BiSpectral Contactless Hand Based Biometric Identification Device

Biometrics plays an increasingly important role in authentication and identification systems. The process of biometric recognition allows the identification of individuals based on the physical or behavioral characteristics. Among the most common biometric features used are fingerprint, iris, face, voice, signature and hand. Hand based biometric systems exhibit many desirable characteristics when working with low resolution sensors (which are most appropriate for civil and commercial applications), including low cost sensors, acceptable indentification performance, robustness to environmental conditions and individual anomalies, and high speed identification algorithms. For higher security applications such as forensics, high resolution images are more suitable (Jain et al, 2001) (Konga et al, 2009). Most hand-based biometric schemes in the literature are based on measuring the hand silhoutte as a distinctive personal attribute for an authentication task. First it was accomplished using guiding pegs mounted on a flat surface of the imaging device (SanchezReillo et al, 2000) (Jain et al, 1999). Although the guiding pegs provide consistent measuring positions, they cause some problems as well: 1) The pegs can deform the shape of a hand (Wong & Shi, 2002) and 2) The users must be well trained to cooperate with the system. Thus, peg-free hand geometry techniques were considered giving the hand some motion freedom (Bulatov et al, 2004). There are two main approaches for geometrical features extraction; those based on measure the finger lengths and widths at various positions, palm size, etc. and another based on represent the global hand shape (Öden et al, 2003) (Yörük et al, 2006). Both approaches use the finger tip points and the finger valley points as the landmarksfor image alignment. The palm texture can be also used as biometric trait for personal identification. It can be used both by itself (Han et al, 2003) (Ribarić & Fratric, 2005) (Sun et al 2005) (Kong & Zhang, 2004) (Badrinath & Gupta, 2009) or combined with hand shape (Ribaric et al, 2003) (Li et al, 2006) (Kumar et al, 2006) (Kumar & Zhang, 2004) at score level or at representation level. Although fusion increases accuracy, it generally increases computation costs and template sizes and reduces user acceptance. Recently, perhaps due to hygiene consideration, contact-free hand biometric systems have been proposed. The two main issues to be dealt with in a contact-free system are hand segmentation and the projective distortions associated with the absence of the contact plane.