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The Image Processing of Droplet for Evaporation Experiment in SJ-10

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Abstract

We have completed an experiment for droplet evaporation processing using Young-Laplace fitting, exponent fitting, polynomial fitting and ellipse fitting, which could be used for multiple shapes of droplets. The droplet evaporation experiment test was an important science experiment in SJ-10. In order to get the change process of the physical parameter, such as the touching edges and the droplet evaporation rate, we had gained the contour edge image of the droplet and used mathematic method to do the fitting analysis. The accuracy of the physical parameter was depended on the accuracy of the mathematic fitting. Using the original Young-Laplace fitting method could not process all the images of evaporation and liquid interface from the space experiment facility of SJ-10, especially the smaller droplet images. We could get more accurate contour fitting and result using the new method described in this article. This article proposes a complete solution, including edge detecting and contour fitting. In edge detecting, Canny detector was applied to extract droplet edge. In contour fitting, Young-Laplace fitting, exponent fitting, polynomial fitting and ellipse fitting are designed to fit the contour of droplets, which make the solution apply to all of droplets in SJ-10.

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Authors and Affiliations

  1. Center for Quantum Technology Research, School of Physics, Beijing Institute of Technology, Beijing, 100081, China

    Changbin Xue

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Yanhui Feng

  3. Key Laboratory of Electronics and Information Technology for Space Systems, National Space Science Center, Chinese Academy of Sciences, Beijing, 100190, China

    Qiang Yu

Authors
  1. Changbin Xue
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  2. Yanhui Feng
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  3. Qiang Yu
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Correspondence to Qiang Yu.

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Xue, C., Feng, Y. & Yu, Q. The Image Processing of Droplet for Evaporation Experiment in SJ-10. Microgravity Sci. Technol. 29, 221–228 (2017). https://doi.org/10.1007/s12217-017-9541-1

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  • DOI: https://doi.org/10.1007/s12217-017-9541-1

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