Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/21292
Title: Contactless and pose invariant biometric identification using hand surface
Authors: Kanhangad, V
Pathak, A 
Zhang, D 
Keywords: 3-D hand geometry
3-D Palmprint
Contactless palmprint
Dynamic Fusion
Hand biometrics
SurfaceCodes
Issue Date: 2011
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on image processing, 2011, v. 20, no. 5, 5620980, p. 1415-1424 How to cite?
Journal: IEEE transactions on image processing 
Abstract: This paper presents a novel approach for hand matching that achieves significantly improved performance even in the presence of large hand pose variations. The proposed method utilizes a 3-D digitizer to simultaneously acquire intensity and range images of the user's hand presented to the system in an arbitrary pose. The approach involves determination of the orientation of the hand in 3-D space followed by pose normalization of the acquired 3-D and 2-D hand images. Multimodal (2-D as well as 3-D) palmprint and hand geometry features, which are simultaneously extracted from the user's pose normalized textured 3-D hand, are used for matching. Individual matching scores are then combined using a new dynamic fusion strategy. Our experimental results on the database of 114 subjects with significant pose variations yielded encouraging results. Consistent (across various hand features considered) performance improvement achieved with the pose correction demonstrates the usefulness of the proposed approach for hand based biometric systems with unconstrained and contact-free imaging. The experimental results also suggest that the dynamic fusion approach employed in this work helps to achieve performance improvement of 60% (in terms of EER) over the case when matching scores are combined using the weighted sum rule.
URI: http://hdl.handle.net/10397/21292
ISSN: 1057-7149
EISSN: 1941-0042
DOI: 10.1109/TIP.2010.2090888
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