Face recognition using improved fast PCA algorithm

The Principal Component Analysis (PCA) is one of the most successful techniques that have been used to recognize faces in images. However, high computational cost and dimensionality is a major problem of this technique. There is evidence that PCA can outperform over many other techniques when the size of the database is small. In this paper, a fast PCA based Face Recognition Algorithm is proposed. In the proposed algorithm the database is sub grouped using some features of interest in faces. Only one of the obtained subgroups is provided to PCA for recognition. The performance of the proposed algorithm is tested on Indian face database, and the obtained results show an improvement in performance of the proposed algorithm as compared to the same with PICA method.