Abstract
Identity recognition is a research hotspot in the information age. Nowadays, more and more occasions require identity recognition, especially in smart home. Identity recognition of the head of the household can avoid many troubles, such as home identification and network information authentication. Nowadays, in smart home identification, especially based on face recognition, system authentication is basically through feature matching. Although this method is convenient and quick to use, it lacks intelligence. Nowadays, for the make-up, facelift, posture, and other differences, the accuracy of the system is greatly reduced. In this paper, the face recognition method is used for identity authentication. Firstly, the AdaBoost learning algorithm is used to construct the face detection and eye detection classifier to realize the detection and localization of the face and eyes. Secondly, the two-dimensional discrete wavelet transform is used to extract facial features and construct a personal face dynamic feature database. Finally, an improved elastic template matching algorithm is used to establish an intelligent classification method for dynamic face elasticity models. The simulation shows that the proposed method can intelligently adapt to various environments without reducing the accuracy.
Highlights
With the rapid development of computer and network technology, the influence of the Internet has penetrated into various fields of social life
Traditional identity authentication methods mainly rely on identity identification items such as keys, certificates, and cards and identity identification knowledge such as user name and password
The research and improvement of face recognition technology can promote the development of biometric technology and lay a good foundation for the application of a more accurate and reliable identity authentication system based on face features
Summary
With the rapid development of computer and network technology, the influence of the Internet has penetrated into various fields of social life. As the first barrier to network security and information system security, identity authentication technology has received more and more attention in the information security era. Traditional identity authentication methods mainly rely on identity identification items such as keys, certificates, and cards and identity identification knowledge such as user name and password. Once identity identification items and identification knowledge are stolen or forgotten, their identity is easy to be impersonated by others. With the development of cyber fraud and attack technology, higher requirements are placed on the accuracy, security, and reliability of the identity authentication method. Traditional identity authentication methods can no longer meet this requirement, and some human biometric features such as fingerprints, irises, sounds, and facial images provide a reliable solution for identity authentication because of their uniqueness and lifetime invariance
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