Secure multi-spectral hand recognition system
Mauricio Ramalho, Sanchit Singh, Paulo Lobato Correia, Luís Ducla Soares · 2011
This paper proposes a secure multimodal biometric recognition system with a multi-level fusion architecture. A multi-spectral cam-era is used to capture hand images in the visible and in the near-infrared (NIR) bands of the spectrum. The system uses four biome-tric traits from the user's hands: palmprint (PP), finger surface (FS), hand geometry (HG) and palm veins (PV), being the latter captured in the near-infrared band. In the feature extraction stage, three different techniques (i.e., Orthogonal Line Ordinal Features, Competitive Code and PalmCode) are implemented to extract fea-tures from the palmprint, finger surface and palm veins. The result-ing features are then converted to binary in order to apply a secure template storage scheme, consisting of a cryptographic hash func-tion combined with an error-correcting code. In the proposed sys-tem architecture, the hand geometry is used as a database indexing trait to reduce the search time needed for identification. Recogni-tion results, obtained using a proprietary database that was built for that purpose, are presented for different combinations of the feature extraction techniques on the various biometric traits, as well as for different fusion methods. 1.