Experimental Study on Image Interpolation for Concealed Object Detection

Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people away from the system. However, the image often suffers from low image quality due to the diffraction limit and low signal level. In the paper, we discuss four image interpolation methods to recognize objects hidden in the clothing of a person. The first method is the bi-cubic with Gaussian smooth filtering, the second is the Lagrangian, the third is the cubic spline, and the last is the Weighted Essentially Non-Oscillatory (WENO) interpolation. In the experiment, a person hiding a metallic gun in the clothing is captured by the passive MMW system. The experimental results show the interpolation methods can enhance the gun object for segmentation and recognition.