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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 43, Iss. 25 — Sep. 1, 2004
  • pp: 4874–4881

Dynamic target tracking with fringe-adjusted joint transform correlation and template matching

Abdullah Bal and Mohammad S. Alam  »View Author Affiliations


Applied Optics, Vol. 43, Issue 25, pp. 4874-4881 (2004)
http://dx.doi.org/10.1364/AO.43.004874


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Abstract

Target tracking in forward-looking infrared (FLIR) video sequences is a challenging problem because of various limitations such as low signal-to-noise ratio (SNR), image blurring, partial occlusion, and low texture information, which often leads to missing targets or tracking nontarget objects. To alleviate these problems, we developed a novel algorithm that involves local-deviation-based image preprocessing as well as fringe-adjusted joint-transform-correlation- (FJTC) and template-matching- (TM) based target detection and tracking. The local-deviation-based preprocessing technique is used to suppress smooth texture such as background and to enhance target edge information. However, for complex situations such as the target blending with background, partial occlusion of the target, or proximity of the target to other similar nontarget objects, FJTC may produce a false alarm. For such cases, the TM-based detection technique is used to compensate FJTC breaking points by use of cross-correlation coefficients. Finally, a robust tracking algorithm is developed by use of both FJTC and TM techniques, which is called FJTC-TM technique. The performance of the proposed FJTC-TM algorithm is tested with real-life FLIR image sequences.

© 2004 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(100.5010) Image processing : Pattern recognition

History
Original Manuscript: December 23, 2003
Revised Manuscript: May 4, 2004
Manuscript Accepted: May 5, 2004
Published: September 1, 2004

Citation
Abdullah Bal and Mohammad S. Alam, "Dynamic target tracking with fringe-adjusted joint transform correlation and template matching," Appl. Opt. 43, 4874-4881 (2004)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-43-25-4874


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References

  1. H. Shekarforoush, R. Chellappa, “A multi-fractal formalism for stabilization, object detection and tracking in FLIR sequences,” IEEE Int. Conf. Image Proc. 3, 78–81 (2000).
  2. J. Y. Chen, I. S. Reed, “A detection algorithm for optical targets in clutter,” IEEE Trans. Aerosp. Electron. Syst. 23, 46–59 (1987). [CrossRef]
  3. A. Yilmaz, K. Shafique, M. Shah, “Target tracking in airborne forward looking infrared imagery,” Image Vision Comput. 21, 623–635 (2003). [CrossRef]
  4. F. Cheng, F. T. S. Yu, D. A. Gregory, “Multitarget detection using spatial synthesis joint transform correlator,” Appl. Opt. 32, 6521–6526 (1993). [CrossRef] [PubMed]
  5. Q. Tang, B. Javidi, “Multiple-object detection with a chirp-encoded joint transform correlator,” Appl. Opt. 32, 4344–4350 (1993). [CrossRef]
  6. P. C. Miller, M. Royce, P. Virgo, M. Fiebig, G. Hamlyn, “Evaluation of an optical correlator automatic target recognition system for acquisition and tracking in densely cluttered natural scenes,” Opt. Eng. 38, 1814–1825 (1999). [CrossRef]
  7. M. S. Alam, D. Chain, “Efficient multiple target recognition using a wavelet transform processor,” Opt. Eng. 39, 1203–1210 (2000). [CrossRef]
  8. M. S. Alam, M. A. Karim, “Multiple target detection using a modified fringe-adjusted joint transform correlator,” Opt. Eng. 33, 1610–1617 (1994). [CrossRef]
  9. M. S. Alam, “Phase-encoded fringe-adjusted joint transform correlation,” Opt. Eng. 39, 1169–1176 (2000). [CrossRef]
  10. M. S. Alam, J. G. Bognar, R. C. Hardie, B. J. Yasuda, “Infrared image registration and high resolution reconstruction using multiple translationally shifted aliased video frames,” IEEE Trans. Instrum. Meas. 49, 915–923 (2000). [CrossRef]
  11. Y. Wu, T. S. Huang, “Non-stationary color tracking for vision-based human-computer interaction,” IEEE Trans. Neural Netw. 13, 948–960 (2002). [CrossRef]
  12. E. Oron, A. Kumar, Y. Barshalom, “Precision tracking with segmentation for imaging sensors,” IEEE Trans. Aerosp. Electron. Syst. 29, 977–987 (1993). [CrossRef]
  13. A. K. Rastogi, B. N. Chatterji, A. K. Ray, “Design of real-time tracking system for fast moving objects,” IETE J. Res. 43, 359–369 (1997).
  14. K. S. Gudmundsson, A. A. S. Awwal, “Sub-imaging technique to improve phase only filter search capability,” Appl. Opt. 42, 4709–4717 (2003). [CrossRef] [PubMed]
  15. K. Brunnstrom, B. N. Schenkman, B. Jacobson, “Object detection in cluttered infrared images,” Opt. Eng. 42, 388–399 (2003). [CrossRef]
  16. S. Sun, H. W. Park, “Automatic target recognition using boundary partitioning and invariant features in forward-looking infrared images,” Opt. Eng. 42, 524–533 (2003). [CrossRef]
  17. B. Javidi, C. Kuo, “Joint transform image correlation using a binary spatial light modulator at the Fourier plane,” Appl. Opt. 27, 663–665 (1988). [CrossRef] [PubMed]
  18. S. K. Rogers, J. D. Cline, M. Kabrisky, “New binarization techniques for joint transform correlation,” Opt. Eng. 29, 1018–1093 (1990).
  19. M. S. Alam, “Deblurring using fringe-adjusted joint transform correlation,” Opt. Eng. 37, 556–564 (1998). [CrossRef]
  20. M. S. Alam, M. A. Karim, “Improved correlation discrimination in a multiobject bipolar joint transform correlator,” Opt. Laser Tech. 24, 45–50 (1992). [CrossRef]
  21. F. T. S. Yu, F. Cheng, T. Nagata, D. A. Gregory, “Effects of fringe binarization of multiobject joint transform correlation,” Appl. Opt. 28, 2988–2990 (1989). [CrossRef] [PubMed]
  22. B. V. K. V. Kumar, L. Hassebrook, “Performance measures for correlation filters,” Appl. Opt. 29, 2997–3006 (1990). [CrossRef] [PubMed]
  23. R. Singh, B. V. Kumar, “Performance of the extended maximum average correlation height (EMACH) filter and the polynomial distance classifier correlation filter (PDCCF) for multiclass SAR detection and classification,” in Algorithms for Synthetic Aperture Radar Imagery IX, E. G. Zelnio, ed., Proc. SPIE4727, 265–276 (2002). [CrossRef]
  24. A. Mahalanobis, A. R. Sims, A. V. Nevel, “Signal-to-clutter measure for measuring automatic target recognition performance using complimentary eigenvalue distribution analysis,” Opt. Eng. 42, 1144–1151 (2003). [CrossRef]

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