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Dorsal hand vein recognition based on directional filter bank

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Abstract

With the increasing needs of security systems, vein recognition is reliable as one of the important solutions for biometrics-based identification systems. The obvious and stable line-feature-based approach can be used to clearly describe dorsal hand vein patterns for personal identification. In this paper, a directional filter bank involving different orientations is designed to extract vein patterns and the minimum directional code is employed to encode line-based vein features into binary code. In addition, there are many non-vein areas in the vein image, which are not meaningful for vein recognition. To improve accuracy, the non-vein areas are detected by evaluating the variance of the minimum directional filtering response image and are considered as non-orientation code. In total, 4,280 dorsal hand vein images from 214 persons are used to validate the proposed dorsal hand vein recognition approach. A high accuracy (\(>\)99 %) and low equal error rate (0.54 %) were obtained using the proposed approach, which shows that the approach is feasible and effective for dorsal hand vein recognition.

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Authors and Affiliations

  1. Department of Electrical Engineering, Chinese Naval Academy, Kaohsiung, 813, Taiwan, ROC

    Jen-Chun Lee

  2. Department of Computer and Communication, China University of Technology, Hukou Township, Hsinchu County, 303, Taiwan, ROC

    Tsung-Ming Lo

  3. Department of Computer Science and Information Engineering, Chien Hsin University of Science and Technology, Jhongli, 320, Taiwan, ROC

    Chien-Ping Chang

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  1. Jen-Chun Lee
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  2. Tsung-Ming Lo
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  3. Chien-Ping Chang
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Correspondence to Jen-Chun Lee.

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Lee, JC., Lo, TM. & Chang, CP. Dorsal hand vein recognition based on directional filter bank. SIViP 10, 145–152 (2016). https://doi.org/10.1007/s11760-014-0714-8

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  • DOI: https://doi.org/10.1007/s11760-014-0714-8

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