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New biometric approach based on geometrical humain brain patterns recognition: Some preliminary results

机译:基于几何人脑模式识别的新生物识别方法:一些初步结果

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In this paper, we describe a new biometric approach based on geometrical characteristics of brain shape. Specifically, we use these geometrics characteristics as a biometric feature 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 many significant geometrical descriptors related to inter-individual variability of brain shape that can be also used to identify individuals. Explicitly, the proposed biometric approach combines two main phases. In the first phase, features extraction (FE) are achieved in order to obtain brain geometrical descriptors vector, called in this work GDB vector. A second phase is called similarity measurement (SM). Finally, the proposed algorithm is evaluated on the Open Access Series of Imaging Studies (OASIS) database containing brain MRI Images. Results using 220 classes show that high accuracy of 98.76% to identify individuals are obtained.
机译:在本文中,我们描述了一种基于大脑形状的几何特征的新生物识别方法。具体来说,我们将这些几何特征用作生物特征来识别个人。为此,考虑了磁共振成像(MRI)图像。我们显示,使用以给定级别获取的MRI体积图像中的单个切片,可以提取出许多与大脑形状的个体差异有关的重要几何描述符,这些描述符也可以用来识别个体。明确地说,所提出的生物识别方法结合了两个主要阶段。在第一阶段,实现特征提取(FE)以获取大脑几何描述符矢量,在本文中称为GDB矢量。第二阶段称为相似度测量(SM)。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220个类别的结果表明,识别个人的准确率高达98.76%。

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