Experiments in Fluids

, 40:764 | Cite as

Estimation of complex air–water interfaces from particle image velocimetry images

  • Shubhra K. Misra
  • M. Thomas
  • C. Kambhamettu
  • J. T. Kirby
  • F. Veron
  • M. Brocchini
Research Article


This paper describes a method for the estimation of the instantaneous air–water interface directly from particle image velocimetry (PIV) images of a laboratory generated air entraining turbulent hydraulic jump. Image processing methods such as texture segmentation based on gray level co-occurrence matrices are used to obtain a first approximation for the discrete location of the free surface. Active contours based on energy minimization principles are then implemented to get a more accurate estimate of the calculated interface and draw it closer to the real surface. Results are presented for two sets of images with varying degrees of image information and surface deformation. Comparisons with visually-interpreted surfaces show good agreement. In the absence of in-situ measurements, several verification tests based on physical reasoning show that the free surface is calculated to acceptable levels of accuracy. Aside from a single image used to tune the set of parameters, the algorithm is completely automated to process an ensemble of images representative of typical PIV applications. The method is computationally efficient and can be used to track fluid-interfaces undergoing non-rigid deformations.


Particle Image Velocimetry Active Contour Laser Induce Fluorescence Texture Class Laser Light Sheet 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the National Oceanographic Partnership Program (NOPP), grant N00014-99-1-1051.


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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Shubhra K. Misra
    • 1
  • M. Thomas
    • 2
  • C. Kambhamettu
    • 2
  • J. T. Kirby
    • 1
  • F. Veron
    • 3
  • M. Brocchini
    • 4
  1. 1.Center for Applied Coastal ResearchUniversity of DelawareNewarkUSA
  2. 2.Video/Image Modeling and Synthesis Lab., Department of Computer and Information SciencesUniversity of DelawareNewarkUSA
  3. 3.Graduate College of Marine StudiesUniversity of DelawareNewarkUSA
  4. 4.D.I.A.M, Universita’ di GenovaGenovaItaly

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