Multi-Level Segmentation for Concealed Object Detection with Multi-Channel Passive Millimeter Wave Imaging.

Passive millimeter wave (MMW) imaging can create interpretable imagery of objects concealed under clothing. Unfortunately, low signal to noise ratio and low temperature resolution make automatic analysis of passive MMW images difficult. In this paper, we analyze passive MMW images generated by 8 mm regime MMW. The imaging system is composed of two channels: one with linear horizontal polarization and the other with linear vertical polarization. Both registration between horizontal and vertical polarization images and segmentation of concealed objects are addressed. Registration is performed by geometric feature matching and affine transform, while multi-level segmentation separates the human body region from the background, and concealed objects from the body region, sequentially. Experiments measuring average error probability show that our method separate objects with higher accuracy than the conventional method with a single channel image. [ABSTRACT FROM PUBLISHER]