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Applied Optics

Applied Optics


  • Vol. 41, Iss. 29 — Oct. 10, 2002
  • pp: 6135–6142

Recognition of unsegmented targets invariant under transformations of intensity

Daniel Lefebvre, Henri H. Arsenault, Pascuala Garcia-Martinez, and Carlos Ferreira  »View Author Affiliations

Applied Optics, Vol. 41, Issue 29, pp. 6135-6142 (2002)

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Images taken in noncooperative environments do not always have targets under the same illumination conditions. There is a need for methods to detect targets independently of the illumination. We propose a technique that yields correlation peaks that are invariant under a linear intensity transformation of object intensity. The new locally adaptive contrast-invariant filter accomplishes this by combining three correlations in a nonlinear way. This method is not only intensity invariant but also has good discrimination and resistance to noise. We present simulation results for various intensity transformations with and without random and correlated noise. When the noise is high enough to threaten errors, the method trades off intensity invariance in order to achieve the optimum signal to noise ratio, and the peak to sidelobe ratio in the presence of clutter is always greater than one. In the presence of random disjoint noise, the signal to noise ratio is independent of the target contrast and of the level of the noise.

© 2002 Optical Society of America

OCIS Codes
(070.0070) Fourier optics and signal processing : Fourier optics and signal processing
(070.4550) Fourier optics and signal processing : Correlators
(100.2000) Image processing : Digital image processing
(100.5010) Image processing : Pattern recognition
(150.2950) Machine vision : Illumination

Original Manuscript: April 2, 2002
Revised Manuscript: June 18, 2002
Published: October 10, 2002

Daniel Lefebvre, Henri H. Arsenault, Pascuala Garcia-Martinez, and Carlos Ferreira, "Recognition of unsegmented targets invariant under transformations of intensity," Appl. Opt. 41, 6135-6142 (2002)

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  1. F. M. Dickey, L. A. Romero, “Normalized correlation for pattern recognition,” Opt. Lett. 16, 1186–1188 (1991). [CrossRef] [PubMed]
  2. B. A. Kast, F. M. Dickey, “Normalization of correlators,” in Optical information processing systems and architectures III, B. Javidi, ed., Proc. Soc. Photo.-Opt. Instrum. Eng.1564, 34–42 (1991). [CrossRef]
  3. R. Kotynski, K. Chalasinska-Macukow, “Normalization of correlation filter based on the Hölder’s inequality,” in Optics in Computing ’98, P. H. Chavel, D. A. Miller, H. Thienpont, ed., Proc. Soc. Photo.-Opt. Instrum. Eng.3490, 195–198 (1998). [CrossRef]
  4. R. Kotynski, K. Chalasinska-Macukow, “Multi-object intensity-invariant pattern recognition with an optimum processor for correlated noise,” in 18th Congress of the International Commission for Optics, A. J. Glass, J. W. Goodman, M. Chang, A. H. Guenther, ed., Proc. Soc. Photo.-Opt. Instrum. Eng.3749, 316–317 (1999). [CrossRef]
  5. H. H. Arsenault, Y. Sheng, J. Bulabois, “Modified composite filter for pattern recognition in presence of noise with a non-zero mean,” Opt. Commun. 63, 15–20 (1987). [CrossRef]
  6. H. J. Caulfield, W. T. Maloney, “Improved discrimination in optical character recognition,” Appl. Opt. 19, 2354–2356 (1969). [CrossRef]
  7. C. F. Hester, D. Casasent, “Multivariate technique for multiclass pattern recognition,” Appl. Opt. 19, 1758–1761 (1980). [CrossRef] [PubMed]
  8. H. H. Arsenault, C. Belisle, “Contrast-invariant pattern recognition using circular harmonic component,” Appl. Opt. 24, 2072–2075 (1985). [CrossRef]
  9. Y.-H. Hsu, H. H. Arsenault, “Optical pattern recognition using circular harmonic expansion,” Appl. Opt. 21, 4016–4019 (1982). [CrossRef] [PubMed]
  10. P. Garcia-Martinez, H. H. Arsenault, C. Ferreira, “Binary image decomposition for intensity-invariant optical nonlinear correlation,” in Optics in Computing 2000, R. A. Lessard, T. V. Galstian, ed., Proc. Soc. Photo.-Opt. Instrum. Eng.4089, 433–438 (2000). [CrossRef]
  11. P. Garcia-Martinez, H. H. Arsenault, “A correlation matrix representation using sliced orthogonal nonlinear generalized decomposition,” Opt. Commun. 172, 181–192 (1999). [CrossRef]
  12. P. Garcia-Martinez, H. H. Arsenault, S. E. Roy, “Optical implementation of the sliced orthogonal nonlinear generalized correlation for image degraded by nonoverlapping noise,” Opt. Commun. 173, 185–193 (2000). [CrossRef]
  13. H. H. Arsenault, D. Lefebvre, “Homomorphic cameo filter for pattern recognition that is invariant with change of illumination,” Opt. Lett. 25, 1567–1569 (2000). [CrossRef]
  14. S. Zhang, M. A. Karim, “Illumination invariant pattern recognition with joint-transform-correlator-based morphological correlation,” Appl. Opt. 38, 7228–7237 (1999). [CrossRef]
  15. K. Chalasinska-Macukow, E. Baranska, “Discrimination of characters using phase information only,” J. Opt. Soc. A 21, 261–266 (1990).
  16. K. Chalasinska-Macukow, F. Turon, M. J. Yzuel, J. Campos, “Contrast performance of pure phase correlation,” J. Opt. Soc. A 24, 71–75 (1993).
  17. M. Rahmati, L. G. Hassebrook, B. V. K. Vijaya Kumar, “Automatic target recognition with intensity- and distortion-invariant hybrid composite filters,” in Optical Pattern Recognition IV, D. P. Casasent, ed.Proc. SPIE1959, 133–145 (1993). [CrossRef]
  18. J. T. Tippett, L. C. Clapp, eds. Optical and Electro-Optical Information Processing, (MIT Press, Cambridge, Mass., 1965), pp. 130–133.
  19. A. Papoulis, Probability, Random Processes and Stochastic Processes, 2nd ed. (McGraw-Hill, New York, 1984), p. 241.
  20. J. L. Horner, P. Gianino, “Phase-only matched filtering,” App. Opt. 23, 812–816 (1984). [CrossRef]
  21. A. Vander Lugt, “Signal detection by complex spatial filtering,” IEEE Trans. Inf. Theory. 10, 139–145 (1964). [CrossRef]

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