Face and ear fusion recognition based on multi-agent

Data fusion is one of the most important problems in current image processing field. Non-invasive characteristic of ear and profile face recognition contrary to other biometric recognition, unique ear features and ubiety about face and ear of 3D human head ensure the feasibility for fusing face and car recognition. A new approach in decision fusion is proposed, the method uses less data than other fusion and has a faster recognition rate. The fusion based on face and car recognition is a meaningful attempt to explore a novel method of biometric recognition. Eyes are parallel to the recognition process of facial patterns, but actual computer architecture is serial. At present, multi-biometrics authentication systems have not a uniform frame construction. The process of 3D face recognition is described by using recent multi-agent System theory for the first time. A multi-agent face recognizing structure model(MAFRSM) for 3D face recognition is proposed. Experiment data show that the MAFRSM can effectively enhance 3D face recognition rate.