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The robustness and security of the biometric watermarking approach can beimproved by using a multiple watermarking. This multiple watermarking proposedfor improving security of biometric features and data. When the imposter triesto create the spoofed biometric feature, the invisible biometric watermarkfeatures can provide appropriate protection to multimedia data. In this paper,a biometric watermarking technique with multiple biometric watermarks areproposed in which biometric features of fingerprint, face, iris and signatureis embedded in the image. Before embedding, fingerprint, iris, face andsignature features are extracted using Shen-Castan edge detection and PrincipalComponent Analysis. These all biometric watermark features are embedded intovarious mid band frequency curvelet coefficients of host image. All fourfingerprint features, iris features, facial features and signature features arethe biometric characteristics of the individual and they are used for crossverification and copyright protection if any manipulation occurs. The proposedtechnique is fragile enough; features cannot be extracted from the watermarkedimage when an imposter tries to remove watermark features illegally. It can usefor multiple copyright authentication and verification.

A Watermarking Technique Using Discrete Curvelet Transform for Security of Multiple Biometric Features