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Particle Image Velocimetry by Feature Tracking

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Computer Analysis of Images and Patterns (CAIP 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2124))

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Abstract

Particle Image Velocimetry (PIV) is a popular approach to flow visualisation in hydro- and aerodynamic studies and applications. The fluid is seeded with particles that follow the flow and make it visible. Traditionally, correlation techniques have been used to estimate the displacements of the particles in a digital PIV sequence. In this paper, two efficient feature tracking algorithms are customised and applied to PIV. The algorithmic solutions of the application are described. Techniques for coherence filtering and interpolation of a velocity field are developed. Experimental results are given, demonstrating that the tracking algorithms offer Particle Image Velocimetry a good alternative to the existing techniques.

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Author information

Authors and Affiliations

  1. Computer and Automation Research Institute, 1111, Budapest, Kende u.13-17, Hungary

    Dmitry Chetverikov

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  1. Dmitry Chetverikov
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Editor information

Editors and Affiliations

  1. Faculty of Electronics and Information Technology Institute of Radioelectronics, Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665, Warsaw, Poland

    Władysław Skarbek

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© 2001 Springer-Verlag Berlin Heidelberg

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Chetverikov, D. (2001). Particle Image Velocimetry by Feature Tracking. In: Skarbek, W. (eds) Computer Analysis of Images and Patterns. CAIP 2001. Lecture Notes in Computer Science, vol 2124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44692-3_40

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  • DOI: https://doi.org/10.1007/3-540-44692-3_40

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42513-7

  • Online ISBN: 978-3-540-44692-7

  • eBook Packages: Springer Book Archive

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