Facial Recognition is a primary branch of Pattern Recognition used to distinguish faces based on feature variation. All the objects in the universe has a proper arrangement termed as “pattern”, thus every human face has a unique pattern. Those patterns are identified or verified by Recognition process. Especially Facial Recognition done manually is a trouble-free process whereas recognizing a face using computers is a knotty task because of illumination, occlusions, facial expression and pose. The input for the recognition face can be in any digital sources such as image or video from the face database. Therefore the key features of the face such as brows, eyes, nose and mouth serves as input. In order to achieve utmost accuracy in facial recognition in digital images different feature extraction techniques are used in Facial Recognition. Feature based and Appearance based complexities like feature extraction and illumination for automated computer vision recognition is discussed. This paper evaluates feature extraction techniques in a broad perspective.

Facial Recognition, Feature Extraction, Illumination, Appearance Based, Recognition Rate

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