Abstract
In this paper we apply a novel approach to near-infrared subcutaneous palm vascular pattern authentication. The proposed method relies on a recursive algorithm based on a positive linear dynamical system whose evolution depends on the two matrices representing the vein patterns to be compared. The output of the system reaches a high value when a good matching between the two matrices is observed, otherwise it converges rapidly to zero, even in presence of noise. With respect to another algorithm we recently introduced, this approach achieves not only a better authentication performance but also a drastic reduction in terms of computation time. These improvements are demonstrated by means of extensive experiments conducted on challenging datasets.
Highlights
With the rapid growth in demand for reliable and highly secure human authentication and identification systems, the importance of technological solutions and algorithms in the biometric field is growing along with security awareness [12]
DATABASES USED IN SIMULATION The performance of the proposed palm vascular pattern authentication system has been tested upon the Polytechnic University (PolyU)
Inspired by our previous study [25], which adopts a dynamic algorithm tailored to palmprint features acquired in the visible electromagnetic spectrum rather than in the near-infrared, we have proposed a novel dynamical system approach achieving significantly improved performance over the earlier proposed system ensuring greater reliability thanks to its higher discriminating power which allows to recognise a subject with ease, even if the templates are highly corrupted by noise
Summary
With the rapid growth in demand for reliable and highly secure human authentication and identification systems, the importance of technological solutions and algorithms in the biometric field is growing along with security awareness [12]. The subcutaneous vascular pattern of the human body is unique to every individual, even between identical twins [14], does not vary during the course of a person’s life, and lies underneath the human skin ensuring confidentiality and robustness to counterfeiting, as opposed to other intrinsic and extrinsic biometric traits that are more vulnerable to spoofing, leading to important security and privacy concerns [15]. D. Palma et al.: Dynamic Biometric Authentication Algorithm for NIR Palm Vascular Patterns.
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