Due to the ability of millimeter waves (mmWs) to penetrate dielectric materials, such as plastic, polymer, and clothes, the mmW imaging technology has been widely used for the detection of concealed weapons and objects. The use of mmW images has also recently been proposed for biometric person recognition to overcome certain limitations in image acquisition at visible frequencies. This paper proposes a biometric person recognition system based on the shape information extracted from real mmW images. To this aim, we report experimental results using the mmW images with different body shape-based feature approaches, such as contour coordinates, shape contexts, Fourier descriptors, and row and column profiles. We also study various distance-based and classifier-based matching schemes. Experimental results suggest the potential of performing person recognition through mmW imaging using only shape information, a functionality that could be integrated in the security scanners deployed in airports.
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