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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 37, Iss. 17 — Jun. 10, 1998
  • pp: 3656–3663

Neural-network method applied to the stereo image correspondence problem in three-component particle image velocimetry

Ian Grant, X. Pan, F. Romano, and X. Wang  »View Author Affiliations


Applied Optics, Vol. 37, Issue 17, pp. 3656-3663 (1998)
http://dx.doi.org/10.1364/AO.37.003656


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Abstract

The successful application of a recurrent neural network of the Hopfield type to the solution of the stereo image-pair reconciliation problem in stereoscopic particle image velocimetry (PIV) in the tracking mode is described. The results of applying the network to both virtual-flow and physical-flow PIV data sets are presented, and the usefulness of this novel approach to PIV stereo image analysis is demonstrated. A partner-particle image-pair density (PPID) parameter is defined as the average number of potential particle image-pair candidates in the search window in the second view corresponding to a single image pair in the first view. A quantitative assessment of the performance of the method is then made from groups of 100 synthetic flow images at various values of the PPID. The successful pairing of complementary image points is shown to vary from 100% at a PPID of 1 and to remain greater than 97% successful for PPID’s up to 5. The application of the method to a hydraulic flow is also described, with in-line stereo images presented, and the application of the neural-matching method is demonstrated for a typical data set.

© 1998 Optical Society of America

OCIS Codes
(100.2960) Image processing : Image analysis
(100.6890) Image processing : Three-dimensional image processing
(150.4620) Machine vision : Optical flow
(280.2490) Remote sensing and sensors : Flow diagnostics
(280.7250) Remote sensing and sensors : Velocimetry

Citation
Ian Grant, X. Pan, F. Romano, and X. Wang, "Neural-Network Method Applied to the Stereo Image Correspondence Problem in Three-Component Particle Image Velocimetry," Appl. Opt. 37, 3656-3663 (1998)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-37-17-3656


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References

  1. I. Grant, Selected Papers on PIV, Vol. MS99 of the SPIE Milestone Series (SPIE Press, Bellingham, Wash., 1994).
  2. I. Grant, “Particle image velocimetry: a review,” Proc. Inst. Mechan. Eng. Part C 211, 55–76 (1997). [CrossRef]
  3. I. Grant and A. Liu, “Method for the efficient incoherent analysis of particle image velocimetry images” (reprinted in Ref. 1), Appl. Opt. 28, 1745–1748 (1989).
  4. I. Grant and X. Pan, “An investigation of the performance of multi layer neural networks applied to the analysis of PIV images,” Exp. Fluids 19, 159–166 (1995). [CrossRef]
  5. I. Grant and X. Pan, “The use of neural techniques in PIV and PTV,” Meas. Sci. Technol. 8, 1399–1405 (1997). [CrossRef]
  6. I. Grant, Y. Zhao, Y. Tan, and J. N. Stewart, “Three component flow mapping: experiences in stereoscopic PIV and holographic velocimetry,” in Proceedings of the Fourth International Conference on Laser Anemometry, Advances and Applications (reprinted in Ref. 1) (American Society of Mechanical Engineers, New York, 1991), pp. 368–371.
  7. K. D. Hinsch, “Three-dimensional particle image velocimetry,” Meas. Sci. Technol. 6, 742–753 (1995). [CrossRef]
  8. I. Grant, S. Fu, X. Pan, and X. Wang, “The application of an in-line, stereoscopic, PIV system to 3-component velocity measurement,” Exp. Fluids 19, 214–222 (1995). [CrossRef]
  9. X. Pan, “Advanced technology applied to PIV measurement,” Ph.D. dissertation (Heriot-Watt University, Edinburgh, Scotland, 1996).
  10. R. Y. Tsai, “A versatile camera calibration technique for high accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses,” IEEE J. Robotics Automat. 3, 323–344 (1987). [CrossRef]
  11. N. M. Nasrabadi and Y. C. Chang, “Hopfield network for stereo vision correspondence,” IEEE Trans. Neural Networks 3, 5–13 (1992). [CrossRef]
  12. I. Grant, X. Pan, X. Wang, and J. N. Stewart, “Correction for viewing angle applied to PIV data obtained in aerodynamic blade vortex interaction studies,” Exp. Fluids 17, 95–99 (1994).

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