Morphology-based detection/discrimination of ground vehicles in terrain board FLIR imagery

This paper describes a unified set of algorithms for the detection and discrimination of ground vehicles in second generation FLIR imagery. The computational substrate uses morphological signal processing and fractal analysis for a potential high-speed hardware implementation. The reported results are focused on the discrimination stage of the overall process. We demonstrate significant false alarm reduction through the use of textural and structural measures and a multistage discrimination procedure. The multistage discrimination process combines hard thresholding and fuzzy classification logic.