In all face recognition and face detection research, to enhance recognition accuracy with the increased speed is a rapid identification of common research goals. In order to achieve this goal, entering the image and pre-processing steps are very important. A good input image quality and pre-processing can greatly enhance the follow-up identification accuracy. In this paper, facial features are used to determine the rotation angle of the face. And using this angle to calculate the angle of the face is in order to make judgments for the recognition system. Face location can be identified with color region cuttings and oval face detections. Captured facial images, based on the use of features of vertical concentration, determine the angle and direction of rotation face. The simulation calculation method is developed for obtaining the face value of each feature point, and calculating three-dimensional model of a virtual face by volume spline interpolation. After detecting the rotation and adding the virtual database, we can achieve the best classification rate and maximum angle in the limited information.
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