Research on Intelligent Algorithm of Identity Authentication Based on Facial Features

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.