Abstract:

Active millimeter-wave near-filed human imaging is a means for concealed objects detection. A method of concealed objects detection in the usage of active millimeter-wave images is presented as a result of image characteristics which include high resolution, characteristics varying in different parts of the human, imaging influenced among human, concealed objects and other objects, and difficulties in concealed objects detection. By dividing images according to human regional characteristics, this method applies image adaptive threshold segmentation and re-extraction with the mathematical morphology to detect concealed objects. The experiments of concealed objects on images of actual acquisition are conducted with a result of accurate rate 84.13% and false alarm rate 6.61%, illustrating the effectiveness and practicality of the proposed method.