Image processing for the experimental investigation of dense dispersed flows: Application to bubbly flows 机翻标题: 暂无翻译,请尝试点击翻译按钮。

来源
International Journal of Multiphase Flow
年/卷/期
2019 / 111 /
页码
16-30
ISSN号
0301-9322
作者单位
Univ Toulouse, CNRS Toulouse, IMFT, Toulouse, France;Univ Toulouse, CNRS Toulouse, IMFT, Toulouse, France;Univ Toulouse, LISBP, INSA, INRA,CNRS, Toulouse, France;Univ Toulouse, CNRS Toulouse, IMFT, Toulouse, France;Univ Toulouse, CNRS Toulouse, IMFT, Toulouse, France;Univ Toulouse, LISBP, INSA, INRA,CNRS, Toulouse, France;
作者
Villegas, L. Rueda;Colombet, D.;Guiraud, P.;Legendre, D.;Cazin, S.;Cockx, A.;
摘要
In this work an image processing technique is proposed to improve the measurement of ellipsoidal objects, 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. (C) 2018 Elsevier Ltd. All rights reserved.
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关键词/主题词
Dispersed flows;Image processing;Truncated bubbles;Overlapping bubbles;
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