Face Recognition using Principal Component Analysis: A Survey
Face Recognition is a reliable biometric system. Face recognition by principal component analysis (PCA) involves identification of face parts and compares them, against images stored in a data Base. Based on different types of methodologies, a detailed survey on PCA has been provided. To recognize a face, PCA methods use correlation between column, row or pixel data. PCA methods can be linear or non-linear subspace, can be two dimensional or three dimensional. PCA based image identification is simple, fast and more accurate as compared to other face recognition techniques. PCA identifies primary features from a face that represents an image.
Keywords - Face Recognition, Principal Component Analysis.