A Novel Facial Recognition Method using Discrete Wavelet Transform Multiresolution Pyramid

Necessity for the facial recognition methods is increasing now-a-days as large number of applications need it.  While implementing the facial recognition methods the cost of data storage and data transmission plays a vital role.  Hence facial recognition methods require image compression techniques to full fill the requirements.  Our paper is based on the discrete wavelet transform multiresolution pyramid.  Various resolutions of the original image with different image qualities can be had without employing any image compression techniques.  Principal Component Analysis is used to measure the facial recognition performance using various resolutions of the image.  Facial images for testing are selected from standard FERET database. Experimental results show that the low resolution facial images also performs equal to the higher resolution images.  So instead of using all the available wavelet coefficients, the minimum number of coefficients representing the lower resolution can be used and there is no need of image compression.