An improved feature extraction method based on DWT and 2DSubXPCA methods

Face is one of the popular biometric used in human authentication for providing secured access. Feature reduction is a challenging task for fast and efficient recognition. Many techniques like Discrete wavelet transform (DWT), Principal component analysis (PCA) and Linear discriminant analysis (LDA) have been used for feature reduction. Some issues like pose variation, change in facial expression and poor illumination make the recognition process a difficult task. In this paper, we bring in a hybrid approach based on DWT and 2DSubXPCA for feature extraction and use nearest neighbor for classification. A maximum classification accuracy of 97.5% with highest dimensionality reduction is obtained for ORL database.