Face Recognition using Enhanced Energy of Discrete Wavelet Transform

The face recognition problem is made difficult by the great variability in head rotation and tilt, lighting intensity and angle, facial expression, aging, partial occlusion (e.g. Wearing Hats, scarves, glasses etc.), etc. In this paper multi scale technique Discrete Wavelet Transform is used for preprocessing. The complexity is reduced by reducing the size of the image to 1 by 4. Discrete Wavelet Transform is applied to face images and divided into four blocks and the energy of each block is calculated. Block energy is maximized and enhanced image is obtained. In this paper K Means clustering algorithm is used to cluster the pixels in face image obtained from preprocessing step. Binary threshold is applied in the clusters. The performance of the proposed method is tested using Fuzzy K Nearest Neighbour classifier and face recognition accuracy rate is computed. Testing is done using ORL face database.