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

机译:一种基于大脑生物特征识别的新颖方法:用于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:人类大脑的许多解剖学研究表明,大脑特征的个体间差异很大。具体而言,提取的特征在我们的应用程序中用作识别个人的生物统计工具。为此,考虑了磁共振成像(MRI)图像。我们表明,使用MRI体积图像中的单个切片(在给定级别上获取),可以提取出有意义的大脑代码,这些代码可用于识别个人。明确地说,提出的生物识别方法使用了一些通常用于虹膜识别的编码技术。具体来说,一维对数Gabor小波已被考虑用于特征提取。最后,在包含大脑MRI图像的影像研究开放获取系列(OASIS)数据库上对提出的算法进行了评估。使用210个类别的结果表明,识别个人的准确率高达98.25%。

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