BiTS – A Biologically-Inspired Target Screener for Detecting Manmade Objects in Natural Clutter Backgrounds

Motivated by biologically-inspired architectures for video analysis and object recognition, a new single band electro-optical (EO) object detector is described for aerial reconnaissance and surveillance applications. Our bio-inspired target screener (BiTS) uses a bank of Gabor filters to compute a vector of texture features over a range of scales and orientations. The filters are designed to exploit the spatial anisotropy of manmade objects relative to the background. The background, which is assumed to be predominantly natural clutter, is modeled by its global mean and covariance. The Mahalanobis distance measures deviations from the background model on a pixel-by-pixel basis. Possible manmade objects occur at peaks in the distance image. We measured the performance of BiTS on a set of 100 ground-truthed images taken under different operating conditions (resolution, sensor geometry, object spacings, background clutter, etc.) and found its probability of detection (PD) was 12% higher than a RX anomaly detector, with half the number of false alarms at a PD of 80%.