OSA's Digital Library

Optics Express

Optics Express

  • Editor: Michael Duncan
  • Vol. 14, Iss. 12 — Jun. 12, 2006
  • pp: 5143–5153

Segmentation of 3D holographic images using bivariate jointly distributed region snake

Mehdi DaneshPanah and Bahram Javidi  »View Author Affiliations

Optics Express, Vol. 14, Issue 12, pp. 5143-5153 (2006)

View Full Text Article

Enhanced HTML    Acrobat PDF (338 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



In this paper, we describe the bivariate jointly distributed region snake method in segmentation of microorganisms in Single Exposure On-Line (SEOL) holographic microscopy images. 3D images of the microorganisms are digitally reconstructed and numerically focused from any arbitrary depth from a single recorded digital hologram without mechanical scanning. Living organisms are non-rigid and they vary in shape and size. Moreover, they often do not exhibit clear edges in digitally reconstructed SEOL holographic images. Thus, conventional segmentation techniques based on the edge map may fail to segment these images. However, SEOL holographic microscopy provides both magnitude and phase information of the sample specimen, which could be helpful in the segmentation process. In this paper, we present a statistical framework based on the joint probability distribution of magnitude and phase information of SEOL holographic microscopy images and maximum likelihood estimation of image probability density function parameters. An optimization criterion is computed by maximizing the likelihood function of the target support hypothesis. In addition, a simple stochastic algorithm has been adapted for carrying out the optimization, while several boosting techniques have been employed to enhance its performance. Finally, the proposed method is applied for segmentation of biological microorganisms in SEOL holographic images and the experimental results are presented.

© 2006 Optical Society of America

OCIS Codes
(100.6890) Image processing : Three-dimensional image processing
(170.3880) Medical optics and biotechnology : Medical and biological imaging

ToC Category:
Image Processing

Original Manuscript: March 1, 2006
Revised Manuscript: May 12, 2006
Manuscript Accepted: May 16, 2006
Published: June 12, 2006

Virtual Issues
Vol. 1, Iss. 7 Virtual Journal for Biomedical Optics

Mehdi DaneshPanah and Bahram Javidi, "Segmentation of 3D holographic images using bivariate jointly distributed region snake," Opt. Express 14, 5143-5153 (2006)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. A. K. Jain, Fundamentals of digital image processing, (Prentice Hall, 1989).
  2. W. K. Pratt, Digital Image Processing, (Wiley, 2001). [CrossRef]
  3. R. M. Haralick and L. G. Shapiro, "Image segmentation techniques," Computer Vision, Graphics, and Image Processing 29, 100-132 (1985). [CrossRef]
  4. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern classification, 2nd ed. (Wiley Interscience, New York, 2000).
  5. J. W. Goodman, and R. W. Lawrence, "Digital image formation from electronically detected holograms," App. Phys. Lett. 11, 77-79 (1967). [CrossRef]
  6. J. H. Bruning, D. R. Herriott, J. E. Gallagher, D. P. Rosenfeld, A. D. White, and D. J. Brangaccio, "Digital wavefront measuring interferometer for testing optical surfaces and lenses" Appl. Opt. 13, 2693-2703 (1974). [CrossRef]
  7. U. Schnars and W. P. O. Juptner, "Direct recording of holograms by a CCD target and numerical reconstruction," Appl. Opt. 33, 179-181 (1994). [CrossRef] [PubMed]
  8. T. Nomura, A. Okazaki, M. Kameda, Y. Morimoto, and B. Javidi, "Image reconstruction from compressed encrypted digital hologram," Opt. Eng. 44 (2005). [CrossRef]
  9. T. J. Naughton, Y. Frauel, B. Javidi, and E. Tajahuerce, "Compression of digital holograms for three-dimensional object reconstruction and recognition," Appl. Opt. 41, 4124-4132 (2002). [CrossRef] [PubMed]
  10. T. J. Naughton, A. E. Shortt, and B. Javidi, "Nonuniform quantization compression of digital holograms," Opt. Lett. (2006) (submitted).
  11. O. Matoba, T. J. Naughton, Y. Frauel, N. Bertaux, and B. Javidi, "Real-time three-dimensional object reconstruction by use of a phase-encoded digital hologram," Appl. Opt. 41, 6187-6192 (2002). [CrossRef] [PubMed]
  12. B. Javidi and D. Kim, "Three-dimensional-object recognition by use of single-exposure on-axis digital holography," Opt. Lett. 30, 236-238 (2005). [CrossRef] [PubMed]
  13. D. Kim and B. Javidi, "Distortion-tolerant 3-D object recognition by using single exposure on-axis digital holography," Opt. Express 12, 5539-5548 (2005). [CrossRef]
  14. B. Javidi, I. Moon, S. Yeom, and E. Carapezza, "Three-dimensional imaging and recognition of microorganism using single-exposure on-line (SEOL) digital holography," Opt. Express 13, 4492-4506 (2005). [CrossRef] [PubMed]
  15. B. Javidi, S. Yeom, I. Moon, and M. Daneshpanah, "Real-time automated 3D sensing, detection, and recognition of dynamic biological micro-organic events," Opt. Express 14, 3806-3829 (2006). [CrossRef] [PubMed]
  16. I. Moon and B. Javidi, "Shape-tolerant three-dimensional recognition of biological microorganisms using digital holography," Opt. Express 13, 9612-9622 (2005). [CrossRef] [PubMed]
  17. T. Zhang and I. Yamaguchi, "Three-dimensional microscopy with phase-shifting digital holography," Opt. Lett. 23,1221-1223 (1998). [CrossRef]
  18. T. Kreis, ed., Handbook of Holographic Interferometry, (Wiley, VCH, 2005).
  19. H. J. W. Goodman, Introduction to Fourier Optics, 2nd ed. (McGraw Hill, New York, 1996).
  20. O. Germain and P. Refregier, "Optimal snake-based segmentation of a random luminance target on a spatially disjoint background," Opt. Lett. 21, 1845-1847 (1996). [CrossRef] [PubMed]
  21. C. Chesnaud, V. Page, and P. Refregier, "Improvement in robustness of the statistically independent region snake-based segmentation method of target-shape tracking," Opt. Lett. 23, 488-490 (1998). [CrossRef]
  22. C. Chesnaud, P. Refregier and V. Boulet, "Statistical region snake-based segmentation adapted to different physical noise models," IEEE Trans. on Pattern Analysis and Machine Intelligence 21, 1145-1157 (1999). [CrossRef]
  23. O. Germain, and P. Refregier, "Edge detection and location in SAR images: Contribution of statistical deformable models," in Image Recognition and Classification: Algorithms, Systems, and Applications, B. Javidi, ed. (Marcel Dekker, New York, 2002), Chap. 4.
  24. M. Kass, A. Witkin, and D. Terzopoulus, "Snakes: Active contour models," Int. J. Comput. Vis. 1, 321-331 (1987). [CrossRef]
  25. C. Xu, and J. L. Prince, "Snakes, shapes, and gradient vector flow," IEEE Trans. Image Process. 7, 359-369 (1998). [CrossRef]
  26. L. D. Cohen, "On active contour models and balloons," CVGIP: Image Understanding 53, 211-218 (1991). [CrossRef]
  27. C. Kervrann, and F. Heitz, "A hierarchical statistical framework for the segmentation of deformable objects in image sequences," in Proceedings of IEEE Conf. on Computer Vision and Pattern Recognition, (Institute of Electrical and Electronics Engineers, Seattle, 1994), pp. 724-728.
  28. R. Deriche, "Using Canny's criteria to derive a recursively implemented optimal edge detector," Int. J. Comp.Vis. 1, 167-187 (1987). [CrossRef]
  29. B. Javidi and J. Wang, "Limitations of the classic definition of the signal-to-noise ratio in matched filter based optical pattern recognition," Appl. Opt. 31, 6826-6829 (1992). [CrossRef] [PubMed]
  30. B. Javidi and J. Wang, "Optimum distortion invariant filters for detecting a noisy distorted target in background noise," J. Opt. Soc. Am. A 12, 2604-2614 (1995). [CrossRef]
  31. L. Vincent, and P. Soille, "Watersheds in digital spaces: an efficient algorithm based on immersion simulations," IEEE Trans. on Pattern Analysis and Machine Intelligence 13, 583-598 (1991). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


Fig. 1. Fig. 2. Fig. 3.
Fig. 4.

Supplementary Material

» Media 1: MOV (1100 KB)     
» Media 2: MOV (2405 KB)     

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited