatzis, Christos

PY - 2018/12/14

Y1 - 2018/12/14

N2 - 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.

AB - 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.

KW - particle sizing

KW - in-line monitoring

KW - particle attributes

KW - size and shape distributions

KW - imaging

KW - forward model

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