Design And Implementation Of Real-time Face Recognition System Based On OpenCV

With the continuous development of society and the progress of science and technology,the world is more and more people need a can quickly determine the identity authentication,face recognition for its convenient rapid,noninvasive,and so on gathering information advantage,make its application more and more common around us,now has become a scientific research one of the most popular research fields,more and more researchers into the face recognition algorithm in the study of system development.With more and more research on face recognition algorithms,the performance of face recognition system is getting better and better,and the application is becoming more and more extensive.Different to the functional requirement of the system has a different application environment,this article is based on opencv developed a camera can be the man in the video real-time face detection and face recognition of face recognition systems,there are three main interface system main interface,face input interface and face recognition interface,the operation of the system steps is simple,clear,in both the accuracy of the premise to realize the real time.Provided during the face detection module is used in the opencv,Adaboost face detector based on Haar feature of face for the face detector mistakenly identified the phenomenon of color eye secondary validation of improved face detector,the improved significantly reduces the error detection rate of face detector,and the covered face detection has a certain improvement.In addition,by collecting face images of students in the laboratory,and collecting dormitory and laboratory environment,I established my own face database and background environment data set based on the existing face database,and trained face detector on this basis.Face image after face detector intercept down from the frame,the need for image preprocessing,the facial features in a face image,and reduce the effects of environmental factors on the accuracy of face recognition,after preprocessing the image stored in the same folder name,its tag has been training classifier in face recognition module.Face recognition module is divided into feature extraction part and face matching part,feature extraction part detailed introduces the local binary pattern(LBP)feature extraction algorithm,aimed at the shortcoming of lack of LBP algorithm for image features using dual LBP algorithm was presented,and proved through the experiment in the face of samples under the condition of less than traditional LBP algorithm improved algorithm improved the accuracy of face recognition,through the experiment proves that the improved algorithm increases the accuracy of deflection Angle face recognition.The face matching part uses SVM(support vector machine)algorithm with good classification performance on small samples.The dual LBP feature extraction algorithm and SVM classification algorithm are combined to realize face recognition module.