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A Supervised Hybrid Methodology for Pose and Illumination Invariant 3D Face Recognition
2012
International Journal of Computer Applications
The 2D face recognition systems encounter difficulties in recognizing faces with illumination variations. The depth map of the 3D face data has the potential to handle the variation in illumination of face images. The view variations are handled by using the moment invariants. Moment Invariants are used as rotation invariant features of the face image. For feature matching an efficient fuzzy-neural technique is proposed. The PCA components of normalized depth map and Moment invariants on mesh
doi:10.5120/7537-474
fatcat:suoy6tto6bbkbhmm5uy3bhum5m