Face Recognition Algorithm And Its Application In Access Control System

In the current trend of the popularization of smart homes and office networks,access control systems are also in a stage of rapid development.Faces have unique and unique biological characteristics and become new exploration directions in the development of intelligent access control systems.Although face recognition technology has many advantages and it has many applications in the access control system,there are still many deficiencies,such as facial expressions,gestures caused by changes in the process of misleading;face facial decoration Obstruction results in reduced recognition accuracy,etc.The main processes of face recognition are face detection,face image feature extraction and identification.This paper mainly researches and optimizes the algorithms of these key steps,and designs and implements a transplantable face recognition system.The following is the main research content of this article:(1)The classical face recognition algorithm is improved.In order to solve the problems of low recognition rate and long recognition time caused by the changes of facial expression and posture and facial occlusion,the classical face recognition algorithm can be encountered in the detection of facial features.In this paper,the traditional face recognition algorithm is deeply studied and studied,and the amount of computation and the speed of recognition are summed up.The advantages and disadvantages of the above three methods are combined to form a friendly face recognition algorithm for feature classification.The algorithm converts the multidimensional pattern in the feature space into one dimension,and makes the same type of samples centralized as much as possible so as to reduce the amount of computation and improve the efficiency of face recognition.(2)An intelligent door control system is built.The working principle of the system is to first capture the image information in the video with the camera,and then extract the useful feature points from the face to determine the face identity.Through experimental detection,it is proved that the system can effectively identify the identity of the person to be detected by real-time detection of face image.The average time required from face detection to face recognition is 62 ms.Even if there is a complex background with non face,the correct rate of face recognition can reach more than 98% and it can also store more than 100 face data.(3)The system to be built has good platform portability.In terms of platform operation,the system development of this article is implemented using the framework of Qt+OpenCV,and can be well transplanted between platforms.That is,one programming implementation can be compiled multiple times,and later the code can be cross-compiled and ported to the embedded the development board or Android platform,and forms a complete and applicable system.