Zhao, Pengyang;
Chen, Zhiquan;
Xue, Jing-Hao;
Feng, Jianjiang;
Yang, Wenming;
Liao, Qingmin;
Zhou, Jie;
(2022)
Single-Sample Finger Vein Recognition via Competitive and Progressive Sparse Representation.
IEEE Transactions on Biometrics, Behavior, and Identity Science
10.1109/tbiom.2022.3226270.
(In press).
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Abstract
As an emerging biometric technology, finger vein recognition has attracted much attention in recent years. However, single-sample recognition is a practical and longstanding challenge in this field, referring to only one finger vein image per class in the training set. In single-sample finger vein recognition, the illumination variations under low contrast and the lack of information of intra-class variations severely affect the recognition performance. Despite of its high robustness against noise and illumination variations, sparse representation has rarely been explored for single-sample finger vein recognition. Therefore, in this paper, we focus on developing a new approach called Progressive Sparse Representation Classification (PSRC) to address the challenging issue of single-sample finger vein recognition. Firstly, as residual may become too large under the scenario of single-sample finger vein recognition, we propose a progressive strategy for representation refinement of SRC. Secondly, to adaptively optimize progressions, a progressive index called Max Energy Residual Index (MERI) is defined as the guidance. Furthermore, we extend PSRC to bimodal biometrics and propose a Competitive PSRC (C-PSRC) fusion approach. The C-PSRC creates more discriminative fused sample and fusion dictionary by comparing residual errors of different modalities. By comparing with several state-of-the-art methods on three finger vein benchmarks, the superiority of the proposed PSRC and C-PSRC is clearly demonstrated.
| Type: | Article |
|---|---|
| Title: | Single-Sample Finger Vein Recognition via Competitive and Progressive Sparse Representation |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/tbiom.2022.3226270 |
| Publisher version: | https://doi.org/10.1109/tbiom.2022.3226270 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Veins, Fingers, Training, Dictionaries, Biometrics (access control), Lighting, Indexes |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10161895 |
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