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دسته بندی:
شبکه های عصبی - Neural Networks
سال انتشار:
2019
عنوان انگلیسی مقاله:
Parallel score fusion of ECG and fingerprint for human authentication based on convolution neural network
ترجمه فارسی عنوان مقاله:
همجوشی امتیاز موازی ECG و اثر انگشت را برای احراز هویت انسان بر اساس شبکه های عصبی کانولوشن
منبع:
Sciencedirect - Elsevier - Computers & Security, 81 (2019) 107-122: doi:10:1016/j:cose:2018:11:003
نویسنده:
Mohamed Hammad a , b , Kuanquan Wang
چکیده انگلیسی:
Biometrics have been extensively used in the past decades in various security systems and
have been deployed around the world. However, all unimodal biometrics have their own
limitations and disadvantages (e.g., fingerprint suffers from spoof attacks). Most of these
limitations can be addressed by designing a multimodal biometric system, which deploys
over one biometric modality to improve the performance and make the system robust to
spoof attacks. In this paper, we proposed a secure multimodal biometric system by fusing
electrocardiogram (ECG) and fingerprint based on convolution neural network (CNN). To the
best of our knowledge, this is the first study to fuse ECG and fingerprint using CNN for human
authentication. The feature extraction for individual modalities are performed using
CNN and then biometric templates are generated from these features. After that, we have
applied one of the cancelable biometric techniques to protect these templates. In the authentication
stage, we proposed a Q-Gaussian multi support vector machine (QG-MSVM) as
a classifier to improve the authentication performance. Dataset augmentation is successfully
used to increase the authentication performance of the proposed system. Our system
is tested on two databases, the PTB database from PhysioNet bank for ECG and LivDet2015
database for the fingerprint. Experimental results show that the proposed multimodal system
is efficient, robust and reliable than existing multimodal authentication algorithms.
According to the advantages of the proposed system, it can be deployed in real applications
Keywords: Authentication | CNN | ECG | Fingerprint | Multimodal biometrics | MSVM
قیمت: رایگان
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