Journal
IET BIOMETRICS
Volume 9, Issue 3, Pages 118-125Publisher
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-bmt.2019.0016
Keywords
feature extraction; vein recognition; image resolution; medical image processing; cryptography; reliability; image denoising; image restoration; sophisticated acquisition devices; high-resolution imaging; PVR system; low-resolution imaging; multiframe super-resolution algorithms; query imaging; low-resolution imaging devices; palm vein recognition system; contactless biometric identification method; image acquisition; feature extraction; pre-processing component; authentication method; informative palm vein patterns; noise suppression
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Palm vein recognition (PVR) refers to the contactless biometric identification method that uses palm vein patterns to confirm the identity of a person. Compared with other methods, PVR has received a wide attention because it provides more secure results. The veins, being located inside the human body, make PVR robust against tempering and changes in morphology of body features. Most PVR systems integrate four stages: image acquisition, pre-processing, feature extraction, and decision. The first two stages determine accuracy of the final identification results. Focusing on the pre-processing component, we discovered that the available approaches fail to generate more informative vein patterns by simultaneously suppressing noise and blur, and also by recovering semantically useful features (edges, contours, and lines) from the acquired images. This weakness calls for sophisticated acquisition devices that make PVR systems costly. In this work, we have proposed multiframe super-resolution (MSR) as a pre-processing stage to improve performance of the traditional PVR systems. MSR exploits information from multiple images of the same scene to reconstruct a high-resolution image. This technique signals the possibility of using inexpensive low-resolution imaging devices demanded by the traditional PVR systems. Experiments show that our method outperforms most classical methods.
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