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首页> 外文会议>2017 15th International Conference on Quality in Research : International Symposium on Electrical and Computer Engineering >Palm vein recognition by using modified of local binary pattern (LBP) for extraction feature
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Palm vein recognition by using modified of local binary pattern (LBP) for extraction feature

机译：通过修改局部二值模式（LBP）进行提取特征的手掌静脉识别

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摘要

Palm vein recognition is developing biometric identification technology. It can be used in physical security and information security for selective control of access to a place or resource. A palm vein recognition has been gaining research interest from last few years because it use physiological intrinsic that uniqueness, stability, not easily spoofed and damaged and have live body identification. There are consists of the following steps: Image acquisition from the database and Pre-Processing, Finding of Region of interest, Extraction of Palm Vein pattern Features and Matching. Prior to the palm vein recognition, vein extraction is generally required for a better recognition. In this paper we propose a vein extraction method modified of the Local Binary Pattern (LBP) combining with Probabilistic Neural Network (PNN) for matching. The aim of the proposed system is to improve the accuracy of palm vein recognition. Simulation result show that the proposed method has a higher recognition rate for palm vein recognition comparing to the other basic Local Binary Pattern.
机译：掌静脉识别技术正在发展生物识别技术。它可以用于物理安全性和信息安全性中，以选择性地控制对位置或资源的访问。近年来，手掌静脉识别技术由于其独特，稳定，不易被欺骗和破坏且具有活体识别功能的生理特性而获得了研究兴趣。包括以下步骤：从数据库中获取图像并进行预处理，查找感兴趣区域，提取棕榈静脉图案特征并进行匹配。在手掌静脉识别之前，通常需要抽出静脉以获得更好的识别。在本文中，我们提出了一种结合局部神经网络（LBP）和概率神经网络（PNN）进行改进的静脉提取方法。提出的系统的目的是提高手掌静脉识别的准确性。仿真结果表明，与其他基本的本地二值模式相比，该方法对掌静脉的识别率更高。

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