Biometrics is the science of recognizing identity of a person based on the physical or behavioral attributes. Retina blood vessels have high degree of uniqueness; this makes retina recognition systems as an emerging security and authentication mechanism. Also, retinal vessels help in detection of numerous eye diseases and play an important role in automatic retinal disease screening systems. Wavelets are very good in extracting localized texture information in digital images. This book explores a new and faster type of wavelets called Kekre wavelets for extracting feature vector from retina. This book further verifies the feasibility of using Kekre wavelets to extract spectral features of the retina blood vessels and use them for verification. Multilevel decomposition is performed and feature vectors are matched using Euclidian distance and Wavelet Energy Entropy for retina match. The book demonstrates the efficacy of wavelet transform to decompose the retina image in a hierarchical framework image signal frequency to represent the retina image. The simplicity and efficacy of Kekre wavelets opens up its use in several digital image processing applications.