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A novel approach based brain biometrics: Some preliminary results for individual identification

机译:一种基于方法的脑生物学学学学学学学学学学学学学学学学研究:个人识别的一些初步结果

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Numerous anatomical studies of the human brain have shown a significant inter-individual variability of brain characteristics. Specifically, the extracted characteristics are used in our application as a biometric tool to identify individuals. For this purpose, Magnetic Resonance Imaging (MRI) images are considered. We show that using a single slice from an MRI volumetric image, acquired at a given level, one can extract significant brain codes that can be used for the purpose to identify individuals. Explicitly, the proposed biometric approach uses some coding techniques that are commonly employed for iris identification. Specifically, 1D log Gabor Wavelet has been considered for feature extraction. Finally, the proposed algorithm is evaluated on the Open Access Series of Imaging Studies (OASIS) database containing brain MRI Images. Results using 210 classes show that high accuracy of 98.25% to identify individuals are obtained.
机译:人脑的许多解剖学研究表明了脑特征的显着间间可变异性。 具体地,提取的特性用于我们的应用中作为识别个体的生物识别工具。 为此目的,考虑磁共振成像(MRI)图像。 我们表明,使用从给定水平获取的MRI容量图像的单个切片,可以提取可用于识别个体的重要大脑代码。 明确地,所提出的生物识别方法使用一些常用于虹膜识别的编码技术。 具体地,已经考虑了1D对数Gabor小波进行特征提取。 最后,在含有脑MRI图像的开放访问系列(OASIS)数据库上评估所提出的算法。 使用210类的结果显示,获得了98.25%的高精度来识别个体。

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