@article{ref1,
title="Real-time outdoor concealed-object detection with passive millimeter wave imaging",
journal="Optics express",
year="2011",
author="Yeom, Seokwon and Lee, Dong-Su and Son, Jung-Young and Jung, Min-Kyoo and Jang, Yushin and Jung, Sang-Won and Lee, Seok-Jae",
volume="19",
number="3",
pages="2530-2536",
abstract="Millimeter wave imaging is finding rapid adoption in security applications such as the detection of objects concealed under clothing. A passive imaging system can be realized as a stand-off type sensor that can operate in open spaces, both indoors and outdoors. In this paper, we address real-time outdoor concealed-object detection and segmentation with a radiometric imaging system operating in the W-band. The imaging system is equipped with a dielectric lens and a receiver array operating at around 
94 GHz. Images are analyzed by multilevel segmentation to identify a concealed object. Each level of segmentation comprises vector quantization, expectation-maximization, and Bayesian decision making to cluster pixels on the basis of a Gaussian mixture model. In addition, we describe a faster process that adopts only vector quantization for the first level segmentation. Experiments confirm that the proposed methods provide fast and reliable detection and segmentation for a moving human subject carrying a concealed gun.<p /> <p>Language: en</p>",
language="en",
issn="1094-4087",
doi="",
url="http://dx.doi.org/"
}