Hand-based authentication is a key biometric technology with a wide range of potential applications both in
industry and government. Traditionally, hand-based authentication is performed by extracting information from
the whole hand. To account for hand and finger motion, guidance pegs are employed to fix the position and
orientation of the hand. In this paper, we consider a component-based approach to hand-based verification. Our
objective is to investigate the discrimination power of different parts of the hand in order to develop a simpler,
faster, and possibly more accurate and robust verification system. Specifically, we propose a new approach which
decomposes the hand in different regions, corresponding to the fingers and the back of the palm, and performs
verification using information from certain parts of the hand only. Our approach operates on 2D images acquired
by placing the hand on a flat lighting table. Using a part-based representation of the hand allows the system to
compensate for hand and finger motion without using any guidance pegs. To decompose the hand in different
regions, we use a robust methodology based on morphological operators which does not require detecting any
landmark points on the hand. To capture the geometry of the back of the palm and the fingers in suffcient
detail, we employ high-order Zernike moments which are computed using an effcient methodology. The proposed
approach has been evaluated on a database of 100 subjects with 10 images per subject, illustrating promising
performance. Comparisons with related approaches using the whole hand for verification illustrate the superiority
of the proposed approach. Moreover, qualitative comparisons with state-of-the-art approaches indicate that the
proposed approach has comparable or better performance.
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