Bubble Trajectory Tracking Based on ORB Algorithm

Authors

  • Shujuan Wang College of Mathematical Sciences, Harbin Engineering University
  • Shichao Lu The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang, China
  • Jiaqi Liu College of Mathematical Sciences, Harbin Engineering University
  • Miao Wang College of Mathematical Sciences, Harbin Engineering University
  • Hongliang Luo College of Mathematical Sciences, Harbin Engineering University
  • Jihong Shen College of Mathematical Sciences, Harbin Engineering University
  • Shouxu Qiao College of Nuclear Science and Technology, Harbin Engineering University
  • Yuntao Dai College of Mathematical Sciences, Harbin Engineering University

DOI:

https://doi.org/10.5566/ias.2794

Keywords:

edge detection, feature matching, gas-liquid two-phase flow, tracking

Abstract

The system of gas-liquid two-phase bubbly flows is widely found in many industrial fields, such as nuclear energy, chemical, petroleum, and refrigeration. Bubbly two-phase flows measuring including detection and tracking affects the specific engineering problem solving to a great extent. The particle tracking velocity (PTV) algorithm is generally used for the tracking of the particles in the flow field. However, it does not take the shape change of particles into account in the process of flow. In this paper, a kind of bubble feature matching method based on ORB algorithm is proposed, and the edge detection method of findContours in OpenCV is used to extract the bubble contour in the image. The proposed algorithm implements the trajectory tracking of the bubbles with shape change when moving up in liquid. The feasibility of bubble trajectory tracking is shown by displaying of different bubble tracks in the plan, 3D plots and contour changing plots.

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Published

2023-04-18

How to Cite

Wang, S., Lu, S., Liu, J., Wang, M., Luo, H., Shen, J., … Dai, Y. (2023). Bubble Trajectory Tracking Based on ORB Algorithm. Image Analysis and Stereology, 42(1), 17–23. https://doi.org/10.5566/ias.2794

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Section

Original Research Paper