In a freeze drying process, the freezing step determines the pore size distribution within the product, which, in turn, affects the sublimation rate. Traditionally, pore analysis is carried out on SEM images by means of a manual, time-consuming approach. Here, an image segmentation technique was used to automatize this process and improve its reliability. A 3D structure of the cake was then reconstructed from the distribution of the super-pixels. We show that the approach herein proposed can remarkably improve prediction of the sublimation rate with respect to traditional methods.

Image segmentation and 3D reconstruction for improved prediction of the sublimation rate during freeze drying / Capozzi, L. C.; Arsiccio, A.; Sparavigna, A. C.; Pisano, R.; Barresi, A. A.. - STAMPA. - (2018), pp. 411-418. ((Intervento presentato al convegno IDS’2018 – 21st International Drying Symposium tenutosi a Valencia, Spain nel 11-14 September 2018 [http://dx.doi.org/10.4995/IDS2018.2018.8877].

Image segmentation and 3D reconstruction for improved prediction of the sublimation rate during freeze drying

Capozzi L. C.;Arsiccio A.;Sparavigna A. C.;Pisano R.;Barresi A. A.
2018

Abstract

In a freeze drying process, the freezing step determines the pore size distribution within the product, which, in turn, affects the sublimation rate. Traditionally, pore analysis is carried out on SEM images by means of a manual, time-consuming approach. Here, an image segmentation technique was used to automatize this process and improve its reliability. A 3D structure of the cake was then reconstructed from the distribution of the super-pixels. We show that the approach herein proposed can remarkably improve prediction of the sublimation rate with respect to traditional methods.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2718498
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