Indoor Passive Millimeter-Wave Imaging for Concealed Object Detection

Abstract

Passive millimeter-wave (PMMW) imaging is an effective technique for concealed objects detection. A PMMW imaging system optimized for corresponding with indoor surroundings is developed and tested. The metal is deposited on the surface of carbon fiber by chemical plating process and the temperature contrast between the human body and concealed objects can be improved by adding the metal deposited carbon fiber to concealed objects. An image enhancement algorithm is proposed on the basis of the combination of wavelet transformation and top-hit transformation, and the experiment results demonstrate that the algorithm proposed is highly efficient for the indoor passive millimeter-wave images. Furthermore, Lucy-Richardson iterative, restricted least square algorithm and user-defined palliative module filtering are combined to process the detecting images, and then the edge detection can be effectively realized using Canny arithmetic operator.