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http://dx.doi.org/10.7840/KICS.2012.37C.2.181

Real-time passive millimeter wave image segmentation for concealed object detection  

Lee, Dong-Su (대구대학교 정보통신공학부)
Yeom, Seok-Won (대구대학교 정보통신공학부)
Lee, Mun-Kyo (삼성탈레스)
Jung, Sang-Won (삼성탈레스)
Chang, Yu-Shin (삼성탈레스)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.37, no.2C, 2012 , pp. 181-187 More about this Journal
Abstract
Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people in both indoors and outdoors. However, because of the diffraction limit and low signal level, the imaging system often suffers from low image quality. Therefore, suitable statistical analysis and computational processing would be required for automatic analysis of the images. In this paper, a real-time concealed object detection is addressed by means of the multi-level segmentation. The histogram of the image is modeled with a Gaussian mixture distribution, and hidden object areas are segmented by a multi-level scheme involving $k$-means, the expectation-maximization algorithm, and a decision rule. The complete algorithm has been implemented in C++ environments on a standard computer for a real-time process. Experimental and simulation results confirm that the implemented system can achieve the real-time detection of concealed objects.
Keywords
passive millimeter wave; segmentation; real-time; concealed-object detection; Open-CV; clustering;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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