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Proceedings Paper

Multi-level segmentation of passive millimeter wave images with Gaussian mixture modeling
Author(s): Seokwon Yeom; Dong-Su Lee; Jung-Young Son
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Paper Abstract

Passive millimeter wave imaging is very useful for security applications since it candetect objects concealed under clothing. In this paper,the multi-level segmentation of passive millimeter wave images is presented to detectconcealed objects under clothing. Our passive millimeter wave imaging system is equipped with a Cassegrain dish antenna and a receiver channel operating around 3 mm wavelength. The expectation-maximization algorithm is adopted to cluster pixelson the basis ofa Gaussian mixture model. The multi-level segmentation is investigated with different numbers of clusters in Gaussian mixture distribution. The performance is evaluated by average probability error. Experimentsconfirm that the presented method is able to detect the wood grip as well as metal part of the hand axconcealed under clothing.

Paper Details

Date Published: 26 May 2011
PDF: 6 pages
Proc. SPIE 8023, Terahertz Physics, Devices, and Systems V: Advance Applications in Industry and Defense, 80230D (26 May 2011); doi: 10.1117/12.883778
Show Author Affiliations
Seokwon Yeom, Daegu Univ. (Korea, Republic of)
Dong-Su Lee, Daegu Univ. (Korea, Republic of)
Jung-Young Son, Daegu Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 8023:
Terahertz Physics, Devices, and Systems V: Advance Applications in Industry and Defense
Mehdi Anwar; Nibir K. Dhar; Thomas W. Crowe, Editor(s)

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