Image processing for the experimental investigation of dense dispersed flows: application to bubbly flows

Lucia Rueda Villegas (1, 2, 3) , Damien Colombet (1, 2, 3) , Pascal Guiraud (1, 2) , Dominique Legendre (1, 3) , Sébastien Cazin (1, 3) , Arnaud Cockx (1, 2)

1 FERMAT - Fédération de Recherche Fluides, Energie, Réacteurs, Matériaux et Transferts
2 LISBP - Laboratoire d'Ingénierie des Systèmes Biologiques et des Procédés
3 IMFT - Institut de mécanique des fluides de Toulouse

In this work an image processing technique is proposed to improve the measurement of ellipsoidal ob- jects, such as bubbles in dispersed flows. This novel algorithm devoted to the measurement of bubble size, shape and trajectory is applied to binarised images from a gray-level gradient filter. To improve data statistics, an ellipse fitting method is employed to take into account truncated bubbles at the image edges. Then, an original approach is proposed to enable the segmentation of overlapping bubbles. The complete algorithm is evaluated on synthetic images and on real images for an air-bubble swarm within water. This new and robust methodology enables to increase substantially (more than 40%) the number of bubbles detected and thus to improve data convergence.

Mots clés: Image processing; Dispersed flows; Truncated bubbles; Overlapping bubbles

Domaines: Mécanique des fluides [physics.class-ph]

Lucia Rueda Villegas, Damien Colombet, Pascal Guiraud, Dominique Legendre, Sébastien Cazin, et al.. Image processing for the experimental investigation of dense dispersed flows: application to bubbly flows. International Journal of Multiphase Flow, 2019, 111, pp.16-30. ⟨10.1016/j.ijmultiphaseflow.2018.10.017⟩. ⟨hal-02139287⟩