Analysis of an optical target tracking system implementing a snake-based segmentation

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5181, Issue , 2003, Pages 85-92

  Matwyschuk, A ^a   Ambs, P ^b   Christnacher, F ^a  

^a FRENCH GERMAN RESEARCH INSTITUTE OF SAINT LOUIS   (France)

^b UNIVERSITÉ DE HAUTE ALSACE   (France)

Author keywords

Correlator; Optical information processing; Spatial light modulator

Indexed keywords

ALGORITHMS; CORRELATORS; LIGHT MODULATION; LIQUID CRYSTALS; OPTICAL CORRELATION; OPTICAL DATA PROCESSING; OPTIMIZATION; PHOTODETECTORS; POLARIZATION; SIGNAL TO NOISE RATIO;

CORRELATION FILTERS; JOINT TRANSFORM CORRELATORS (JFT); OPTICAL TARGET TRACKING SYSTEM;

OPTICAL SYSTEMS;

EID: 2342616238     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.508277     Document Type: Conference Paper

References (17)

1. F.T.S. Yu and I.E. Ludman, "Microcomputer-based programmable optical correlator for automatic pattern recognition and identification", Optics Letters, 11, 395, 1986.
2. F.T.S. Yu, S. Jutamulia, T.W. Lin, D.A. Gregory, "Adaptative real-time pattern recognition using a liquid crystal TV based joint transform correlator", Applied Optics, 26, 1370, 1987.
3. E. C. Tam, F. T. S. Yu, D. A. Gregory, R. D. Juday, "Autonomous real-time objet tracking with an adaptative joint transform correlator", Optical Engineering, 29(4), 314-320, 1990.
4. M. Kass, A. Witkin and D. Terzopoulos, "Snakes: Active Contour Models", International Journal of Computer Vision, 1, 321-331, 1988.
5. F. Goudail and Ph. Réfrégier, "Optimal detection of a target with random gray levels on a spatially disjoint background noise", Optics Letters, 21, 495-497, 1996.
6. Ch. Chesnaud, V. Page and Ph. Réfrégier, "Improvement in robustness of the statistically independent region snake-based segmentation method of target-shape tracking", Optics Letters, 23, 488-490, 1998.
7. O. Germain and Ph. Réfrégier, "Optimal snake-based segmentation of a random luminance target on a spatially disjoint background", Optics Letters, 21, 1845-1847, 1996.
8. P. Réfrégier, O. Germain and T. Gaidon, "Optimal snake segmentation of target and background with independent Gamma density probablities, application to speckled and prepocessed images", Optics Communications, 137, 382-388, 1997.
9. C. Chesnaud and P. Réfrégier, "Snaked-based target segmentation implementable on optical correlators", SPIE Optical Processing & Computing, 3490, 30-33, 1998.
10. E. Hueber, L. Bigué, P. Réfrégier and P. Ambs, "Optical snake-based segmentation processor with a shadow-casting incoherent correlator", Optics Letters 26 (23), 1852-1854 (2001).
11. A. Matwyschuk, P. Ambs and F. Christnacher, "Improvement of the optical target tracking using a snake-based segmentation", in 1st Workshop Information Optics IOG 2002, 75-78, Mannheim, Germany, 2002.
12. A. Matwyschuk, P. Ambs and F. Christnacher, "Target tracking correlator assisted by a snake-based optical segmentation method", Optics Communications, 219/1-6, 125-137, 2003.
13. B. Javidi and J. Wang, "Limitation of the classic definition of the correlation signal-to-noise ratio in optical pattern recognition with disjoint signal and scene noise", Applied Optics, 31 (32), 6826-6829, 1992.
14. C. S. Weaver and J. W. Goodman, "A technique for optically convolving two functions", Applied Optics, 5, 1248-1249, 1966.
15. D. Casasent and J. Chen, "Nonlinear local image preprocessing using coherent optical techniques", Applied Optics 22 (6), 808-814 (1983).
16. B. Javidi, "Comparison of the nonlinear joint transform correlator and the nonlinearly transformed matched filter based correlator for noisy input scenes ", Optical Engineering, 29(9), 1013-1020, 1990.
17. L. S. Jamal-Aldin, R. C. D. Young and C. R. Chatwin, "Non-linear pre-processing operation for enhancing correlation filter performance in clutter ", SPIE, 3490, 182-186, 1998.