Journal of the Optical Society of Korea

  • 제14권4호
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  • Pages.388-394
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  • 2010
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  • 1226-4776(pISSN)
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  • 2093-6885(eISSN)
한국광학회 (Optical Society of Korea)
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Comparisons of Object Recognition Performance with 3D Photon Counting & Gray Scale Images

  • Lee, Chung-Ghiu (Department of Electronic Engineering, Chosun University) ;
  • Moon, In-Kyu (School of Computer Engineering, Chosun University)
  • 투고 : 2010.04.16
  • 심사 : 2010.11.15
  • 발행 : 2010.12.25
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초록

In this paper the object recognition performance of a photon counting integral imaging system is quantitatively compared with that of a conventional gray scale imaging system. For 3D imaging of objects with a small number of photons, the elemental image set of a 3D scene is obtained using the integral imaging set up. We assume that the elemental image detection follows a Poisson distribution. Computational geometrical ray back propagation algorithm and parametric maximum likelihood estimator are applied to the photon counting elemental image set in order to reconstruct the original 3D scene. To evaluate the photon counting object recognition performance, the normalized correlation peaks between the reconstructed 3D scenes are calculated for the varied and fixed total number of photons in the reconstructed sectional image changing the total number of image channels in the integral imaging system. It is quantitatively illustrated that the recognition performance of the photon counting integral imaging system can be similar to that of a conventional gray scale imaging system as the number of image viewing channels in the photon counting integral imaging (PCII) system is increased up to the threshold point. Also, we present experiments to find the threshold point on the total number of image channels in the PCII system which can guarantee a comparable recognition performance with a gray scale imaging system. To the best of our knowledge, this is the first report on comparisons of object recognition performance with 3D photon counting & gray scale images.

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참고문헌

  1. G. Lippmann, “La photographic integrale,” C. R. Acad. Sci. 146, 446-451 (1908).
  2. H. E. Ives, “Optical properties of a Lippmann lenticuled sheet,” J. Opt. Soc. Am. 21, 171-176 (1931). https://doi.org/10.1364/JOSA.21.000171
  3. B. Javidi, F. Okano, and J. Son, Three-dimensional Imaging, Visualization, and Display Technologies (Springer, New York, USA, 2008).
  4. T. Wei, D. Shin, and B. Lee, “Resolution-enhanced reconstruction of 3D object using depth-reversed elemental images for partially occluded object recognition,” J. Opt. Soc. Korea 13, 139-145 (2009). https://doi.org/10.3807/JOSK.2009.13.1.139
  5. R. Martinez-Cuenca, G. Saavedra, M. Martinez-Corral, and B. Javidi, “Progress in 3-D multiperspective display by integral imaging,” Proc. IEEE 97, 1067-1077 (2009).
  6. T. Okoshi, “Three-dimensional displays,” Proc. IEEE 68, 548-564 (1980). https://doi.org/10.1109/PROC.1980.11695
  7. F. Okano, J. Arai, K. Mitani, and M. Okui, “Real-time integral imaging based on extremely high resolution video system,” Proc. IEEE 94, 490-501 (2006). https://doi.org/10.1109/JPROC.2006.870687
  8. S. Park, B. Song, and S. Min, “Analysis of image visibility in projection-type integral imaging system without diffuser,” J. Opt. Soc. Korea 14, 121-126 (2010). https://doi.org/10.3807/JOSK.2010.14.2.121
  9. Y. Igarishi, H. Murata, and M. Ueda, “3D display system using a computer-generated integral photograph,” Jpn. J. Appl. Phys. 17, 1683-1684 (1978). https://doi.org/10.1143/JJAP.17.1683
  10. H. Arimoto and B. Javidi, “Integrate three-dimensional imaging with computed reconstruction,” Opt. Lett. 26, 157-159 (2001). https://doi.org/10.1364/OL.26.000157
  11. A. Stern and B. Javidi, “Three-dimensional image sensing, visualization, and processing using integral imaging,” Proc. IEEE 94, 591-607 (2006). https://doi.org/10.1109/JPROC.2006.870696
  12. M. Levoy, “Light fields and computational imaging,” IEEE Computer Mag. 39, 46-55 (2006).
  13. B. Tavakoli, B. Javidi, and E. Watson, “Three dimensional visualization by photon counting computational integral imaging,” Opt. Express 16, 4426-4436 (2008). https://doi.org/10.1364/OE.16.004426
  14. S. Yeom, B. Javidi, and E. Watson, “Photon counting passive 3D image sensing for automatic target recognition,” Opt. Express 13, 9310-9330 (2005). https://doi.org/10.1364/OPEX.13.009310
  15. I. Moon and B. Javidi, “Three-dimensional recognition of photon-starved events using computational integral imaging and statistical sampling,” Opt. Lett. 34, 731-733 (2009). https://doi.org/10.1364/OL.34.000731
  16. M. Guillanume, P. Melon, and P. Refregier, “Maximum-likelihood estimation of an astronomical image from a sequence at low photon levels,” J. Opt. Soc. Am. A 15, 2841-2848 (1998). https://doi.org/10.1364/JOSAA.15.002841
  17. J. W. Goodman, Statistical Optics (John Wiley & Sons, inc., Hoboken, USA, 1985).
  18. B. Javidi and E. Tajahuerce, “Three-dimensional object recognition by use of digital holography,” Opt. Lett. 25, 610-612 (2000). https://doi.org/10.1364/OL.25.000610