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DOI: 10.14569/IJACSA.2019.0100419
PDF

Medical Image(s) Watermarking and its Optimization using Genetic Programming

Author 1: Rafi Ullah Habib
Author 2: Hani Ali Alquhayz

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 4, 2019.

  • Abstract and Keywords
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Abstract: In this paper, an medical image watermarking technique has been proposed, where intelligence has been incorporated into the encoding and decoding structure. The motion vectors of the medical image sequence are used for embedding the watermark. Instead of a manual selection of the candidate motion vectors, a generalized approach is used to select the most suitable motion vectors for embedding the watermark. Genetic programming (GP) module has been employed to develop a function in accordance with imperceptibility and watermarking capacity. Employment of intelligence in the system improves its imperceptibility, capacity, and resistance toward different attacks that can occur during communication and storing. The motion vectors are generated by applying a block-based motion estimation algorithm. In this work, Full-Search method has been used for its better performance as compared to the other methods. Experimental results show marked improvement in capacity and visual similarity as compared to the conventional approaches.

Keywords: Capacity; imperceptibility; genetic programming; image sequence; watermarking

Rafi Ullah Habib and Hani Ali Alquhayz, “Medical Image(s) Watermarking and its Optimization using Genetic Programming” International Journal of Advanced Computer Science and Applications(IJACSA), 10(4), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100419

@article{Habib2019,
title = {Medical Image(s) Watermarking and its Optimization using Genetic Programming},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100419},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100419},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {4},
author = {Rafi Ullah Habib and Hani Ali Alquhayz}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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