Research on Multimode Biometric Features Recognition System Adopting Neural Network

ABSTRACT

The small sample issue is a common problem in face recognition system, and multi-modal model has strong generalization ability to solve the problem of small sample, which has already become the most important area of research in pattern recognition, however, the low accuracy and efficiency of the model has become a major challenge. Based on this, this paper proposes a efficient multimode biometric face and fingerprint recognition system based on neural network, which provides more efficient identification though choosing a good feature extraction and recognition algorithms. The Adoption of biometric recognition to authenticate a person's identity has greatly improved operational efficiency and the recognition accuracy in comparison with adoption of password or passphrase. The feasibility and effectiveness of the method in this paper has been verified in multimode biometric system database.

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