Research Of Face Detection And Recognition System Based On Video

In the modern society of rapid development, security issues have become more and more prominent, and it is necessary for customs, airports and railway stations to improve the performance of real-time monitoring identification system because of the frequent movement of people. Therefore, study on the face detection and recognition system which is based on video identification will have a special value of application and a broad prospect of development.Face detection and recognition technology is a typical biological recognition technology, it relates to a lot of scientific theories, such as artificial intelligence, image processing and so on, and it has broad research value. This paper research face detection and recognition technology deeply from three respects, which are video image processing, face detection, face feature extraction and recognition, and realize the face detection and recognition based on the dynamic video image.In the video image processing stage, the color image is converted into a gray image by using the gray scale normalization; by the method of illumination normalization, it can weak the adverse impact on the image of the light; the video images which are used to detect human face can be zoomed in and out by the method of scale normalization, so are the face images; in order to eliminate the noise of face images, the method of noise filter can be used. In the Face detection stage, the Ada Boost face detection algorithm has been researched in detail, including the Haar feature extraction, classifier training and classifier cascade; and then the face classifier has been created with a lot of face and non-face sample, and also improves the rate of face detection. In the feature extraction stage, this paper makes a special effort on study of the LBP algorithm and proposes a new Double Coding Local Binary Pattern algorithm(d-LBP) to improve the weakness of traditional LBP algorithm, such as incomplete features extraction. The improved algorithm can completely and fast extract LBP texture feature, which succeed in taking full consideration of the relationship of amplitude and mean among pixel gray values. Then, the paper uses the d-LBP algorithm combined with PCA(Principal Component Analysis) to extract statistical characteristics in each small block of the original face image and get the vector of texture feature, and it fulfills the face recognition by using K Nearest Neighbor algorithm. Finally, experiments have been done in the face database of ORL, experimental results shown that the d-LBP algorithm has a good ability of identification and improves the recognition rate in some degree.The Face detection and recognition system based o n video has been divided into face recognition module and face registered module. It has been designed and implemented in the development environment of Qt, and the experiment shows that the system has a good ability of identification, and a certain degree of robustness to posture, expression, illumination and distance.