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DOI: 10.14569/IJACSA.2019.0100301
PDF

LSB based Image Steganography by using the Fast Marching Method

Author 1: Xiaoli Huan
Author 2: Hong Zhou
Author 3: Jiling Zhong

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 3, 2019.

  • Abstract and Keywords
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Abstract: This paper presents a novel approach for image steganography based on the Least Significant Bit (LSB) method. Most traditional LSB methods choose the initial embedding location of the cover image randomly, and the secret messages are embedded sequentially without considering the image pixels’ values and positions. Our approach utilizes the user-selected seeds in the cover image to avoid the smooth/flat areas where cause a higher detection rate. Then the fast marching method is used to calculate T (the time of arrival of the front of the seeds) and propagate the seeds by computational dynamics. The front propagation process decides the embedding positions of the secret messages. The same algorithm can be used to retrieve the hidden information as well. The coordinates of the seeds are used as the shared key only known to the sender and receiver to add additional security protection. Peak Signal to Noise Ratio (PSNR) is evaluated to measure the quality of resulting images. The experiments show that the proposed approach generates results with high payload capacity and satisfied imperceptibility.

Keywords: Image steganography; LSB; the fast marching method; coordinates; PSNR

Xiaoli Huan, Hong Zhou and Jiling Zhong, “LSB based Image Steganography by using the Fast Marching Method” International Journal of Advanced Computer Science and Applications(IJACSA), 10(3), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100301

@article{Huan2019,
title = {LSB based Image Steganography by using the Fast Marching Method},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100301},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100301},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {3},
author = {Xiaoli Huan and Hong Zhou and Jiling Zhong}
}



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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