Study On Techniques And Applied System For Face Detection And Recognition Based On Information Fusion

Biometrics, a kind of technology in personal identification system, is the totally brand-new, safe, reliable and effective technique, that is different from traditional method, because it use physical and behavior characteristic of human body such as fingerprint, iris, face, handprint, writing or voice. Human face is the most popular pattern and the most easily accepting method in the daily life, so person's face identification is becoming the most promising one of the verification methods. Learned the domestic and international discourse and research papers concerning face detection and recognition in recent years, some theories problem to computer identify technique to person's face is analyzed. Aim at establishing the personal identification system for mobile video; using the idea of information fusion, the dissertation brings forward a face detection and recognition method. Experiments prove the method in this dissertation is reasonable, and have great value in theories and practice. The textual main research work primarily includes:1. Via domestic and international research productions at face detection, the dissertation bring forward a detection method aim at mobile video, in which back-ground separating based movement detection, color and Symmetry based features fusion, mosaic and neural network are used synthetically. In this method, knowledge based method and statistic based method is synthetically. This method realizes information fusion on feature level and decision level in which mixed structure that can split the difference of speed and recognition rate is used. Experiments prove the method in this dissertation is reasonable, effective.2. On the base of research on multifarious methods, the dissertation studied face recognition method based on hidden Markov model (HMM). On foundation of some improvement in HMM method, the dissertation first decompose face image to four son images by wavelet transform,second make use of the decomposition images to establish HMM modules respective, at the last acquire the result use decision fusion. Because of better expression of statistical features, this method acquire better recognition rate. The dissertation use optimal discriminate vectors based method to solve the reject rate problem HMM based method. The test on some face database proves that this method can increase recognition rate.3. On the base of research on information fusion, the dissertation analyze the speed of multi-classifier and bring forward the method that can split the difference of speed and recognition rate, believe analysis. The dissertation analyzes classical vote method in decision fusion and brings forward improved method. Experiments prove that the method can heighten the recognition rate and robust.4. With the research on Biometrics based application system and application design experiences of mine, the dissertation analyze corporation human resource and check system design process, software engineering, blue print design and database design is mainly discussed.