Real-time concealed object detection and recognition in passive imaging at 250 GHz.

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 1.2 mm (250 GHz). 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 30 min. 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.