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

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.