A new pipeline approach is addressed for the task of detecting and tracking pixel-sized moving targets from a time sequence of dynamic images of a high-noise environment. The trajectories of the moving targets are unknown, but continuous and smooth. The image sequence contains significant, randomly drifting background clutter, and is also contaminated by random sensor noise. The Pipeline Target Detection Algorithm (PTDA) uses the temporal continuity of the smooth trajectories of moving targets, and successfully detects and simultaneously tracks all the target trajectories by re-constructing them from the time sequence of noisy images in a single targetframe in real time. The pipeline approach breaks the constraint of straight line trajectory that most other algorithms require for the similar tasks and detects and tracks any trajectories of arbitrary shapes as long as they are continuous and smooth. The pipeline fashion of the aigorithm is a complete parallel distributedprocessing (PDP) type process, and therefore is highly time efficient. It also agrees with the pattern that real image sequences are acquired, so is ideal for real-time target detection and tracking.

Date Published: 1 October 1990
PDF
Proc. SPIE 1305, Signal and Data Processing of Small Targets 1990, (1 October 1990); doi: 10.1117/12.2321758

Published in SPIE Proceedings Vol. 1305:
Signal and Data Processing of Small Targets 1990
Oliver E. Drummond, Editor(s)