This paper proposes an edge detection scheme formillimeterwave images

which has low resolution and large noise. It introduces standard gradient strength according to statistical signal processing theory. The basic idea is to employ cubic Bspline as edge detector. Thewavelet transform results reflect the variations for images—along horizontal edges and vertical edges

which are usedwith statistical information together to get the standard gradientmagnitude. For each millimeter wave image a fixed and identical threshold is adopted to detect the image edges roughly. Finally

non2maximum suppression phase and a filter are introduced to get the specific edges. The experiment results demonstrate that the scheme is effective and feasible for detecting the edge of the hidden objects on the background of the human body

which meet the real time requirement in custom.