Biometric Watermarking Technique Based on CS Theory and Fast Discrete Curvelet Transform for Face and Fingerprint Protection

Abstract

Nowadays, multibiometric system is employed to overcome limitation of the unimodal biometric system. The problem associated with multibiometric system is to design technique which offers security for biometric data. A biometric watermarking technique using compressive sensing (CS) theory and Fast Discrete Curvelet Transform is proposed for face and fingerprint protection. Compressive sensing has provided computational security to watermark fingerprint image and used for generation of sparse measurements of the watermark fingerprint image. This proposed watermarking technique embeds sparse measurements of the watermark fingerprint image into high frequency curvelet coefficients of host face image. The quantitative measure such as a structural similarity index measure is used for cross verification between original watermark fingerprint image and reconstructed fingerprint image. The watermarked face image and reconstructed watermark fingerprint image are formed face-fingerprint based multibiometric system which is used for two levels of verification of individuals. The experimental results demonstrate that proposed watermarking technique does not affect verification and authentication performance of multibiometric system.