In this paper, we present a vehicular buried threat detection approach developed over the past several years, and its latest implementation and integration in VPEF environment. Buried threats have varying signatures under different operation environment. To reliably detect the true targets and minimizing the number of false alarms, a suite of false alarm mitigators (FAMs) have been developed to process the potential targets identified by the baseline module. A vehicle track can be formed over a number of frames and targets are further analyzed both spatially and temporally. Algorithms have been implemented in C/C++ as GStreamer plugins and are suitable for vehicle mounted, on-the-move realtime exploitation.

Date Published: 14 May 2015
PDF: 14 pages
Proc. SPIE 9454, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX, 94540P (14 May 2015); doi: 10.1117/12.2177743

Published in SPIE Proceedings Vol. 9454:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX
Steven S. Bishop; Jason C. Isaacs, Editor(s)