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Robust hybrid descriptors for multi-instance finger vein recognition

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Abstract

Finger vein recognition is a type of biometric technology that uses the vein pattern inside the human finger as a personal identifier. In this paper, Local Hybrid Binary Gradient Contour (LHBGC) and Hierarchical Local Binary Pattern (HLBP) are proposed as the texture descriptors for finger vein recognition to increase the discriminant capability of the finger vein texture. LHBGC extracts both sign and magnitude components of the finger vein image for recognition, while HLBP utilizes the LBP uniform texture pattern of the vein image without any training required. Furthermore, a multi-instance biometrics that fuses multiple evidences from an individual has also been proposed to address the problem of noisy data. Multi-instance biometrics is the most inexpensive way to obtain multiple biometric evidences from a biometric trait without multiple sensors and additional feature extraction algorithms. Experiments on several benchmark databases validate the efficiency of the proposed multi-instance approach. An equal error rate as low as 0.00002% is achieved using the combination of three fingers at score level fusion.

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Acknowledgements

Our thanks to the Group of Machine Learning and Applications, Shandong University and University Sains Malaysia for allowing us to use the SDUMLA-HMT and FV-USM Finger Vein Database they had collected. The project is supported in part by MOSTI Science Fund Malaysia (01-02-01-SF0217).

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Authors and Affiliations

  1. Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450, Melaka, Malaysia

    Thian Song Ong, Ardianto William, Tee Connie & Michael Kah Ong Goh

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  1. Thian Song Ong
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  2. Ardianto William
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  3. Tee Connie
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  4. Michael Kah Ong Goh
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Corresponding author

Correspondence to Tee Connie.

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This study involved human participants in finger vein data collection. Informed consent had been obtained prior to the data collection process. All documents pertaining to the data collection process had been submitted to the Springer Online Submission System.

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Ong, T.S., William, A., Connie, T. et al. Robust hybrid descriptors for multi-instance finger vein recognition. Multimed Tools Appl 77, 29163–29191 (2018). https://doi.org/10.1007/s11042-018-6077-3

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  • DOI: https://doi.org/10.1007/s11042-018-6077-3

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