Fusion of Visual and Thermal Face Recognition Techniques: A ...

1. Introduction
Face recognition has developed over 30 years and is still a rapidly growing research
area due to increasing demands for security in commercial and law enforcement
applications. Although, face recognition systems have reached a significant level of
maturity with some practical success, face recognition still remains a challenging
problem due to large variation in face images.
Face recognition is usually achieved through three steps: acquisition, normalization
and recognition. Acquisition includes the detection and tracking of face-like images in a
dynamic scene. Normalization includes the segmentation, alignment and normalization of
the face images. Finally, recognition includes the representation and modeling of face
images as identities, and the association of novel face images with known models. In
order to realize such a system, acquisition, normalization and recognition must be
performed in a coherent manner.
The performance of face recognition systems varies significantly according to the
environment where face images are taken and according to the way user-defined
parameters are adjusted in several applications. Recognition based only on the visual
spectrum remains limited in uncontrolled operating environments such as outdoor
situations and low illumination conditions. Visual face recognition also has difficulty in
detecting disguised faces, which is critical for high-end security applications. The thermal
infrared (IR) spectrum comprises mid-wave infrared (MWIR) (3-5µm), and long-wave
infrared (LWIR) (8-12µm), all longer than the visible spectrum (0.4-0.7µm). Thermal IR
imagery is independent of ambient lighting since thermal IR sensors only measure the
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