生物识别
判别式
人工智能
计算机科学
模式识别(心理学)
神经影像学
稳健性(进化)
特征(语言学)
鉴定(生物学)
模式
特征提取
计算机视觉
神经科学
心理学
生物
植物
基因
生物化学
哲学
社会学
语言学
社会科学
化学
作者
Kamel Aloui,Amine Naït‐Ali,Mohamed Saber Naceur
标识
DOI:10.1016/j.patrec.2017.10.001
摘要
Considering the evolution of neuroimaging in the medical field, some new emerging biometric modalities become interesting and promising candidates to recognize persons. These modalities are considered as a part of “Hidden Biometrics” which consists in using clinical measurements and medical imaging for recognition purpose. The main motivation in using hidden biometrics is the fact that system attacks may be extremely difficult to consider. This specificity highly contributes in increasing the robustness in terms of person verification and identification. In this paper, we deal with a novel non-invasive approach to recognize persons by extracting a brain signature, called “brainprint”. In particular, we explored the brain cortical regions of volumetric brain MRI (Magnetic Resonance Imaging) images, acquired from 220 healthy subjects. For each subject, four 3D cortical surfaces are considered, then transformed into 2D cortical folds maps. From the resulting textures, brainprints are constructed by extracting features using Wavelet Gabor Transform. These brainprints are considered in this work as a discriminative signature of the brain. In terms of performance evaluation, we show that an EER = 2.90 ± 0.47 is reached for verification mode. On the other hand, when dealing with identification, the proposed approach allows a recognition rate of 99.6%.
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