TY - GEN
T1 - Machine vision for the quality assessment of emulsions in pharmaceutical processing
AU - Unnikrishnan, Saritha
AU - Donovan, John
AU - Macpherson, Russell
AU - Tormey, David
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Emulsion quality evaluation using machine vision techniques depends on the efficiency of the image segmentation algorithms. Two different machine vision techniques are investigated to determine their competency in detecting droplets from in-process microscopic images of a cream emulsion. Histogram-based segmentation shows promising potential compared to edge and symmetry detection. A statistical study of the droplet characteristics was conducted. The results demonstrate that the histogram-based approach is more proficient in the progressive analysis of droplet evolution during emulsification. A real-time integration of the technique is proposed, as a soft sensor, to predict the optimum process time and to increase manufacturing efficiency in chemical industries.
AB - Emulsion quality evaluation using machine vision techniques depends on the efficiency of the image segmentation algorithms. Two different machine vision techniques are investigated to determine their competency in detecting droplets from in-process microscopic images of a cream emulsion. Histogram-based segmentation shows promising potential compared to edge and symmetry detection. A statistical study of the droplet characteristics was conducted. The results demonstrate that the histogram-based approach is more proficient in the progressive analysis of droplet evolution during emulsification. A real-time integration of the technique is proposed, as a soft sensor, to predict the optimum process time and to increase manufacturing efficiency in chemical industries.
KW - automated image analysis
KW - droplet characteristics
KW - emulsion
KW - machine vision
KW - quality evaluation
KW - sustainable manufacturing
UR - http://www.scopus.com/inward/record.url?scp=85063126143&partnerID=8YFLogxK
U2 - 10.1109/UV.2018.8642158
DO - 10.1109/UV.2018.8642158
M3 - Conference contribution
AN - SCOPUS:85063126143
T3 - 4th IEEE International Conference on Universal Village 2018, UV 2018
BT - 4th IEEE International Conference on Universal Village 2018, UV 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Universal Village, UV 2018
Y2 - 21 October 2018 through 24 October 2018
ER -
