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Deep Patch Matching For Hand Vein Recognition

Published: 10 May 2019 Publication History

Abstract

Hand vein recognition for personal identification has attracted considerable attention from scholars due to the uniqueness of vein pattern and nearly impossible forgery. However, recognition can be difficult to obtain when remarkable discrepancies exist in vein images caused by inconstant hand poses during imaging. This study proposes deep patch matching methodology (DPM) for hand vein recognition to solve significant differences in vein images. The proposed method calculates the similarity map of each circle patch based on vessel-enhanced filters using convolution. All similarity maps are further aggregated to calculate image similarity using max-pooling. The proposed algorithm is evaluated using public NCUT part A database. The recognition rate of the proposed algorithm is 99.71%. Experimental results reveal that the proposed algorithm obtains the highest accuracy among existing methods.

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  1. Deep Patch Matching For Hand Vein Recognition

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    ICMSSP '19: Proceedings of the 2019 4th International Conference on Multimedia Systems and Signal Processing
    May 2019
    213 pages
    ISBN:9781450371711
    DOI:10.1145/3330393
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • Shenzhen University: Shenzhen University
    • Sun Yat-Sen University

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 10 May 2019

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    Author Tags

    1. Circle patch
    2. Deep patch matching
    3. Hand vein recognition
    4. Patch similarity map

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    • Research-article
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    Funding Sources

    • National Key Research and Development Program of China
    • National Science Foundation Program of China

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    ICMSSP 2019

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