Abstract
Face Recognition [Pentland et al 1991] confronts innumerable hurdles in the form of variations in lighting conditions during image capture, Occlusions, damage in facial portions due to accidents etc. Hence recovery of the complete picture of a human face from partially occluded images is quite a challenge in Image Processing. Facial imaging proposed in this paper is the method of generating 3-D face mask of a subject. This process involves receiving one frontal image of the subject from a digital imaging device (Cameras in Smartphone, tablet or PC) and applying algorithms for edge recovery of the face. Once the face edges are detected, the light intensity incident on the face is mapped as a 3D histogram. The intensity gradients formed due to the contour [Kass et al 1998] of the face are then mapped on to the face as depth points in a grid-based space. Finally, the representation determined from the database is used to generate 3D facial data of the subject based on the best mapping.