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Data Analysis

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Springer Handbook of Experimental Fluid Mechanics

Part of the book series: Springer Handbooks ((SHB))

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Abstract

From the beginning of science, visual observation has played a major role. At that time, the only way to document the results of an experiment was by verbal description and manual drawings. The next major step was the invention of photography more than one and a half centuries ago, which enabled experimental results to be documented objectively. In experimental fluid mechanics, flow visualization techniques gave direct insight into complex flows, but it was very difficult and time consuming to extract quantitative measurements from photographs and films.

Nowadays, we are in the middle of a second revolution sparked by the rapid progress in both photonics and computer technology. Sensitive solid-state cameras are available that acquire digital image data, and standard personal computers and workstations have become powerful enough to process these data. These technologies are now available to any scientist or engineer. As a consequence, image processing has expanded and continues to expand rapidly from a few specialized applications into a standard scientific tool.

This chapter gives a brief presentation of some of the most important general image processing techniques that are required to process image data in experimental fluid mechanics. The second section (Sect. 25.2) deals with motion analysis. The most important methods are introduced and classified according to the fundamental principles, assumptions and approximations upon which they are based.

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Abbreviations

3-D:

three-dimensional

AGW:

adaptive Gaussian windowing

BCCE:

brightness change constraint equation

CCD:

charge-coupled device

CMOS:

complementary metal oxide semiconductor

EBCCE:

extended brightness change constraint equation

FFT:

fast Fourier transform

GBCCE:

generalized brightness change constraint equation

MHT:

multiple hypothesis tracker

PIV:

particle image velocimetry

PSF:

point spread function

PTV:

particle tracking velocimetry

SSD:

sum-of-squared differences

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Authors and Affiliations

  1. Research Group Image Processing, Interdisciplinary Center for Scientific Computing, University of Heidelberg, Im Neuenheimer Feld 368, 69120, Heidelberg, Germany

    Bernd Jähne Prof.

  2. Research Group Image Processing, Interdisciplinary Center for Scientific Computing, University of Heidelberg, Im Neuenheimer Feld 368, 69120, Heidelberg, Germany

    Michael Klar Ph.D

  3. Research Group Image Processing, Interdisciplinary Center for Scientific Computing, University of Heidelberg, Im Neuenheimer Feld 368, 69120, Heidelberg, Germany

    Markus Jehle Dr.

Authors
  1. Bernd Jähne Prof.
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  2. Michael Klar Ph.D
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  3. Markus Jehle Dr.
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Corresponding authors

Correspondence to Bernd Jähne Prof. , Michael Klar Ph.D or Markus Jehle Dr. .

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Editors and Affiliations

  1. Fachgebiet Strömungslehre und Aerodynamik, Technische Universität Darmstadt, Petersenstraße 30, 64287, Darmstadt, Germany

    Cameron Tropea Dr.

  2. Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, 842 W. Taylor St., 60607-7022, Chicago, IL, USA

    Alexander L. Yarin Dr.

  3. Mechanical Engineering, Michigan State University, A118 Engineering Research Complex, 48824-1326, East Lansing, MI, USA

    John F. Foss Dr.

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Jähne, B., Klar, M., Jehle, M. (2007). Data Analysis. In: Tropea, C., Yarin, A.L., Foss, J.F. (eds) Springer Handbook of Experimental Fluid Mechanics. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30299-5_25

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