3D Face Recognition Based on Pose Correction Using Euler Angle Method

Face recognition is one of the biometric method, to identification of given face image using main features of the face. 3D face recognition approach handles the challenges of 2D face recognition such as pose, illumination, expression, etc in a better way. The exploration of 3D face recognition is widely used for security at many places like airport, organizations, crime detection etc. uncontrolled condition of real-world biometric applications is pose which is a great challenge to any face recognition approach. Such pose variations can cause extensive occlusions, resulting in missing data. This work presents 3D face recognition method which is invariant to pose. The method handles pose correction problem with rotation matrix based on Euler angle. Further dimensionality of face image is reduced by the principal component analysis and the recognition is done by the Euclidean distance algorithm. we used GAVAB 3D face database for simulation and measured performance like Recognition rate, False acceptance rate (FAR), False rejection rate (FRR) and Equal error rate (EER) are used to evaluate performance of the method. We have achieved 1.12 % improvement in Recognition rate and 0.15% improvement in equal error rate for probes with neutral and non-neutral, respectively.