Assisted Management System In Computer Labs Based On Face Recognition

Face recognition is one of the focuses of image processing and pattern recognition . Compared with the recognition of the other livings' features, it has such advantages as being convenient, fast, secret and without active cooperation. Through the researches in recent years, it has achieved a certain application achievements.The previous personnel management systems have been based on the processing of characters, data, Chinese characters. Though they included the processing of images, they were part of basic information for personnel inquiry.Face recognition for identity identification has overwhelming advantage and is used in such situations as the safety examination of airport and the test of the entrance and leaving of the border, where we need higher safety. Due to the complexity of image processing, image information hasn't been made full use of.The thesis discusses the research background and the present research status of the recognition technology of living things and face recognition as well as the methods of face recognition. The thesis focuses on several kinds of very mature recognition algorithms: Principal Component Analysis and face recognition based on Gabor Transform. The thesis uses the images base to recognize the two methods and analyses the research result. The recognition based on Gabor Transform is superior to Eigen face on recognition rate and robust. On the other hand, Eigen face has more speed. We have attempted to apply real-time image processing to assist management and applied the results of face recognition to teaching practice through applying theory into practice.The thesis also discusses the importance and the present status of management of computer labs , the present status of students as well as the advantage of face recognition for assisted identification.Assisted management system in computer labs based on face recognition has been developed. It can collect the bar code information of students through bar code scanners and make webcam collect image information at random at the same time. Compared with the data stored in students' image bases in computers, the system can recognize the face automatically and feed the results as one of the basis of identification back to the manager.