An Enhanced Face Recognition System Based on Rotated Two Dimensional Principal Components
Face has been one of the widely used modality from very beginning of biometrics recognition technology because of its worldwide acceptability. It is easy to capture and easy to process. On literature study it is found that one of widely used feature extraction technique i.e. principal component analysis has been improved by two dimensional principal component analysis. But it is still required improvement. In this paper, 2DPCA is tried to improve by adopting rotated Two Dimensional Principal Component Analysis. This R2DPCA (Robust Two Dimensional Principal Component Analysis) algorithm is applied over different face databases to check it performance.