An Efficient Method for Feature Extraction of Face Recognition Using PCA

The process of identification of a person by their facial image is the face recognition. For criminal identification, for passport verification. Face recognition approached for still image can be broadly categorized into holistic methods. This technique makes it possible to use the facial images of a person to authenticate him into a secure system. He entire raw face image as an input. Holistic methods use whereas extract local facial features and use their geometric and appearance properties feature based methods. How to build a simple yet a complete face recognition system using principal component Analysis, a holistic approach this paper describes. Linear projection to the original image space to achieve dimensionality reduction this method apply. By projective face images onto a feature space that spans the significant variations among known face images the system function. As eigenfaces do not necessarily correspond to feature such as ears, eyes and noses the significant features known. For the ability to learn and later recognize new faces in an unsupervised manner it provides. Found to be fast, relatively simple, and works well in an constrained environment this method.