Study On Face Recognition Technology Based On Embedded Access Control System

With the progress of the society, the technology of security and protection is receiving more and more attention, access control system has become an essential part of security and protection system.With the development of automatic identification technology, access control system is developing rapidly. RFID technology and biometric identification technology have become the mainstream of modern access control technology, now.Compared with other human biological characteristics, the use of facial features for authentication is the most natural and most direct means, and is easily accepted by the user.In this paper, we discuss face recognition technology for embedded access control system, which consists of three main components: face detection, feature extraction and face recognition. We proposed a two-dimensional principal component analysis face recognition algorithms based on wavelet transform.Firstly, we studied face detection methods based on multiple classifier cascades, in order to achieve the face location in the system. The experimental results show that the method has good accuracy.Secondly, we studied the wavelet transform in image processing applications and used the wavelet decomposition and reconstruction algorithm for image processing to remove noise and reduce the dimension, etc.Finally, feature extraction and recognition is a key part of the face recognition system. In this paper, 2DPCA face recognition algorithms based on wavelet transform and the nearest neighbor classifier based on the within-class average distance are proposed, the effectiveness is verified in the standard ORL face database.