Evaluation of performance of an active terahertz imaging system for concealed face recognition

Abstract

One of the most important problems encountered by face recognition systems is occlusions. Especially with the COVID-19 pandemic, recognition of masked faces has been attracting interest. There are proposed visible spectrum recognition algorithms, which perform the recognition task from the uncovered part of the face. However, reliability and accuracy of these algorithms does not reach the level of traditional face recognition algorithms, even though they outperform human observers. Furthermore, these approaches do not provide a solution when almost all the face area is covered. In the past, use of millimeter/submillimeter (SMMW/MMW) and terahertz (THz) imaging has been considered as an alternative to visible spectrum systems as an answer to the limitations of visible spectrum systems, such as changing lighting conditions and occlusions. In this study, several performance characteristics of an active THz imaging system operating at 340 GHz are presented for a face recognition approach based on a similarity comparison of THz face images. Here we examine the dynamic range, contrast resolution, spatial resolution, pixel resolution and noise level of the imaging system. Furthermore, analysis results performed on a set of THz images of head areas of 20 individuals are presented. Results indicate that THz imaging is sensitive to facial characteristics through clothing material which can be exploited for a biometric approach based on THz imaging for recognition of concealed faces.