Abstract

Interferometric data, either from single-frame fringe-tracking and Fourier-transform techniques or from multiframe phase-shifting techniques, pose a problem of 2π ambiguity, that is, wrapped-phase information. As the degree of noise level increases, especially in high-speed aerodynamics, these techniques encounter difficulties in phase extraction to provide continuous unwrapped-phase information. Here, a new hybrid approach, called the integrated expert system, which is developed primarily for aerodynamic interferogram evaluation, is presented. The integrated expert system utilizes interferometric-specific knowledge rules to compensate for the limitations associated with conventional techniques. It integrates in a single structure an expert system and algorithmic programming to provide, as much as possible, a unified approach for all the interferogram evaluation techniques. This initial attempt may provide a useful groundwork for future development in intelligent interferogram processing.

© 1995 Optical Society of America

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. C. M. Vest, Holographic Interferometry (Wiley, New York, 1979).
  2. R. J. Pryputniewicz, K. A. Stetson, “Measurement of vibration patterns using electro-optic holography,” in Proceedings of Laser Interferometry: Quantitative Analysis of Interferograms, R. J. Pryputniewicz, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 1162, 456–467 (1989).
  3. F. Becker, Y. H. Yu, “Digital fringe reduction techniques applied to the measurement of three-dimensional transonic flow fields,” Opt. Eng. 24, 429–434 (1985).
  4. A. Choudry, “Automated fringe reduction techniques,” in Proceedings of Interferometric Metrology, N. A. Massie, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 816, p. 49–55 (1987).
  5. D. W. Robinson, G. T. Reid, Interferogram Analysis: Digital Fringe Pattern Measurement Techniques (Institute of Physics, Philadelphia, 1993).
  6. N. Nandhakumar, J. K. Affarwal, “The artificial intelligence approach to pattern recognition: a prospective and an overview,” Patt. Recog. 18, 383–389 (1985).
    [CrossRef]
  7. M. D. Levine, S. I. Shaheen, “A modular computer vision for picture segmentation and interpretation,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-3, 540–556 (1981).
    [CrossRef]
  8. G. T. Reid, “Automatic fringe pattern analysis: a review,” Opt. Lasers Eng. 7, 37–68 (1987).
    [CrossRef]
  9. T. M. Kreis, “Computer aided evaluation of fringe patterns,” Opt. Lasers Eng. 19, 221–240 (1993).
    [CrossRef]
  10. J. Slepica, S. S. Cha, “Stabilization of ill-posed nonlinear regression method and its application to interferogram reduction,” in Second International Conference on Photomechanics and Speckle Metrology: Moire Techniques, Holographic Interferometry, Optical NDT, and Applications to Fluid Mechanics, F.-P. Chiang, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 1554B, 574–579 (1991).
  11. J. J. Gierloff, “Phase unwrapping by regions,” in Current Developments in Optical Engineering II, R. E. Fisher, W. J. Smith, eds., Proc. Soc. Photo-Opt. Instrum. Eng. 818, 2–9 (1987).
  12. J. Giarratano, G. Riley, Expert System: Principle and Programming (PWS-Kent, Boston, 1989).
  13. E. Yu, S. S. Cha, W. Joo, “Use of interferometric directionality for noise reduction,” Opt. Eng. 34, 173–182 (1995).
    [CrossRef]
  14. M. E. Denofsky, “How near is near?” MIT-AI Demo-334 (Artificial Intelligence Laboratory, MIT, Cambridge, Mass., 1976).
  15. J. Schorner, A. Ettemeye, U. Neupert, H. Rottenko, C. Winter, “New approaches interpreting holographic images,” Opt. Lasers Eng. 14, 283–291 (1991).
    [CrossRef]

1995 (1)

E. Yu, S. S. Cha, W. Joo, “Use of interferometric directionality for noise reduction,” Opt. Eng. 34, 173–182 (1995).
[CrossRef]

1993 (1)

T. M. Kreis, “Computer aided evaluation of fringe patterns,” Opt. Lasers Eng. 19, 221–240 (1993).
[CrossRef]

1991 (1)

J. Schorner, A. Ettemeye, U. Neupert, H. Rottenko, C. Winter, “New approaches interpreting holographic images,” Opt. Lasers Eng. 14, 283–291 (1991).
[CrossRef]

1987 (1)

G. T. Reid, “Automatic fringe pattern analysis: a review,” Opt. Lasers Eng. 7, 37–68 (1987).
[CrossRef]

1985 (2)

F. Becker, Y. H. Yu, “Digital fringe reduction techniques applied to the measurement of three-dimensional transonic flow fields,” Opt. Eng. 24, 429–434 (1985).

N. Nandhakumar, J. K. Affarwal, “The artificial intelligence approach to pattern recognition: a prospective and an overview,” Patt. Recog. 18, 383–389 (1985).
[CrossRef]

1981 (1)

M. D. Levine, S. I. Shaheen, “A modular computer vision for picture segmentation and interpretation,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-3, 540–556 (1981).
[CrossRef]

Affarwal, J. K.

N. Nandhakumar, J. K. Affarwal, “The artificial intelligence approach to pattern recognition: a prospective and an overview,” Patt. Recog. 18, 383–389 (1985).
[CrossRef]

Becker, F.

F. Becker, Y. H. Yu, “Digital fringe reduction techniques applied to the measurement of three-dimensional transonic flow fields,” Opt. Eng. 24, 429–434 (1985).

Cha, S. S.

E. Yu, S. S. Cha, W. Joo, “Use of interferometric directionality for noise reduction,” Opt. Eng. 34, 173–182 (1995).
[CrossRef]

J. Slepica, S. S. Cha, “Stabilization of ill-posed nonlinear regression method and its application to interferogram reduction,” in Second International Conference on Photomechanics and Speckle Metrology: Moire Techniques, Holographic Interferometry, Optical NDT, and Applications to Fluid Mechanics, F.-P. Chiang, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 1554B, 574–579 (1991).

Choudry, A.

A. Choudry, “Automated fringe reduction techniques,” in Proceedings of Interferometric Metrology, N. A. Massie, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 816, p. 49–55 (1987).

Denofsky, M. E.

M. E. Denofsky, “How near is near?” MIT-AI Demo-334 (Artificial Intelligence Laboratory, MIT, Cambridge, Mass., 1976).

Ettemeye, A.

J. Schorner, A. Ettemeye, U. Neupert, H. Rottenko, C. Winter, “New approaches interpreting holographic images,” Opt. Lasers Eng. 14, 283–291 (1991).
[CrossRef]

Giarratano, J.

J. Giarratano, G. Riley, Expert System: Principle and Programming (PWS-Kent, Boston, 1989).

Gierloff, J. J.

J. J. Gierloff, “Phase unwrapping by regions,” in Current Developments in Optical Engineering II, R. E. Fisher, W. J. Smith, eds., Proc. Soc. Photo-Opt. Instrum. Eng. 818, 2–9 (1987).

Joo, W.

E. Yu, S. S. Cha, W. Joo, “Use of interferometric directionality for noise reduction,” Opt. Eng. 34, 173–182 (1995).
[CrossRef]

Kreis, T. M.

T. M. Kreis, “Computer aided evaluation of fringe patterns,” Opt. Lasers Eng. 19, 221–240 (1993).
[CrossRef]

Levine, M. D.

M. D. Levine, S. I. Shaheen, “A modular computer vision for picture segmentation and interpretation,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-3, 540–556 (1981).
[CrossRef]

Nandhakumar, N.

N. Nandhakumar, J. K. Affarwal, “The artificial intelligence approach to pattern recognition: a prospective and an overview,” Patt. Recog. 18, 383–389 (1985).
[CrossRef]

Neupert, U.

J. Schorner, A. Ettemeye, U. Neupert, H. Rottenko, C. Winter, “New approaches interpreting holographic images,” Opt. Lasers Eng. 14, 283–291 (1991).
[CrossRef]

Pryputniewicz, R. J.

R. J. Pryputniewicz, K. A. Stetson, “Measurement of vibration patterns using electro-optic holography,” in Proceedings of Laser Interferometry: Quantitative Analysis of Interferograms, R. J. Pryputniewicz, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 1162, 456–467 (1989).

Reid, G. T.

G. T. Reid, “Automatic fringe pattern analysis: a review,” Opt. Lasers Eng. 7, 37–68 (1987).
[CrossRef]

D. W. Robinson, G. T. Reid, Interferogram Analysis: Digital Fringe Pattern Measurement Techniques (Institute of Physics, Philadelphia, 1993).

Riley, G.

J. Giarratano, G. Riley, Expert System: Principle and Programming (PWS-Kent, Boston, 1989).

Robinson, D. W.

D. W. Robinson, G. T. Reid, Interferogram Analysis: Digital Fringe Pattern Measurement Techniques (Institute of Physics, Philadelphia, 1993).

Rottenko, H.

J. Schorner, A. Ettemeye, U. Neupert, H. Rottenko, C. Winter, “New approaches interpreting holographic images,” Opt. Lasers Eng. 14, 283–291 (1991).
[CrossRef]

Schorner, J.

J. Schorner, A. Ettemeye, U. Neupert, H. Rottenko, C. Winter, “New approaches interpreting holographic images,” Opt. Lasers Eng. 14, 283–291 (1991).
[CrossRef]

Shaheen, S. I.

M. D. Levine, S. I. Shaheen, “A modular computer vision for picture segmentation and interpretation,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-3, 540–556 (1981).
[CrossRef]

Slepica, J.

J. Slepica, S. S. Cha, “Stabilization of ill-posed nonlinear regression method and its application to interferogram reduction,” in Second International Conference on Photomechanics and Speckle Metrology: Moire Techniques, Holographic Interferometry, Optical NDT, and Applications to Fluid Mechanics, F.-P. Chiang, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 1554B, 574–579 (1991).

Stetson, K. A.

R. J. Pryputniewicz, K. A. Stetson, “Measurement of vibration patterns using electro-optic holography,” in Proceedings of Laser Interferometry: Quantitative Analysis of Interferograms, R. J. Pryputniewicz, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 1162, 456–467 (1989).

Vest, C. M.

C. M. Vest, Holographic Interferometry (Wiley, New York, 1979).

Winter, C.

J. Schorner, A. Ettemeye, U. Neupert, H. Rottenko, C. Winter, “New approaches interpreting holographic images,” Opt. Lasers Eng. 14, 283–291 (1991).
[CrossRef]

Yu, E.

E. Yu, S. S. Cha, W. Joo, “Use of interferometric directionality for noise reduction,” Opt. Eng. 34, 173–182 (1995).
[CrossRef]

Yu, Y. H.

F. Becker, Y. H. Yu, “Digital fringe reduction techniques applied to the measurement of three-dimensional transonic flow fields,” Opt. Eng. 24, 429–434 (1985).

IEEE Trans. Pattern Anal. Mach. Intell. (1)

M. D. Levine, S. I. Shaheen, “A modular computer vision for picture segmentation and interpretation,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-3, 540–556 (1981).
[CrossRef]

Opt. Eng. (2)

F. Becker, Y. H. Yu, “Digital fringe reduction techniques applied to the measurement of three-dimensional transonic flow fields,” Opt. Eng. 24, 429–434 (1985).

E. Yu, S. S. Cha, W. Joo, “Use of interferometric directionality for noise reduction,” Opt. Eng. 34, 173–182 (1995).
[CrossRef]

Opt. Lasers Eng. (3)

J. Schorner, A. Ettemeye, U. Neupert, H. Rottenko, C. Winter, “New approaches interpreting holographic images,” Opt. Lasers Eng. 14, 283–291 (1991).
[CrossRef]

G. T. Reid, “Automatic fringe pattern analysis: a review,” Opt. Lasers Eng. 7, 37–68 (1987).
[CrossRef]

T. M. Kreis, “Computer aided evaluation of fringe patterns,” Opt. Lasers Eng. 19, 221–240 (1993).
[CrossRef]

Patt. Recog. (1)

N. Nandhakumar, J. K. Affarwal, “The artificial intelligence approach to pattern recognition: a prospective and an overview,” Patt. Recog. 18, 383–389 (1985).
[CrossRef]

Other (8)

M. E. Denofsky, “How near is near?” MIT-AI Demo-334 (Artificial Intelligence Laboratory, MIT, Cambridge, Mass., 1976).

J. Slepica, S. S. Cha, “Stabilization of ill-posed nonlinear regression method and its application to interferogram reduction,” in Second International Conference on Photomechanics and Speckle Metrology: Moire Techniques, Holographic Interferometry, Optical NDT, and Applications to Fluid Mechanics, F.-P. Chiang, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 1554B, 574–579 (1991).

J. J. Gierloff, “Phase unwrapping by regions,” in Current Developments in Optical Engineering II, R. E. Fisher, W. J. Smith, eds., Proc. Soc. Photo-Opt. Instrum. Eng. 818, 2–9 (1987).

J. Giarratano, G. Riley, Expert System: Principle and Programming (PWS-Kent, Boston, 1989).

A. Choudry, “Automated fringe reduction techniques,” in Proceedings of Interferometric Metrology, N. A. Massie, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 816, p. 49–55 (1987).

D. W. Robinson, G. T. Reid, Interferogram Analysis: Digital Fringe Pattern Measurement Techniques (Institute of Physics, Philadelphia, 1993).

C. M. Vest, Holographic Interferometry (Wiley, New York, 1979).

R. J. Pryputniewicz, K. A. Stetson, “Measurement of vibration patterns using electro-optic holography,” in Proceedings of Laser Interferometry: Quantitative Analysis of Interferograms, R. J. Pryputniewicz, ed., Proc. Soc. Photo-Opt. Instrum. Eng. 1162, 456–467 (1989).

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (8)

Fig. 1
Fig. 1

Overall structure of the developed integrated expert system.

Fig. 2
Fig. 2

Database structure, data processing, and data flow diagram.

Fig. 3
Fig. 3

Unified procedure for automated interferogram analysis.

Fig. 4
Fig. 4

Hierarchical structure in the IES inferencing.

Fig. 5
Fig. 5

Intermediate results of low-level processing: (a) original noise-ridden image, (b) uneven background intensity, (3) image after directional smoothing and background subtraction, and (d) edge-detected binary fringes.

Fig. 6
Fig. 6

Thresholding results after (a) ordinary smoothing, (b) directional smoothing, and background subtraction.

Fig. 7
Fig. 7

Results of the high-level processing: (a) line-fringe map, (b) broken-line map, (c) complete-line map, and (d) final isophase line map with fringe-order numbers.

Fig. 8
Fig. 8

Classification of typical fringe shapes; thick lines indicate line-fringes.

Tables (1)

Tables Icon

Table 1 Examples of Combining Feature Qualifiers in Classifying Fringe Shapes

Equations (4)

Equations on this page are rendered with MathJax. Learn more.

I i ( x , y ) = B ( x , y ) + A ( x , y ) cos [ Φ ( x , y ) + Δ Φ i ] ,
Φ ( x , y ) = arctan [ 3 I 3 ( x , y ) - I 2 ( x , y ) 2 I 1 ( x , y ) - I 2 ( x , y ) - I 3 ( x , y ) ] .
I ( x , y ) = B ( x , y ) + C ( x , y ) + C * ( x , y ) ,
Φ ( x , y ) = arctan Im C ( x , y ) Re C ( x , y ) .

Metrics