KIT | KIT-Bibliothek | Impressum | Datenschutz

High‐Throughput Object Recognition and Sizing in Disperse Systems

Völp, Annika Ricarda; Fessler, Felix; Reiner, Jasmin; Willenbacher, Norbert

Size and shape of dispersed objects defines properties of suspensions, emulsions, and foams, such as stability, texture, and flow. Accordingly, a rational product design requires reliable size distribution analysis. This is particularly challenging in dense foams. An endoscopic setup was optimized for bubble imaging minimizing light reflections, uneven illumination, and foam distortion. A software tool was developed detecting large quantities of foam bubbles at dispersed phase fractions up to 93 % from images with spatially varying contrast within minutes based on the template matching algorithm. Reliability of the method is also illustrated for a bimodal glass bead mixture, anisotropic nanocrystals, and emulsion droplets during freezing.

Open Access Logo

Verlagsausgabe §
DOI: 10.5445/IR/1000124648
Veröffentlicht am 14.10.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Bio- und Lebensmitteltechnik (BLT)
Institut für Mechanische Verfahrenstechnik und Mechanik (MVM)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 09.2020
Sprache Englisch
Identifikator ISSN: 0930-7516, 1521-4125
KITopen-ID: 1000124648
Erschienen in Chemical engineering & technology
Band 43
Heft 9
Seiten 1897–1902
Vorab online veröffentlicht am 07.07.2020
Nachgewiesen in Web of Science
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page