Implementation of Dual Tree Complex Wavelet Transform Approach for Secured Biometric Application

Abstract

Biometrics-based authentication systems offer obvious usability advantages over traditional password and token-based authentication schemes. However, biometrics raises several privacy concerns. A biometric is permanently associated with a user and cannot be changed. Hence, if a biometric identifier is compromised, it is lost forever and possibly for every application where the biometric is used. Moreover, if the same biometric is used in multiple applications, a user can potentially be tracked from one application to the next by cross-matching biometric databases. In this paper, we demonstrate several methods to generate multiple cancellable identifiers from fingerprint images to overcome these problems. Designing of a novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. We outlined several advances that originated both from the cryptographic and biometric community to address this problem. In particular, we outlined the advantages of cancellable biometrics over other approaches and presented a case study of different techniques. This project can be enhanced by reducing the image using DTCWT. This modification can decrease the image size and execution can be reduced by enhancing the image clarity. This enhancement can be shown using PSNR values.