Abstract
The presented study concerns detection and recognition of hidden objects covered with various types of clothing by using passive imagers operating in a terahertz (THz) range at 1.2mm (250GHz). The aim of this study is to propose a detection and classification algorithm operating robustly at a high processing speed. The paper briefly describes properties of the THz spectrum, theoretical limitations, performance of the imager, and physical properties of fabrics in a wide range of frequencies. Two methods have been presented, trained, and tested using a dataset with various configurations in sessions each lasting 30min. During experiments, different clothes and hidden objects have been combined. The paper presents a comparison of robust detection and recognition methods for concealed objects using a multiframe single-shot detector and region-based fully convolutional networks. The comparison of the original results of various experiments is presented.
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