Parallelizing Image Processing Algorithms for Face Recognition on Multicore Platforms

Abstract

A good face detection system should have the ability to identify objects with varying degrees of illumination and orientation. It should also be able to respond to all the possible variations in the image. The image of the face depends on the relative camera face pose such as the nose and one eye, which can fledge partially or completely. The appearance of a face is directly influenced by the facial expression of a person and partially occluded by objects around it. One of the most important and necessary conditions for face recognition is to exclude the background of reliable face classification techniques. However, the face can appear in complex backgrounds and different positions. The face recognition system can mistake some areas of the background for faces. In this paper solve some face recognition problems include segmenting, extracting, and identifying facial features that are thought to face from the background.