Mid-wave IR face recognition systems

Today’s military threats are different from those of the recent past. The organizations and skills necessary to develop efficient operations against such threats are not the same as even 10 years ago. The present-day army requires diverse capabilities to operate in the modern combat environment, and one of the high-demand skills of soldiers is the ability to detect and track humans as well as identify them. Face-based recognition (FR) is popular with the military for establishing human identity, because it has several advantages over other biometric traits: it is non-intrusive, understandable, and a facial image can be captured in a covert manner at variable standoff distances. Although varying factors such as illumination, cosmetics, and facial disguise can hinder FR performance, one of the biggest challenges is the ability to recognize a person in both dayand night-time environments. To mitigate such a challenge, FR operation in the IR spectrum (active and passive) has become increasingly important. The IR spectrum is comprised of the active IR band (near-IR or short-wave IR, SWIR), and the thermal (passive) IR band. The passive IR band is further divided into the mid-wave (MWIR) and long-wave IR (LWIR) bands. The MWIR range is 3–5 m, whereas the LWIR range is 7–14 m. Both MWIR and LWIR cameras can sense temperature variations across human faces at a distance and produce thermograms in the form of 2D images. However, although both pertain to the thermal spectrum, they reveal different image characteristics of the facial skin (note that, in fact, thermal cameras are categorized as MWIR or LWIR). The difference between MWIR and LWIR is that MWIR has both reflective and emissive properties, whereas LWIR consists primarily of emitted radiation. There are three main advantages of MWIR over the active IR band. First, MWIR imagery can be acquired without any external illumination in day or night environments, while regions in the active IR band Figure 1. Sample face images in the (a) visible and (b) mid-wave IR (MWIR) bands after geometric normalization is applied. (c) MWIRbased features extracted using our proposed method.1