Multi-level segmentation of passive millimeter wave images with Gaussian mixture modeling

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

doi:10.1117/12.883778

25 May 2011 Multi-level segmentation of passive millimeter wave images with Gaussian mixture modeling

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

Proceedings Volume 8023, Terahertz Physics, Devices, and Systems V: Advance Applications in Industry and Defense; 80230D (2011) https://doi.org/10.1117/12.883778
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

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.

Citation Download Citation

Seokwon Yeom, Dong-Su Lee, and Jung-Young Son "Multi-level segmentation of passive millimeter wave images with Gaussian mixture modeling", Proc. SPIE 8023, Terahertz Physics, Devices, and Systems V: Advance Applications in Industry and Defense, 80230D (25 May 2011); https://doi.org/10.1117/12.883778

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