Title
Fast Finger Vein Recognition Based on Sparse Matching Algorithm under a Multicore Platform for Real-Time Individuals Identification.
Abstract
Nowadays, individual identification is a problem in many private companies, but also in governmental and public order entities. Currently, there are multiple biometric methods, each with different advantages. Finger vein recognition is a modern biometric technique, which has several advantages, especially in terms of security and accuracy. However, image deformations and time efficiency are two of the major limitations of state-of-the-art contributions. In spite of affine transformations produced during the acquisition process, the geometric structure of finger vein images remains invariant. This consideration of the symmetry phenomena presented in finger vein images is exploited in the present work. We combine an image enhancement procedure, the DAISY descriptor, and an optimized Coarse-to-fine PatchMatch (CPM) algorithm under a multicore parallel platform, to develop a fast finger vein recognition method for real-time individuals identification. Our proposal provides an effective and efficient technique to obtain the displacement between finger vein images and considering it as discriminatory information. Experimental results on two well-known databases, PolyU and SDUMLA, show that our proposed approach achieves results comparable to deformation-based techniques of the state-of-the-art, finding statistical differences respect to non-deformation-based approaches. Moreover, our method highly outperforms the baseline method in time efficiency.
Year
DOI
Venue
2019
10.3390/sym11091167
SYMMETRY-BASEL
Keywords
Field
DocType
individuals identification,finger vein recognition,sparse matching,multicore algorithm
Affine transformation,Combinatorics,Pattern recognition,Artificial intelligence,Invariant (mathematics),Biometrics,Finger vein recognition,Multi-core processor,Blossom algorithm,Mathematics
Journal
Volume
Issue
Citations 
11
9
0
PageRank 
References 
Authors
0.34
0
7