A REVIEW PAPER ON MEDICAL IMAGE WATERMARKING FOR COPYRIGHT PROTECTION BASED ON VISUAL CRYPTOGRAPHY USING GENETIC ALGORITHM
Journal Title: International Journal of Engineering Sciences & Research Technology - Year 30, Vol 5, Issue 7
Abstract
A method for creating digital image copyright protection is proposed in this paper. The proposed method in this paper is based on visual cryptography using Genetic Algorithm. The proposed method is working on selection of random pixels from the original digital image instead of specific selection of pixels. In today’s scenario protection of digital data is utmost necessary in every part of life. More robust methods are being developed to protect the proprietary rights of the multimedia. In this paper, an invisible watermarking technique is proposed, to embed multiple binary watermarks into digital medical images based on the concept of Visual Cryptography (VC). The proposed scheme embeds the watermarks without modifying the original host image. Multiple watermarks can be embedded as shares in the same image. In addition, the size of the watermarks is not restricted to being smaller than that of the original host image. Experimental results prove that, the output of proposed watermarking technique gives good similarity ratio, peak signal to noise ration and correlation coefficient. To improve the visual quality of the extracted watermark we use Genetic Algorithm. This relationship keeps the marked image coherent against diverse attacks even if the most significant bits of randomly selected pixels have been changed by attacker as we will see later in this paper. Experimental results show the proposed method can recover the watermark pattern from the marked image even if major changes are made to the original digital image. The Medical Image Watermarking is implemented using Image Processing Toolbox within Matlab Software. This work has been tested and found suitable for its purpose.
Authors and Affiliations
Ms. Satbirkaur
Keywords
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- EP ID EP143933
- DOI 10.5281/zenodo.56919
- Views 107
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