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Proceedings Paper

Maximum-likelihood approach to target tracking on image sequences
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Paper Abstract

Until now, most optical pattern recognition filters have been designed to process one image at a time. In contrast, many point-source target processing algorithms utilize successive frame integration to enhance the signal-to- clutter ratio. Our aim is to utilize the temporal correlation between successive frames in order to improve the tracking of extended targets appearing on very cluttered backgrounds. In our image model, the successive frames are assumed to consist of a moving object appearing on a moving background. From this model, the maximum-likelihood processor for tracking the object from one frame to the next one is derived. Given some simplifying assumptions, this processor is shown to consist in the linear combination of two sub-processors which are based on correlation operation. They could thus be implemented on a hybrid optoelectronical system that utilizes the rapidity of optical correlation.

Paper Details

Date Published: 27 March 1997
PDF: 12 pages
Proc. SPIE 3073, Optical Pattern Recognition VIII, (27 March 1997); doi: 10.1117/12.270383
Show Author Affiliations
Francois Goudail, Ecole Nationale Superieure de Physique Marseille (France)
Philippe Refregier, Ecole Nationale Superieure de Physique Marseille (France)


Published in SPIE Proceedings Vol. 3073:
Optical Pattern Recognition VIII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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