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Proceedings Paper

Likelihood-based dual-threshold selection for imaging target trackers
Author(s): Larisa Stephan; Gillian K. Groves
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Paper Abstract

Most greylevel threshold-selection algorithms find thresholds that are optimal according to specific regional or global statistics. These traditional approaches do not involve any model of the target except that it is expected to be separable from the background by a threshold suite. Thus, they fail to make use of the most important feature of imaging target trackers: the well-known location of the target in each frame. We present a technique that uses knowledge of the target location to build up a temporally- smoothed greylevel distribution map from which we extract two thresholds that separate from the background the greylevels with a high probability of belonging to the target under track.

Paper Details

Date Published: 7 July 2000
PDF: 8 pages
Proc. SPIE 4025, Acquisition, Tracking, and Pointing XIV, (7 July 2000); doi: 10.1117/12.391659
Show Author Affiliations
Larisa Stephan, Raytheon Co. (United States)
Gillian K. Groves, Raytheon Co. (United States)

Published in SPIE Proceedings Vol. 4025:
Acquisition, Tracking, and Pointing XIV
Michael K. Masten; Larry A. Stockum, Editor(s)

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