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Knowledge-Based Segmentation for Tracking Through Deep Turbulence

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6 Author(s)
Vela, P.A. ; Georgia Inst. of Technol., Atlanta ; Niethammer, M. ; Pryor, G.D. ; Tannenbaum, A.R.
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A combined knowledge-based segmentation/active contour algorithm is used for target tracking through turbulence. The algorithm utilizes Bayesian modeling for segmentation of noisy imagery obtained through longrange, laser imaging of a distance target, and active contours for tip tracking. The algorithm demonstrates improved target tracking performance when compared to weighted centroiding. Open-loop and closed-loop comparisons of the algorithms using simulated imagery validate the hypothesis.

Published in:

Control Systems Technology, IEEE Transactions on  (Volume:16 ,  Issue: 3 )

Date of Publication:

May 2008

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