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On errors of digital particle image velocimetry

Huang, H. and Dabiri, D. and Gharib, M. (1997) On errors of digital particle image velocimetry. Measurement Science and Technology, 8 (12). pp. 1427-1440. ISSN 0957-0233. doi:10.1088/0957-0233/8/12/007.

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The goal of the present study is to quantify and reduce, when possible, errors in two-dimensional digital particle image velocimetry (DPIV). Two major errors, namely the mean bias and root-mean-square (RMS) errors, have been studied. One fundamental source of these errors arises from the implementation of cross correlation (CC). Other major sources of these errors arise from the peak-finding scheme, which locates the correlation peak with a sub-pixel accuracy, and noise within the particle images. Two processing techniques are used to extract the particle displacements. First, a CC method utilizing the FFT algorithm for fast processing is implemented. Second, a particle image pattern matching (PIPM) technique, usually requiring a direct computation and therefore more time consuming, is used. Using DPIV on simulated images, both the mean-bias and RMS errors have been found to be of the order of 0.1 pixels for CC. The errors of PIPM are about an order of magnitude less than those of CC. In the present paper the authors introduce a peak-normalization method which reduces the error level of CC to that of PIPM without adding much computational effort. A peak-compensation technique is also introduced to make the mean-bias error negligible in comparison with the RMS error. Noise in an image suppresses the mean-bias error but, on the other hand, significantly amplifies the RMS error. A digital video signal usually has a lower noise level than that of an analogue one and therefore provides a smaller error in DPIV.

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Additional Information:Copyright © Institute of Physics and IOP Publishing Limited 1997. Received 12 June 1997, accepted for publication 24 September 1997. Print publication: Issue 12 (December 1997). This work was sponsored by an URI grant from the Office of Naval Research, USA (grant number N00014-92-J-1618).
Issue or Number:12
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:8908
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Deposited On:25 Sep 2007
Last Modified:08 Nov 2021 20:54

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