Biometrics inspired watermarking based on a fractional dual tree complex wavelet transform

In this paper, a novel biometrics inspired watermarking technique is proposed. For this purpose, a newly proposed mathematical transform, namely the fractional dual tree complex wavelet transform (FrDT-CWT), and singular value decomposition (SVD) are used. The core idea is to use biometrically generated keys in the embedding process of a gray-scale watermark. Therefore, this paper first proposes a method for generating keys from biometrics efficiently. The host image is first randomized by Hessenberg decomposition and a chaotic map, followed by embedding in the FrDT-CWT domain by modifying the singular values of the randomized image. Further, in order to prevent the ambiguity problem of SVD-based techniques, a verification step is introduced to verify the watermarked image. Finally, a reliable extraction process is proposed to extract the watermark from the possibly attacked watermarked image after verification. The security, attack, and comparative analysis confirms the high security, efficiency, and robustness of the proposed watermarking technique. Highlights? A novel biometrics inspired watermarking technique is proposed. ? The watermark is embedded in a fractional dual tree complex wavelet transform domain using SVD. ? A method is also proposed to generate keys from biometrics efficiently. ? To prevent the ambiguity problem of SVD-based techniques, a verification step is casted. ? The security, attack, and comparative analysis confirms the high security, efficiency, and robustness of the proposed technique.