Optimization of Three-dimensional Face Recognition Algorithms in Financial Identity Authentication

  • Cong Luo Guizhou University of Finance and Economics, Guiyang, Guizhou, China
  • Xiangbo Fan Guizhou University of Finance and Economics, Guiyang, Guizhou, China
  • Ying Yan Guizhou University of Finance and Economics, Guiyang, Guizhou, China
  • Han Jin Guizhou University of Finance and Economics, Guiyang, Guizhou, China
  • Xuan Wang Guizhou University of Finance and Economics, Guiyang, Guizhou, China


Identity authentication is one of the most basic components in the computer network world. It is the key technology of information security. It plays an important role in the protection of system and data security. Biometric recognition technology provides a reliable and convenient way for identity authentication. Compared with other biometric recognition technologies, face recognition has become a hot research topic because of its convenience, friendliness and easy acceptance. With the maturity and progress of face recognition technology, its commercial application has become more and more widespread. Internet finance, e-commerce and other asset-related areas have begun to try to use face recognition technology as a means of authentication, so people’s security needs for face recognition systems are also increasing. However, as a biometric recognition system, face recognition system still has inherent security vulnerabilities and faces security threats such as template attack and counterfeit attack. In view of this, this paper studies the application of threedimensional face recognition algorithm in the field of financial identity authentication. On the basis of feature extraction of face information using neural network algorithm, K-L transform is applied to image high-dimensional vector mapping to make face recognition clearer. Thus, the image loss can be reduced.


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How to Cite
LUO, Cong et al. Optimization of Three-dimensional Face Recognition Algorithms in Financial Identity Authentication. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 17, n. 3, mar. 2022. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/3744>. Date accessed: 22 may 2022. doi: https://doi.org/10.15837/ijccc.2022.3.3744.


Face Recognition, Principal Component Analysis, BP Neural Network, Three-dimensional Face