Identity Authentication Based On Facial Features And Its Application In Attendance System

The biological characteristics are the inherent attributes of human beings, which have strong self-stability and individual independency. They are the ideal source of information for ID verification. Compared with other biological characters, the patterns of face are natural and direct; therefore the technique of face verification is widely used as the main approach in ID verification. The process of facial recognition can be divided into three stages: face detection and preprocessing of face image, feature extraction and recognition. In this work, we firstly discuss the background and then analyze the main existing face recognition algorithms. With this understanding, we present the method of face matching based on personality features and layered face matching based on Active Appearance Model (AAM) and Independent Component Analysis (ICA) features. The content is described as below:(1) Firstly, we design and realize the face detecting based on the Adaboost algorithm. And the method of face image preprocessing such as gray information normalization, angle circumrotating adjusting and dimension normalization are designed and realized synchronously. In this way, the foundation is established for the feature extraction and recognition of face.(2) The method of face matching based on facial personality features is presented. In this method, the feature points are labeled automatically by using the Active Appearance Model (AAM). According to the facial geometry information, the vector of face is established. Next the method of selecting right facial personality features is given. At last, a face matching algorithm with weighted template is presented for face recognition.(3) The method of ICA features extraction of face image based on wavelet transform is presented. In this method, the face image is decomposed once to get the low band information by using wavelet transform technology. The low band images include the main information of original images. And then the features of face images are extracted by using ICA.(4) The method of layered face matching based on AAM and ICA features is presented. In the proposed method, firstly, the method of face matching based on facial personality features is used to make the first face recognition. In the condition of all faces are unaccepted, the method of face matching based on ICA features is used to make the second face recognition. In this way, the features of face shape are considered and meanwhile the features of face texture are also considered to supplement for face recognition. And it can improve the effect of face recognition.(5) The whole hard structure of attendance system based on face recognition is planned. And the function of face matching subsystem in attendance system is analyzed emphatically. A prototype system of face matching subsystem in attendance system is designed and implemented by using the object-oriented methods.