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Fast Finger Vein Recognition Based on Sparse Matching Algorithm under a Multicore Platform for Real-Time Individuals Identification

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Laboratory of Technological Research in Pattern Recognition (LITRP), Universidad Católica del Maule, Talca 3480112, Chile
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Department of Computer Science and Industries, Faculty of Engineering Science, Universidad Católica del Maule, Talca 3480112, Chile
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Universidad Tecnólogica de Chile INACAP, Sede Talca 3480063, Chile
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Department of Basic and Technological Sciences, Universidad Nacional de Chilecito, Chilecito, La Rioja 5360, Argentina
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Author to whom correspondence should be addressed.
Symmetry 2019, 11(9), 1167; https://doi.org/10.3390/sym11091167
Received: 28 August 2019 / Revised: 6 September 2019 / Accepted: 10 September 2019 / Published: 15 September 2019
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. View Full-Text
Keywords: individuals identification; finger vein recognition; sparse matching; multicore algorithm individuals identification; finger vein recognition; sparse matching; multicore algorithm
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Hernández-García, R.; Barrientos, R.J.; Rojas, C.; Soto-Silva, W.E.; Mora, M.; Gonzalez, P.; Frati, F.E. Fast Finger Vein Recognition Based on Sparse Matching Algorithm under a Multicore Platform for Real-Time Individuals Identification. Symmetry 2019, 11, 1167.

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