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PIER PIER B PIER C PIER M PIER Letters PIER Photonics
2013-04-23
Vector Clustering of Passive Millimeter Wave Images with Linear Polarization for Concealed Object Detection
By
Seokwon Yeom,

    Dr. Seokwon Yeom

    Division of Computer and Communication Engineering

    Daegu Univ

    South Korea

    Homepage

Dongsu Lee,

    Dr. Dongsu Lee

    Daegu University

    Korea

    Homepage

Hyoung Lee,

    Dr. Hyoung Lee

    Daegu University

    Korea

    Homepage

Joungyoung Son,

    Dr. Joungyoung Son

    Daegu University

    Korea

    Homepage

Vladimir P. Gushin

    Dr. Vladimir P. Gushin

    Daegu University

    Korea

    Homepage

Progress In Electromagnetics Research Letters, Vol. 39, 169-180, 2013
doi:10.2528/PIERL13021907 | Google Scholar

Abstract
Passive millimeter (MMW) imaging can penetrate clothing to create interpretable imagery of concealed objects. However, the image quality is often restricted by low signal to noise ratio and temperature contrast as well as low spatial resolution. In this paper, we explore a four-channel passive MMW imaging system operating in the 8 and 3 mm wavelength regimes with linear vertical and horizontal polarization directions. Both registration between different channel images and segmentation of concealed objects are addressed. Multi-channel image registration is performed by geometric feature matching and affine transform, and then multi-level segmentation separates the human body region from the background, and concealed objects from the body region, sequentially. In the experiments, several metallic and non-metallic objects concealed under clothing are captured in indoors. It will be shown that our method can separate objects with higher accuracy than the conventional method.
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Citation
Seokwon Yeom, Dongsu Lee, Hyoung Lee, Joungyoung Son, and Vladimir P. Gushin, "Vector Clustering of Passive Millimeter Wave Images with Linear Polarization for Concealed Object Detection," Progress In Electromagnetics Research Letters, Vol. 39, 169-180, 2013.
doi:10.2528/PIERL13021907
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