<title>Sequential digital filters for fast detection of targets in FLIR image data</title>

Abstract

This paper revisits the applications of CFAR and morphological techniques to the problem of FLIR ATR. For many years, both morphology and CFAR approaches have been researched and tested in various automatic target recognition applications. However, detecting targets accurately and efficiently with a minimal false alarm presence continues to be a problem. The morphology based algorithm introduced in this paper employs closing and opening operations in parallel and subtracts the output from the original image to remove clutter that is larger than the target. The CFAR detector algorithm extracts targets by adaptively thresholding the input image at levels proportional to the local background statistics. The advantages and drawbacks of each technique are discussed, as well as the performance results on multiple databases. Experimental evaluations indicate that both algorithms perform well, even for low contrast targets and high clutter environments. These algorithms demonstrate improvement on a morphological multistage technique discussed.