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


Vol. 37,  No. 2, pp. 181-187, Feb.  2012


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  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.

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  Cite this article

[IEEE Style]

D. Lee, S. Yeom, M. Lee, S. Jung, Y. Chang, "Real-time passive millimeter wave image segmentation for concealed object detection," The Journal of Korean Institute of Communications and Information Sciences, vol. 37, no. 2, pp. 181-187, 2012. DOI: .

[ACM Style]

Dong-Su Lee, Seokwon Yeom, Mun-Kyo Lee, Sang-Won Jung, and YuShin Chang. 2012. Real-time passive millimeter wave image segmentation for concealed object detection. The Journal of Korean Institute of Communications and Information Sciences, 37, 2, (2012), 181-187. DOI: .

[KICS Style]

Dong-Su Lee, Seokwon Yeom, Mun-Kyo Lee, Sang-Won Jung, YuShin Chang, "Real-time passive millimeter wave image segmentation for concealed object detection," The Journal of Korean Institute of Communications and Information Sciences, vol. 37, no. 2, pp. 181-187, 2. 2012.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880