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首页> 外文期刊>International journal of imaging systems and technology >Finger Vein Recognition Using Minutia-Based Alignment and Local Binary Pattern-Based Feature Extraction
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Finger Vein Recognition Using Minutia-Based Alignment and Local Binary Pattern-Based Feature Extraction

机译：基于基于细节点的对齐和基于局部二进制模式的特征提取的手指静脉识别

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摘要

With recent increases in security requirements, biometrics such as fingerprints, faces, and irises have been widely used in many recognition applications including door access control, personal authentication for computers, Internet banking, automatic teller machines, and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins to identify individuals at a high level of accuracy. This article proposes a new finger vein recognition method using minutia-based alignment and local binary pattern (LBP)-based feature extraction. Our study makes three novelties compared to previous works. First, we use minutia points such as bifurcation and ending points of the finger vein region for image alignment. Second, instead of using the whole finger vein region, we use several extracted minutia points and a simple affine transform for alignment, which can be performed at fast computational speed. Third, after aligning the finger vein image based on minutia points, we extract a unique finger vein code using a LBR which reduces false rejection error and thus the equal error rate (EER) significantly. Our resulting EER was 0.081% with a total processing time of 118.6 ms.
机译：随着最近对安全性要求的提高，指纹，面部和虹膜等生物识别技术已广泛用于许多识别应用程序中，包括门禁控制，计算机的个人身份验证，互联网银行，自动柜员机和过境控制。手指静脉识别使用手指静脉的独特模式来高度准确地识别个人。本文提出了一种新的手指静脉识别方法，该方法使用基于细节特征的对齐和基于局部二进制模式（LBP）的特征提取。与以前的作品相比，我们的研究提出了三个新颖之处。首先，我们使用细节点（例如分叉点和指静脉区域的终点）进行图像对齐。其次，不是使用整个手指静脉区域，而是使用几个提取的细节点和简单的仿射变换进行对齐，可以快速地执行计算。第三，在基于细节点对齐手指静脉图像之后，我们使用LBR提取唯一的手指静脉代码，该代码可减少错误拒绝错误，从而显着降低等错误率（EER）。我们得到的EER为0.081％，总处理时间为118.6 ms。

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  • 作者

    Eui Chul Lee; Hyeon Chang Lee; Kang Ryoung Park;

  • 作者单位

    Department of Computer Science, Biometrics Engineering Research Center, Sangmyung University, 7, Hongji-dong, Jongno-gu, Seoul 110-743, Republic of Korea;

    Department of Electronics Engineering, Biometrics Engineering Research Center, Dongguk University, 26, Pil-dong 3-ga, Chung-gu, Seoul, Republic of Korea, 100-715;

    Department of Electronics Engineering, Biometrics Engineering Research Center, Dongguk University, 26, Pil-dong 3-ga, Chung-gu, Seoul, Republic of Korea, 100-715;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    biometrics; finger vein recognition; minutia points; alignment; LBP;

    机译：生物识别;手指静脉识别细节点对准;低血压;

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