Knowledge-Based Segmentation for Tracking Through Deep Turbulence
Vela, Patricio A.
Pryor, Gallagher D.
Tannenbaum, Allen 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. Index Terms—Active contours, Bayesian statistics, geometric flows, tracking, turbulence.