This work deals with image enhacements technology for 2D faces.. Describes methods of image processing, which are used in the proposed methods. These methods eliminate inhomogeneous lighting and shadows in the face. It also suggests the detector face, which is used as input for the method to eliminate shadows.

[Non communiqué] / In the past decade, 3D statistical face model (3D Morphable Model) has received much attention by both the commercial and public sectors. It can be used for face modeling for photo-realistic personalized 3D avatars and for the application 2D face recognition technique in biometrics. This thesis describes how to achieve an automatic 3D face reconstruction system that could be helpful for building photo-realistic personalized 3D avatars and for 2D face recognition with pose variability. The first systems we propose Combined Active Shape Model for 2D frontal facial landmark location and its application in 2D frontal face recognition in degraded condition. The second proposal is 3D Active Shape Model (3D-ASM) algorithm which is presented to automatically locate facial landmarks from different views. The third contribution is to use biometric data (2D images and 3D scan ground truth) for quantitatively evaluating the 3D face reconstruction. Finally, we address the issue of automatic 2D face recognition across pose using 3D Morphable Model