Face recognition using Kekre's wavelets energy & performance analysis of feature vector variants

Biometric authentication technologies are based on measurable physiological or psychological characteristics of human beings. Face is one of the important physiological biometrics traits. Wavelets are useful in multi-resolution analysis of images, they are very good option for analyzing texture feature of images. In this paper a new family of wavelets called as kekre's wavelet is used for multiresolutoin analysis of face images. Different variants of feature vectors are generated and their performance for face recognition is analyzed. The analysis shows that kekre's wavelets are faster than Haar wavelets and the feature vector based on these wavelets gives good accuracy.