Research On HMM Based Face Detection And Face Recognition System

An accurate automatic personal identification is critical to a wide range of application domains such as access control, electronic commerce, and welfare benefits disbursement. Traditional personal identification methods (e.g., passwords, PIN) suffer from a number of drawbacks and are unable to satisfy the security requirement of our highly inter-connected information society.Facial images are probably the most common biometric characteristic in order to make a personal identification. Face recognition is one of the most active research areas ranging from static, controlled mug shot verification to dynamic, uncontrolled face identification, in a cluttered background. Face recognition is a non-intrusive technique and people generally do not have any problem in accepting face as a biometric characteristic.In this paper, the current research, methods and trend on face detection and face recognition were introduced firstly. Main content of this paper includes face detection in color space and face recognition based on HMM (Hidden Markov Model). In the paper, we try to integrate the technique of skin color model, template match and HMM and the theory of intelligent image processing in computer vision, and puts forward and realizes a set of method and algorithm that are valuable for practical face recognition system.Face detection is the first important step in a fully automatic human face recognition system. Skin color has been proven to be a useful and robust cue for face detection, localization and tracking .In this paper we presented a algorithm based on skin-color detection. Tanking to the skin color's trait, this algorithm has a good robust for images containing human faces with some poses, different lighting conditions and complex scenes. In the course of image preprocessing, the noise in face images was removed by using light compensation and median filter. The method of skin color and two-eye template were used.A hidden Markov model method (HMM) was used to recognize face in our recognition system. The element of HMM was introduced firstly. Then the recognition method based on HMM, the model of face and the training scheme were expatiated.Finally, an automated face recognition simulation system was established which mainly included video input module, face detection module and face recognition module. A face database was constructed. Several Exterior conditions (e.g. light condition, the screen angle of the object and the distance of the object) were tested by experiments. The results show that the system has reached expected goals in time complexity and recognition rate.The results of experiment indicate that the new methods of the technology of human face detection and recognition were available.