Multi-level segmentation of passive millimeter wave images with high cluster numbers for hidden object detection

Seokwon Yeom; Dong-Su Lee; Jung-Young Son

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Multi-level segmentation of passive millimeter wave images with high cluster numbers for hidden object detection

机译：Multi-level segmentation of passive millimeter wave images with high cluster numbers for hidden object detection

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摘要

Passive millimeter wave imaging is useful for security applications since it can detect objects concealed under clothing. However, because of the diffraction limit and low signal level, the automatic image analysis is very challenging. The multi-level segmentation of passive millimeter wave images is discussed as a way to detect concealed 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 pixels on the basis of a Gaussian mixture model. The multi-level segmentation is investigated with more than two clusters to recognize the hidden object in different parts. The performance is evaluated by the average probability error. Experiments confirm that the presented method is able to detect the wood grip of a hand ax as well as the metal part concealed under clothing.

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来源
《Optical Engineering》 |2012年第9期|091613-1-091613-5|共5页
作者
Seokwon Yeom; Dong-Su Lee; Jung-Young Son;
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作者单位

Daegu University, Division of Computer and Communication Engineering, Gyeongsan, Gyeongbuk 712-714, Republic of Korea;

Konyang University, Department of Biomedical Engineering, Nonsan, Chungnam 320-711, Republic of Korea;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类计量学;
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Multi-level segmentation of passive millimeter wave images with high cluster numbers for hidden object detection

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