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Development of Fast and Exact FFT Algorithm for Cross-Correlation PIV

상호상관 PIV기법을 위한 빠르고 정확한 FFT 알고리듬의 개발

  • Published : 2005.10.01

Abstract

Normalized cross-correlation (correlation coefficient) is a useful measure for pattern matching in PIV (Particle Image Velocimetry) analysis. Because it does not have a corresponding simple expression in frequency domain, several fast but inexact measures have been used. Among them, three measures of correlation for PIV analysis and the normalized cross-correlation were evaluated with a sample calculation. The test revealed that all other proposed correlation measures sometimes show inaccurate results, except the normalized cross-correlation. However, correlation coefficient method has a weakpoint that it requires so long time for calculation. To overcome this shortcoming, a fast and exact method for calculating normalized cross-correlation is suggested. It adopts Fast Fourier Transform (FFT) for calculation of covariance and the successive-summing method for the denominator of correlation coefficient. The new algorithm showed that it is really fast and exact in calculating correlation coefficient.

정규 상호 상관 (상관계수)은 입자영상유속계(PIV) 분석에서 형태 분석을 위한 가장 정확하고 적합한 척도이다. 그러나 상관계수는 주파수 영역에서 그에 상당하는 간단한 수식 표현이 없기 때문에, 빠르지만 부정확한 척도들이 종종 이용된다. 이러한 척도 중에서 선정된 세 가지 방법과 상관계수법을 상호 비교하였다. 그 결과 상관계수법을 제외한 나머지 척도들은 모두 종종 부정확한 결과를 도출함을 알 수 있었다. 그러나 상관계수법은 계산 시간이 많이 걸린다는 단점을 지니고 있다. 이 문제를 해결하기 위해, 상관계수법을 계산하는 빠르고 정확한 방법을 제시하였다. 이 방법은 상관계수의 분산을 계산하는 Fn 알고리듬과 분모를 계산하는 순차가감법을 결합한 것이다. 시험 결과 이 방법은 상관계수를 빠르고 정확하게 계산할 수 있음을 보였다.

Keywords

References

  1. Brigham, E. O. (1988). The fast Fourier transform and its applications, Prentice-Hall, Inc.
  2. Draper, N. R, and Smith, H. (1998). Applied regression analysis, John Wiley & Sons, Inc.
  3. Fincham, A. M., and Spedding, G. R. (1997). 'Low cost, high resolution DPIV for measurement of turbulent fluid flow.' Experiments in Fluids, 23, 449-462 https://doi.org/10.1007/s003480050135
  4. Gonzalez, R. C., and Woods, R. E. (1992). Digital image processing, Addison-Wesley Pub.
  5. Gui, L., and Merzkirch, W. (2000). 'A comparative study of the MQD method and several correlation-based PIV evaluation algorithms.' Experiments in Fluids, 28(1), 36-44 https://doi.org/10.1007/s003480050005
  6. Keane, R. D., and Adrian, R. J. (1992). 'Theory of cross-correlation analysis of PlV images.' Applied Scientific Research, 49, 191-215 https://doi.org/10.1007/BF00384623
  7. Lewis, J. P. (1995). 'Fast template matching.' Vision Interface, 120-123
  8. Pratt, W. K. (1991). Digital Image Processing, John Wiley & Sons, Inc.
  9. Raffel, M., Willert, C. E., and Kompenhans, J. (1998). Particle image velocimetry, a practical guide, Springer
  10. Ritter, G. X., and Wilson, J. N. (2000). Handbook of computer vision algorithms in image algebra, CRC Press
  11. Utami, T., Blackwelder, R. F., and Ueno, T. (1991), 'A cross-correlation technique for velocity field extraction from particulate visualization.' Experiments in Fluids, 10(4), 213-223 https://doi.org/10.1007/BF00190391
  12. Westerweel, J. (1993). Digital particle lmage velocimetry theory and application, Delft University Press
  13. Willert, C. E., and Gharib, M. (1991), 'Digital particle image velocimetry.' Experiments in Fluids, 10(4), 181-193 https://doi.org/10.1007/BF00190388

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