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Representation of Dorsal Hand Vein Pattern Using Local Binary Patterns (LBP)

机译:使用局部二进制模式(LBP)表示手背静脉模式

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In this revolutionized and digital world, the increasing need of security to protect individuals and information has led to a rise in developing biometric systems over traditional security systems such as pin-code and password. Finding more reliable, practical and more acceptable biometrics and techniques are attracting the attention of researchers. Recently, hand vein pattern biometrics has gained increasing interest from both research communities and industries. Researchers are exploiting the different biometric phases by applying existing techniques or devising new ones to develop enhanced biometric systems. Up to now, most researchers have thinned the dorsal hand vein pattern and apply corresponding techniques for feature representation and matching. However, not many techniques have been explored with relation to considering the whole hand vein image. In this research work, local binary pattern, which is a powerful technique for representing texture description of an image, have been applied on dorsal hand vein images. This method outperforms existing vein representation techniques by having a recognition rate of 98.4% on a database of more than 1000 images. In addition, this proposed method has no effect on rotated images, which is desirable in any biometric security system.
机译:在这个革命性的数字世界中,对保护个人和信息的安全性的日益增长的需求导致与传统的安全系统(例如密码和密码)相比,开发生物识别系统的需求有所增加。寻找更可靠,实用和可接受的生物特征和技术正吸引研究人员的注意力。最近,手静脉模式生物识别技术引起了研究界和行业的越来越多的关注。研究人员正在通过应用现有技术或设计新技术来开发增强的生物识别系统,从而探索不同的生物识别阶段。迄今为止,大多数研究人员已经使手背静脉细化,并应用了相应的技术进行特征表示和匹配。然而,关于考虑整个手静脉图像,尚未探索许多技术。在这项研究工作中,局部二值模式是一种用于表示图像纹理描述的强大技术,已应用于手背静脉图像。该方法在超过1000张图像的数据库上具有98.4%的识别率,优于现有的静脉表示技术。另外,该提出的方法对旋转的图像没有影响,这在任何生物统计安全系统中都是期望的。

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