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A semi-blind HVS based image watermarking scheme using elliptic curve cryptography

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Abstract

In the present paper, an advanced encryption technique commonly known as Elliptic Curve Cryptography (ECC) is used to embed a binary image as a watermark in five grayscale host images in a semi-blind manner. The ECC algorithm is a fast encryption technique which successfully encrypts the subject with significantly less number of bits as compared to other popular encryption algorithms such as Rivest-Shamir-Adleman (RSA) and Direct Selling Association (DSA). In the proposed watermarking scheme, embedding in the grayscale host images is carried out in DWT-SVD domain. First, entropy based Human Visual System (HVS) parameters are computed block wise to identify the most appropriate blocks in spatial domain. First level DWT is computed for these selected blocks and watermark embedding is carried out by using the calculated Singular Value Decomposition (SVD) parameters. Preliminary results of this work show that proposed scheme outperforms the other similar schemes carried out in DCT-SVD domain without using any encryption method. It is concluded that the use of DWT-SVD hybrid architecture along with the fast encryption technique ECC is responsible for better performance in present case. In the second part of this simulation, an established HVS model working in DCT domain is implemented and compared with the entropy based HVS model implemented in transform domain to embed the ECC encrypted binary watermark in images. In this case also, proposed scheme performs better both in terms of visual imperceptibility and robustness as compared to other scheme. It is concluded that HVS parameters – Luminance, Contrast and Edge Sensitivity are better placed in comparison to entropy parameters to examine image features and characteristics for watermarking purpose.

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Gupta, R., Mishra, A. & Jain, S. A semi-blind HVS based image watermarking scheme using elliptic curve cryptography. Multimed Tools Appl 77, 19235–19260 (2018). https://doi.org/10.1007/s11042-017-5351-0

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  • DOI: https://doi.org/10.1007/s11042-017-5351-0

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