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Erschienen in:
2020 | OriginalPaper | Buchkapitel
An Identity Identification Method for Multi-biometrics Fusion
verfasst von : Yingli Wang, Yan Liu, Hongbin Ma, Xin Luo, Danyang Qin
Erschienen in: Communications, Signal Processing, and Systems
Verlag: Springer Singapore
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Abstract
In order to improve the reliability and security of biometric-based identity authentication system and reduce the risk of unauthorized access caused by forgery feature attacks, this paper proposes a method for identifying the identity of visitors. The method is based on D-S evidence theory. The palm print and palm vein are used as authentication features. Firstly, the same collection device is used to collect palm print and palm vein images under different wavelengths of light source and extract the HOG features of the image; then, use the one-vs-one multi-classification method of SVM to classify different individuals, and finally, using the D-S fusion strategy at the decision-making level to improve the security and accuracy of the identity authentication system. Through many experiments, the recognition rate of decision-making layer fusion is above 98%, which confirms the effectiveness of the proposed method.