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Authentication of Individuals based on Wrist Vein Images by Extracting Phase of Fractional Fourier Transform

机译:通过提取分数傅里叶变换的阶段,基于手腕静脉图像的个人认证

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Nowadays, biometric systems play a main role in personal information protection. Each person has a distinct pattern of wrist veins that can be used for authentication. Fractional Fourier transform (FrFT) changes signal to complex form. In this paper, FrFT was utilized for the time-frequency analysis of images. After the pre-processing stage and extracting veins from the background, the phase of FrFT coefficients was computed for each image. The PUT database was used in the proposed method for verifying individuals. This database consists of 1200 wrist and 1200 palm vein images. In this paper, wrist vein images were only utilized. Receiver Operating Characteristic (ROC) and Support Vector Machine (SVM) were used for feature selection and classification, respectively. The results showed that wrist vein images can be used for verification and FrFT is a capable tool for feature extraction as the average accuracy was obtained 99.65±0.95% in the operating point.
机译:如今,生物识别系统在个人信息保护中发挥着主要作用。每个人都有一个独特的腕静脉模式,可用于认证。分数傅里叶变换(FRFT)将信号变为复杂的形式。本文利用了FRFT进行了图像时频分析。在预处理阶段和从背景中提取静脉之后,为每个图像计算FRFT系数的相位。 Put数据库用于验证个人的提议方法。该数据库由1200名手腕和1200掌静脉图像组成。在本文中,腕静脉图像仅利用。接收器操作特征(ROC)和支持向量机(SVM)分别用于特征选择和分类。结果表明,腕静脉图像可用于验证,FRFT是特征提取的能力工具,因为在工作点中获得了平均精度99.65±0.95%。

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