一种基于脑生物识别的新方法:个体识别的一些初步结果

K. Aloui, A. Naït-Ali, M. Naceur
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引用次数: 13

摘要

大量对人脑的解剖研究表明,大脑特征在个体间存在显著差异。具体来说,提取的特征在我们的应用程序中用作识别个体的生物识别工具。为此,考虑了磁共振成像(MRI)图像。我们表明,使用MRI体积图像的单个切片,在给定的水平上获得,可以提取重要的大脑代码,可用于识别个体。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小波被考虑用于特征提取。最后,在包含脑MRI图像的Open Access Series of Imaging Studies (OASIS)数据库上对该算法进行了评估。210个分类的结果表明,对个体的识别准确率高达98.25%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel approach based brain biometrics: Some preliminary results for individual identification
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.
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