Abstract

This paper presents advanced image analysis methods for extracting information from high speed Planar Laser Induced Fluorescence (PLIF) data obtained from turbulent flames. The application of non-linear anisotropic diffusion filtering and of Active Contour Models (Snakes) is described to isolate flame boundaries. In a subsequent step, the detected flame boundaries are tracked in time using a frequency domain contour interpolation scheme. The implementations of the methods are described and possible applications of the techniques are discussed.

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References

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  1. J. Warnatz, U. Maas, and R.W. Dibble, Combustion - physical and chemical fundamentals, modeling and simulation, experiments, pollutant formation (Springer-Verlag, Heidelberg 1996).
  2. C.F. Kaminski, J. Hult, and M. Ald�n, ``High repetition rate planar laser induced fluorescence of OH in a turbulent non-premixed flame,' Appl. Phys. B 68, 757-760 (2000).
    [CrossRef]
  3. A. Dreizler, S. Lindenmaier, U. Maas, J. Hult, M. Ald�n, and C.F. Kaminski, ``Characterisation of a spark ignition system by planar laser-induced fluorescence of OH at high repetition rates and comparison with chemical kinetic calculations,' Appl. Phys. B 70, 287-294 (2000).
    [CrossRef]
  4. J. Hult, A. Omrane, J. Nygren, C.F. Kaminski, B. Axelsson, R. Collin, P.-E. Bengtsson, and M. Ald�n, ``Quantitative three dimensional imaging of soot volume fraction in turbulent non-premixed flames', (in preparation).
  5. G.J. Smallwood, O.L. Gulder, D.R. Snelling, B.M. Deschamps, and I. Gokalp, ``Characterization of flame front surfaces in turbulent premixed methane/air combustion,' Combustion and Flame 101(4), 461-470 (1995).
    [CrossRef]
  6. R. Knikker, D. Veynante, J.C. Rolon, and C. Meneveau, ``Planar Laser-Induced Fluorescence in a Turbulent Premixed Flame to analyze Large Eddy Simulation Models,' in Proceedings of the 10th international Symposium on Turbulence, Heat and Mass Transfer, Lisbon (2000), http://in3.dem.ist.utl.pt/downloads/lxlaser2000/pdf/26\_3.pdf
  7. B.D. Haslam and P.D. Ronney, ``Fractal properties of propagating fronts in a strongly stirred fluid,' Phys. Fluids 7(8), 1931-1937 (1995).
    [CrossRef]
  8. Y.-C. Chen and M.S. Mansour, ``Topology of turbulent premixed flame fronts resolved by simultaneous planar imaging of LIPF of OH radical and rayleigh scattering,' Experiments in Fluids 26, 277-287 (1999).
    [CrossRef]
  9. O.L. Gulder, G.J. Smallwood, R. Wong, D.R. Snelling, R. Smith, B.M. Deschamps, and J.-C. Sautet, `` Flame front surface characteristics in turbulent premixed propane/air combustion,' Combustion and Flame 120(4), 407-416 (2000).
    [CrossRef]
  10. P. Perona and J. Malik, ``Scale-space and edge detection using anisotropic diffusion,' IEEE Trans. on Pattern Analysis and Machine Intelligence 12(7), 629-639 (1990).
    [CrossRef]
  11. M. Kass, A. Witkin, and D. Terzopoulos, ``Snakes: Active Contour Models,' International Journal on Computer Vision 1(4), 321-331 (1988).
    [CrossRef]
  12. C.F. Kaminski, J. Hult, M. Ald�n, S. Lindenmaier, A. Dreizler, U. Maas, and M. Baum, ``Complex turbulence/chemistry interactions revealed by time resolved fluorescence and direct numerical simulations,' Proc. Combust. Inst. 28, The Combustion Institute, Pittsburgh, in press (2000).
  13. F. Catt�, P.-L. Lions, J.-M. Morel, and T. Coll, ``Image selective smoothing and edge detection by nonlinear diffusion,' SIAM J. Numer. Anal. 29, 182-193 (1992).
    [CrossRef]
  14. H. Malm, J. Hult, G. Sparr, and C.F. Kaminski, ``Non-linear diffusion filtering of images obtained by planar laser induced florescence spectroscopy,' J. Opt. Soc. Am. A 17, 2148-2156 (2000).
    [CrossRef]
  15. T. McInerney and D. Terzopoulos, ``T-Snakes: Topology adaptive snakes,' Medical Image Analysis 4, 73-91 (2000).
    [CrossRef] [PubMed]
  16. S. Lobregt and M. Viergever, ``A discrete dynamic contour model,' IEEE Trans. on Medical Imaging 14(1), 12-24 (1995).
    [CrossRef]
  17. A. Jain, Fundamentals of digital image processing (Prentice Hall, 1989).
  18. J. Hult , G. Josefsson, M. Ald\'{en, and C.F. Kaminski, ``Flame front tracking and simultaneous flow field visualization in turbulent combustion,' in Proceedings of the 10th International Symposium on Application of Laser Techniques to Fluid mechanics, Lisbon (2000), http://in3.dem.ist.utl.pt/downloads/lxlaser2000/pdf/26\_2.pdf
  19. V. Caselles, R. Kimmel, and G. Sapiro, ``Geodesic active contours,' in Proceedings of the International Conference on Computer Vision, 694 -699 (1995).

Other (19)

J. Warnatz, U. Maas, and R.W. Dibble, Combustion - physical and chemical fundamentals, modeling and simulation, experiments, pollutant formation (Springer-Verlag, Heidelberg 1996).

C.F. Kaminski, J. Hult, and M. Ald�n, ``High repetition rate planar laser induced fluorescence of OH in a turbulent non-premixed flame,' Appl. Phys. B 68, 757-760 (2000).
[CrossRef]

A. Dreizler, S. Lindenmaier, U. Maas, J. Hult, M. Ald�n, and C.F. Kaminski, ``Characterisation of a spark ignition system by planar laser-induced fluorescence of OH at high repetition rates and comparison with chemical kinetic calculations,' Appl. Phys. B 70, 287-294 (2000).
[CrossRef]

J. Hult, A. Omrane, J. Nygren, C.F. Kaminski, B. Axelsson, R. Collin, P.-E. Bengtsson, and M. Ald�n, ``Quantitative three dimensional imaging of soot volume fraction in turbulent non-premixed flames', (in preparation).

G.J. Smallwood, O.L. Gulder, D.R. Snelling, B.M. Deschamps, and I. Gokalp, ``Characterization of flame front surfaces in turbulent premixed methane/air combustion,' Combustion and Flame 101(4), 461-470 (1995).
[CrossRef]

R. Knikker, D. Veynante, J.C. Rolon, and C. Meneveau, ``Planar Laser-Induced Fluorescence in a Turbulent Premixed Flame to analyze Large Eddy Simulation Models,' in Proceedings of the 10th international Symposium on Turbulence, Heat and Mass Transfer, Lisbon (2000), http://in3.dem.ist.utl.pt/downloads/lxlaser2000/pdf/26\_3.pdf

B.D. Haslam and P.D. Ronney, ``Fractal properties of propagating fronts in a strongly stirred fluid,' Phys. Fluids 7(8), 1931-1937 (1995).
[CrossRef]

Y.-C. Chen and M.S. Mansour, ``Topology of turbulent premixed flame fronts resolved by simultaneous planar imaging of LIPF of OH radical and rayleigh scattering,' Experiments in Fluids 26, 277-287 (1999).
[CrossRef]

O.L. Gulder, G.J. Smallwood, R. Wong, D.R. Snelling, R. Smith, B.M. Deschamps, and J.-C. Sautet, `` Flame front surface characteristics in turbulent premixed propane/air combustion,' Combustion and Flame 120(4), 407-416 (2000).
[CrossRef]

P. Perona and J. Malik, ``Scale-space and edge detection using anisotropic diffusion,' IEEE Trans. on Pattern Analysis and Machine Intelligence 12(7), 629-639 (1990).
[CrossRef]

M. Kass, A. Witkin, and D. Terzopoulos, ``Snakes: Active Contour Models,' International Journal on Computer Vision 1(4), 321-331 (1988).
[CrossRef]

C.F. Kaminski, J. Hult, M. Ald�n, S. Lindenmaier, A. Dreizler, U. Maas, and M. Baum, ``Complex turbulence/chemistry interactions revealed by time resolved fluorescence and direct numerical simulations,' Proc. Combust. Inst. 28, The Combustion Institute, Pittsburgh, in press (2000).

F. Catt�, P.-L. Lions, J.-M. Morel, and T. Coll, ``Image selective smoothing and edge detection by nonlinear diffusion,' SIAM J. Numer. Anal. 29, 182-193 (1992).
[CrossRef]

H. Malm, J. Hult, G. Sparr, and C.F. Kaminski, ``Non-linear diffusion filtering of images obtained by planar laser induced florescence spectroscopy,' J. Opt. Soc. Am. A 17, 2148-2156 (2000).
[CrossRef]

T. McInerney and D. Terzopoulos, ``T-Snakes: Topology adaptive snakes,' Medical Image Analysis 4, 73-91 (2000).
[CrossRef] [PubMed]

S. Lobregt and M. Viergever, ``A discrete dynamic contour model,' IEEE Trans. on Medical Imaging 14(1), 12-24 (1995).
[CrossRef]

A. Jain, Fundamentals of digital image processing (Prentice Hall, 1989).

J. Hult , G. Josefsson, M. Ald\'{en, and C.F. Kaminski, ``Flame front tracking and simultaneous flow field visualization in turbulent combustion,' in Proceedings of the 10th International Symposium on Application of Laser Techniques to Fluid mechanics, Lisbon (2000), http://in3.dem.ist.utl.pt/downloads/lxlaser2000/pdf/26\_2.pdf

V. Caselles, R. Kimmel, and G. Sapiro, ``Geodesic active contours,' in Proceedings of the International Conference on Computer Vision, 694 -699 (1995).

Supplementary Material (3)

» Media 1: MOV (202 KB)     
» Media 2: MOV (1019 KB)     
» Media 3: MOV (144 KB)     

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Figures (7)

Fig. 1.
Fig. 1.

Schematic setup for time resolved PLIF of turbulent spark ignition.

Fig. 2.
Fig. 2.

An example showing a typical experimental image sequence. (a)-(d) Four images (381×291 pixels, 0.1408 mm/pixel) captured with 1.7 ms time increments respectively.

Fig. 3.
Fig. 3.

Sample image corresponding to a single shot PLIF image of OH. To the left the raw data is shown. The same data is shown to the right after 30 iterations using the non-linear diffusion algorithm described in the text. In the lower section of the figure, cross-sectional profiles corresponding to the horizontal green line in the images are shown. Contours are clearly enhanced and local noise is efficiently filtered out. An animation of the diffusion process is presented in the related animation file nldf.mov (202 KB).

Fig. 4.
Fig. 4.

An example illustrating the progress of the snake iterations: (a) The original raw image. (b) The initial snake (in red) applied on the non-linear diffusion filtered image. (c)-(e) The snake after 1, 25, and 85 iterations, respectively. (f) The final result overlaid on the original raw image. See the related animation file snake.mov (1 MB).

Fig. 5.
Fig. 5.

Temporal interpolation: Three validation tests (a)-(c) using synthetic examples. Top: Original synthetic sequences comprising F=16 shapes (generated by evolving a shape in time using predetermined controlled deformations). Centre: Four original shapes extracted from the synthetic sequence to be input into the interpolation algorithm. These 4 curves can be seen overlaid on the top figures in magenta, red, blue and cyan. Bottom: The interpolation result (reconstruction of 16 frames from 4 only). (a) Elliptical shapes: Error=3.53%. (b) Star shapes: Error=5.25%. (c) Shapes based on deforming a real flame boundary: Error=0.75%.

Fig. 6.
Fig. 6.

Temporal interpolation: (a-f) Different validation tests on synthetic examples. The original 4 contours are displayed in black and the interpolated ones in color.

Fig. 7.
Fig. 7.

An example of temporal interpolation on PLIF data: (a) The flame contours in an image sequence. The four original contours are shown in thick black and the interpolated ones in between are shown in random colors. (b) The calculated velocity vectors overlaid on the original contours. See related animation file interp.mov (144 KB). (c) The color map representation of the flame velocity values. The image shows the magnitude (in m/s) of the flame front velocity at each boundary point in each frame using the colormap shown to the right.

Equations (11)

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

t I = div ( g ( ( G σ * I ) ) I )
v i ( n ) = v i 1 ( n ) + w 1 F i tens ( n ) + w 2 F i flex ( n ) + w 3 F i ext ( n ) + w 4 F i inf ( n )
F i flex ( n ) = 2 v i ( n ) v i ( n 1 ) v i ( n + 1 )
F i flex ( n ) = 2 F i tens ( n ) F i tens ( n 1 ) F i tens ( n + 1 )
F i inf ( n ) = F ( I s ( x i ( n ) , y i ( n ) ) ) n i ( n )
F ( I ( x , y ) ) = { + 1 , I ( x , y ) T 1 , otherwise
F i ext ( n ) = P ( x i ( n ) , y i ( n ) )
X ( k , j ) = w ( k ) n = 1 N x ( n , j ) cos π ( 2 n 1 ) ( k 1 ) 2 N
w ( k ) = { 1 N , k = 1 2 N , 2 k N
x ( n , j ) = w ( k ) k = 1 N X ( k , j ) cos π ( 2 n 1 ) ( k 1 ) 2 N
ε = A i A o A i A o A o

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