Automatic aerial target detection and tracking system inudairborne FLIR images based on efficient target trajectoryudfiltering

摘要

Common strategies for detection and tracking of aerial moving targets in airborne Forward-Looking Infraredud(FLIR) images offer accurate results in images composed by a non-textured sky. However, when cloud andudearth regions appear in the image sequence, those strategies result in an over-detection that increases veryudsignificantly the false alarm rate. Besides, the airborne camera induces a global motion in the image sequenceudthat complicates even more detection and tracking tasks. In this work, an automatic detection and trackingudsystem with an innovative and efficient target trajectory filtering is presented. It robustly compensates theudglobal motion to accurately detect and track potential aerial targets. Their trajectories are analyzed by a curveudfitting technique to reliably validate real targets. This strategy allows to filter false targets with stationary oruderratic trajectories. The proposed system makes special emphasis in the use of low complexity video analysisudtechniques to achieve real-time operation. Experimental results using real FLIR sequences show a dramaticudreduction of the false alarm rate, while maintaining the detection rate.