Abstract
Millimeter Wave (MMW) imaging systems are currently being used to detect hidden threats. Unfortunately the current performance of detection algorithms is very poor due to the presence of severe noise, the low resolution of MMW images and, in general, the poor quality of the acquired images. In this paper we present a new real time MMW threat detection algorithm based on a tailored de-noising, body and threat segmentation, and threat detection process that outperforms currently existing detection procedures. A complete comparison with a state of art threat detection algorithm is presented in the experimental section.
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